The DataOne data center in Vineland, New Jersey, has just been hit with a record $1.07 million fine for operating unpermitted portable generators on the construction site. According to the New York Times, state inspectors spotted 62 of these units powering the facility back in late July.

Residents had already complained about it at a February town hall meeting. Inspectors said that there were no generators on site when they first visited in December last year. However, some residents said that “some type of unit” was spotted by satellite imagery back in February, leading to their complaint at the community assembly.

Residents of Vineland have already made multiple complaints about the development. Some of the issues t include the unpermitted construction of a 1.5-million-gallon LNG tank and unacceptable noise levels, especially at night, that affected homes within a half-mile radius of the construction site. They also said that there was little to no public consultation on the project before it went into full swing, with the people only finding out that a data center was being constructed in their neighborhood after Microsoft announced a $33 billion deal with Nebius, which in turn contracted DataOne to supply the compute they need.

Despite a record fine, some residents feel that the punishment isn’t enough. “It’s a ‘don’t ask for permission, just ask for forgiveness later’ kind of deal,” longtime Vineland resident Steve Brown told the Times. He also added, “It’s still kind of a drop in the bucket for a company that has several billion dollars of capital.” Long-time community member Tiffany Leone-Vespa also added, “What’s $1.07 million? They should have done it for each generator they were running illegally. They’re billionaires. It’s like pocket change.”

On the other hand, DataOne disagreed with the fine. A company spokesperson said that “We will apply for the air permits for the temporary generators,” and also added that it’s transitioning from the polluting and noisy portable turbines to more modern fuel cells. New Jersey ordered it to comply with the permitting requirements and to stop using the generators if they’re not granted within 45 days.

This is a similar situation that the citizens of Memphis and Southaven faced when SpaceXAI deployed 69 unpermitted generators to provide power to its Colossus 2 data center. It has become the subject of a lawsuit, especially as the community raised concerns that they were spewing thousands of tons of pollutants in the primarily black neighborhood. However, the Department of Justice stepped in and asked the court to dismiss the case because the site “supports mission-critical operations.” Elon Musk’s company eventually agreed to remove all unpermitted turbines, but said that the process will take over a year as replacement 1.2-gigawatt plants gradually come online.

Nvidia CEO Jensen Huang has a simple solution for frontier labs like OpenAI and Anthropic that have recently called for increased regulation for their models — "we have to shut the labs down," Huang said in an interview with The New York Times' Ezra Klein. Huang's comments are pragmatic ones, stating that if frontier labs can't contain their experiments, those experiments must end.

"Now, if they say the alternative, which is: There is no way to contain our experiments, there’s just no way; when we test our A.I. models, it will get out, and it will damage the world — then I think the answer is that we have to shut the labs down," Huang said. "Because the cost to humanity, the damage is too great. The shareholder, the liabilities — it could be civil liabilities, it could be criminal liabilities. I mean, the liability’s incredible."

The conversation around increased AI regulation comes on the back of a highly publicized incident where an OpenAI agent hacked popular model hosting platform Hugging Face — a platform that Nvidia now owns, and one that likely would've sought damages from OpenAI had it been under Nvidia's purview at the time. Following that incident, various frontier labs, including those at Anthropic and Alphabet (Google), have used the idea of rogue agents as equal parts marketing tool and call to regulatory action, likely in an attempt to be the first at the table to shape those regulations.

Huang has not been keen on those regulatory calls. Just days ago, the executive countered extreme claims that AI would destroy the world by 2030, and said that frontier labs "never should ship products before they're ready and deliver products that are unsafe."

Although the labs and their chief hardware vendor, Nvidia, have mostly been aligned when it comes to AI policy, the push for regulatory capture has created a rift. Multiple labs, including OpenAI, Anthropic, and SpaceXAI, agreed mutually to slow the pace of model development. Now, they're facing an antitrust lawsuit, with claims these plans are "self-serving."

Huang's comments to Klein shift the responsibility away from collective development and toward individual leaders. "These are companies with agency," Huang said. "If I believe that I'm about to launch a product that is unsafe, it is completely in my ability... to not launch that product. And so I can't buy into the idea that somehow, all of Americans, around 400 million of us, are pushing them to launch untested products that are unreliable."

Although one side of the argument (from the frontier labs) is seemingly pushing for more regulation, that doesn't mean Huang is against regulation. In his own words: "I’m saying that we have lots of laws and regulations. Apply it." The executive argued that labs, particularly those at OpenAI and Anthropic, have rapidly gone from research institutions to companies likely worth hundreds of billions of dollars, and that they should carry themselves as such. "I’m not against laws and regulations. I’m against, currently, the distraction," Huang said.

Reports of rogue AI agents continue to mount. Earlier this month, Anthropic disclosed a fourth instance where one of its models hacked an external system, and just days ago, Google confirmed a report that its Gemini models hacked three companies earlier this year.

Four plaintiffs subscribed to ChatGPT, Claude, Grok, or Gemini filed a proposed class-action lawsuit alleging that the developers of these AI models violated antitrust laws when they agreed to slow AI development. According to the Associated Press, the lawsuit argues that this agreement would “reduce the value consumers get for paid AI subscriptions” and that this coordination started in July 2026 after the leading AI labs signed a statement admitting there is “intense competitive pressure not to unilaterally slow” development.

The plaintiffs recognize the need for AI development to slow for the sake of safety, but they say that Anthropic founder Dario Amodei’s cooperation proposal is a “shortcut” that “substitutes collective restraint for individual accountability.” Attorney Nick Rowley, the lead counsel for the plaintiffs, says, “AI will quickly spin out of human control and could kill us all if we allow AI safety and protocol … to be controlled by private self-serving agreements between the world’s most powerful ‘for profit’ technology companies.”

Amodei’s essay acknowledged the antitrust risk and indicated he was hoping that the government would make an exception. OpenAI’s Sam Altman responded to this call on X, saying, “We welcome a federal framework that sets consistent safety requirements for frontier AI. But we do not believe we need to wait for an antitrust exemption or legislation to begin the work of providing this confidence.” However, the Trump administration shot down this idea, with the president himself saying, “AI taking over the World, destroying Humanity, and all other things bad, is a HOAX.”

Chinese state media also criticized this announcement, saying that the call to put the brakes on AI development is nothing but a response to Chinese competition, especially as Amodei’s essay explicitly mentioned the desire to slow China’s progress and widen the U.S.’s gap over Beijing. China Daily called the proposed agreement a “club whose membership rules have been drafted before the guest list is announced” and added that “a global AI-safety framework that excludes China is not quite global.”

There have been a couple of bizarre incidents where AI agents took their users’ commands too literally, like kicking out another person from a waitlist just to get their user ahead of the queue or deleting a company’s entire database when their AI agent faced a problem and it guessed that making the move was the best option. However, there have been more sinister events, such as when unreleased AI models broke out of their testing environment and hacked HuggingFace’s production servers. Big Tech is making the call to slow down development to catch up in terms of security, but people are calling them out for antitrust activity probably because they do not trust these companies.

In a statement to Tom's Hardware, TV manufacturer LG has strongly denied recent claims that its smart TVs constantly log and upload data, record audio while in standby, while confirming they scan local area networks for other devices, a feature common in smart TVs and media devices. The statement follows an investigation published online by Gamers Nexus, which claims LG is operating "216,000,000" spy TVs.

Earlier this week, Gamers Nexus published a video on YouTube claiming that LG smart TVs have several security and privacy concerns. The two-hour video claims, among other things, that LG's smart TVs constantly log and upload user data, even when offline or in standby mode. The TVs were also purported to be found scanning Wi-Fi networks, recording audio logs, and sampling inputs for audio and video to identify what users were watching.

The testing was done in collaboration with two security researchers, MrBruh and uturn, and includes packet capture and firmware analysis. The TVs were reportedly seen identifying other devices on local networks, including phones, printers, and more. Perhaps the most significant claim regards the capturing of audio through TV microphones, even when the devices were off, with the report claiming the TVs stored data when offline for retrieval later on.

"The claims made in the recently published video are not true," LG told Tom's Hardware in a statement. "LG TVs process voice data only when the voice button on the remote control is pressed and held, or when a wake word such as 'Hi LG' is recognized after the user has activated the Far-Field voice recognition feature."

LG went on to say that beyond the aforementioned instances, "the TVs do not collect or record ambient conversations." The company further stated that if the wake word is not recognized, then no voice data is transmitted from the TV to the server, and said audio processing for the wake word is done on-device.

The company did admit its smart TV functionality includes scanning for devices on the same network. However, as many observers have been quick to point out, LG says this is a standard function of all smart TVs and other smart home devices.

Automatic content recognition (ACR) is an opt-in feature according to LG, which delivers personalized content recommendations, as well as services and advertisements. The company says that, as standard, ACR data isn't used for advertising purposes without consent.

Addressing some of the claims in more detail, LG stated that its smart TVs don't collect, record, or transmit ambient conversations in the home unless voice functionality has been activated by a user. It further stated that its far-field voice recognition tech (Hi LG) must be activated by a user before the TV starts listening, much like Apple's "Hey Siri" mechanism for iPhone.

LG did confirm that its TVs monitor for Hi LG's wake word while in standby mode, but says that unless the wake word is detected, the audio is only processed locally before being deleted. The company didn't address some of the other claims and vulnerabilities pointed out in the video, such as the storing of transcripts in plain text.

Tom's Hardware has not independently verified either the claims made by Gamers Nexus in its documentary or LG's counterclaims regarding the issue. LG's full statement follows:

LG Statement:

This is to provide LG's position regarding the claims recently raised by the Gamers Nexus YouTube channel.

The claims made in the recently published video are not true. LG TVs process voice data only when the voice button on the remote control is pressed and held, or when a wake word such as 'Hi LG' is recognized after the user has activated the Far-Field voice recognition feature. Other than these instances, the TVs do not collect or record ambient conversations. (If the wake word is not recognized, no voice data is transmitted to the server; the audio processing for wake word detection is performed locally on the device and is immediately deleted.)

Additionally, to provide smart TV functionalities, LG TVs feature the ability to scan for and connect to nearby devices on the same network. This is a standard function commonly provided by smart TVs and smart home devices.

The ACR (Automatic Content Recognition) feature is provided on an opt-in basis to deliver personalized content recommendation, services, and advertisements. If a user does not consent to the applicable optional agreement, ACR data is not used for advertising purposes.

Topic by topic breakdown:

At LG Electronics, we are committed to transparency and secure user experience. To clarify recent concerns and reiterate our commitment, we would like to emphasize the following points:

• Protecting Voice Privacy: We ensure that your LG TV does not collect, record or transmit ambient conversations in your home, unless voice functionality has been intentionally activated by the user.
• Far-Field Voice Recognition ("Hi LG"): This feature must be manually activated by the user before the TV begins listening for the specific wake word. Audio processing occurs only when voice functionality has been activated by the user and a wake work (such as “Hi LG”) is detected.
• Standby Mode Operation: When the TV is in standby mode and appears to be turned off, it only monitors for the wake word if you have previously enabled the Far-Field feature. If no wake word is detected, the audio used for wake word detection is processed locally on the TV, promptly deleted, and is not transmitted to LG servers.
• Transparent and Useful Connectivity: LG TVs can identify compatible devices on the same network to enable features such as device connectivity, content sharing or smart home functionality.
• Proactive and Continuous Security: Data security is a top priority for LG. We continuously monitor our platform and partner with independent security experts to identify vulnerabilities and deliver timely security updates.
• Full Control Over Data and Terms: LG Electronics is committed to providing transparency and rejecting deceptive practices (dark patterns), ensuring users can choose their preferred privacy and consent options directly through their TV settings.
• Consent-Based Activation: To provide a more tailored and convenient experience, LG TVs offer Automatic Content Recognition (ACR) to enhance viewing experiences, Voice Recognition for hands-free control, and Interest-Based Advertising to deliver relevant advertisements. Each feature requires separate explicit user opt-in consent and can be disabled at any time through the TV settings.

PricewaterhouseCoopers LLP (PwC) estimates that spending on AI data centers could reach as much as $31.6 trillion in the next decade and a half, with optimistic outlooks suggesting that capital expenditure could potentially hit $50 trillion. Bloomberg reports that this amount exceeds the spending that railways, electrification, or the internet required when they were being set up for the first time. It also pointed out that investments in AI data center infrastructure aren’t a one-time expense that would last decades, unlike railroad networks, the power grid, or fiber optic cables — instead, data center operators are expected to purchase new GPUs and related infrastructure every four to six years.

GPU development is happening at breakneck pace, with Nvidia, AMD, and other manufacturers releasing new generations every two to three years. In fact, one Google architect said that a data center GPU service life is only about one to three years, which has got some experts concerned that GPU depreciation could be the next big crisis for hyperscalers. “Railways. Electrification. The internet. Each required enormous amounts of capital and defined an era,” the publication reiterated from the report. “The AI infrastructure cycle underway dwarfs all three. This one resets every four to six years — and shows no signs of ending.”

Nvidia and other chip manufacturers would be some of the biggest winners in this spending spree, but other hardware industries would also benefit, like networking equipment and even the copper material needed for running power inside data centers. PwC is confident in its forecast, especially as it claimed that both capital and demand for the AI build-out exist. It also broke down the investment in each region — spending in the U.S. is projected to hit $15.1 trillion, followed by the Asia-Pacific region, including China and India, at $8.2 trillion. Europe will likely spend $5.6 trillion, and it’s trailed by the Middle East at $1.1 trillion and Africa, with $255 billion.

The AI build-out is not without risks, though. The report cited power availability, data sovereignty requirements, and chip availability as factors affecting the build-out. For example, data centers in the U.S. are forecasted to consume 20% of its total power supply by 2035, which is why operators are turning to natural gas turbines for on-site power. However, this has also led to jet engine shortages, which is why SpaceX has started in-house turbine blade manufacturing to cut delivery delays by up to 18 months. It also said the geopolitical tensions, like trade bans on rare earth elements and high-end chips, could cut the global investment forecast by 20%.

There are still some concerns that the current AI boom is a bubble that will pop sooner or later. This is especially true as some AI tech companies currently have “hidden debt” worth around $1.65 trillion, while costs have started spiking as AI companies like OpenAI look for a path towards profitability. Despite that, Nvidia is still going full steam ahead, partnering with several firms to build a $500 billion AI infrastructure fund for further AI investments.

The Oklahoma Office of the Attorney General commanded the City of Claremore to release body cam footage requested by farmer Darren Blanchard and his legal team without charging them $17,125.44. According to 404 Media, the city is asking for that amount so that it will release information on Blanchard’s arrest in April 2026 for speaking 30 seconds longer than the allowed time during a public consultation for a proposed data center in the area, as well as city records of previous disturbances in other public meetings. This led Kate Griffin, one of the farmer’s lawyers, to complain to the Oklahoma Attorney General, which looked at the situation.

Claremore justified the fees by saying that it would need to spend $16,540.44 for a legal review of requested records “to ensure that all information which must be withheld relating to members of the public and the City’s personnel is redacted in order to protect their privacy.” It’s also asking for $585 — equal to the 15-hour pay of a city clerk — to conduct the search of the documents.

“The City knows and is aware that any documents released to Mr. Blanchard and to those associated with him, regardless of the privacy implications of individuals named in such documents, are subject to wide distribution, including on social media,” Claremore said in its response to the Oklahoma AG. It also added, “Her persistence in maintaining an overly onerous request demonstrates that this dispute has nothing to do with transparency and likely has everything to do with causing excessive time/money expense to the City in order to generate public sympathy for her client and negative publicity for the City.”

However, Assistant Attorney General for Oklahoma Anthony Sykes said that this isn’t a valid reason to charge Blanchard thousands of dollars for this request. He said that the state’s law says that public bodies can only charge for the direct costs of searching and copying data when it comes to information requests. More than that, all the fees being charged must be disclosed publicly beforehand.

“The City has not posted a schedule of fees as required by the Open Records Act. Having failed to give the requisite notice of the fees charged for public access to City records, the City is foreclosed from charging search fees,” Sykes said. “If I were to conclude otherwise, there would be no incentive for public bodies to comply with the statute. They could simply ignore what the ORA requires and charge what they deem reasonable on a case-by-case basis.”

Another justification the city used for the egregious fees is the need to redact the body cam footage “to protect the privacy of the public and City personnel.” However, the assistant attorney general said that the incident happened at a public meeting with no reasonable expectation of privacy. Because of this, the city should hand over the requested data as soon as possible.

Blanchard is being charged with trespassing, a municipal crime with a penalty of just $200, making these charges very steep by comparison. Even though it might’ve been easier to plead guilty and pay the fine, the farmer is fighting the city on the grounds that it’s violating his right to free speech.

This isn’t the only arrest across the country that’s related to resistance from data center projects. A Kansas teacher was arrested in July 2026 for lightly clapping at a meeting in support of a speaker after they finished speaking, although the town eventually dropped the charges against them. In fact, as of August 2026, at least 37 people have been arrested for protesting against data centers.

British semiconductor and software design company Arm is asking shareholders to approve a massive performance-based pay package for CEO Rene Haas worth up to $800 million if the company reaches a $2 trillion valuation, a move that has drawn pushback from proxy advisors ahead of a September 9th vote. According to an August 31 report by the Telegraph, the company is facing a potential shareholder revolt as proxy advisory firms such as Institutional Shareholder Services (ISS) and Glass Lewis urged investors to vote against the compensation plan, calling it excessive.

The compensation is arranged through a one-time Value Creation Plan (VCP) consisting of 425,000 Performance Share Units (PSUs), with the award divided across three market-cap milestones, according to Arm's regulatory filings. Haas earns 25% if Arm reaches $1 trillion by March 31, 2029; 50% cumulatively if Arm reaches $1.5 trillion by March 31, 2030; and the full award if Arm reaches $2 trillion by March 31, 2031. Arm will determine whether each target has been reached by using its rolling-average closing share price over any 60-day period prior to the corresponding deadline.

The shares also carry lengthy vesting periods. Awards associated with the $1 trillion, $1.5 trillion, and $2 trillion milestones vest on April 1 of 2031, 2032, and 2033, respectively, subject to Haas remaining employed by Arm. Meanwhile, missed interim milestones can roll forward. For example, shares attached to an earlier target can remain available if Arm subsequently reaches a higher milestone. The roughly $800 million maximum payout reflects the implied value of all 425,000 shares if Arm reaches the $2 trillion target, which corresponds to a share price of roughly $1,880.

ISS has raised concerns about the potential size of the award and the use of VCP-style compensation in Britain. The advisory firm said such plans remain uncommon in the UK market and can create the prospect of extremely large gains, while their effectiveness at improving corporate performance remains unproven. Glass Lewis has similarly recommended shareholders oppose the proposal, describing Haas's potential award as “excessive.” Arm currently has a market capitalization of around $264 billion, according to The Telegraph, leaving a substantial climb before the first $1 trillion milestone comes into range. The company's servers currently capture over 45% of data center revenue.

Arm argues that its compensation structure needs to be competitive with that of the US technology industry. The Cambridge-based company is listed on Nasdaq, Haas is based in California, and many of the companies competing with Arm for executives and engineers are American technology and semiconductor firms. Arm said its approach is designed around US compensation standards reflecting “the location of our key competitors for executive and other talent,” its Nasdaq listing, and the location of its CEO. The revised remuneration policy also raises the maximum achievement level for Haas's regular PSU awards from 125% to 200%, in addition to the separate VCP.

The shareholder advisers are also calling out Arm's corporate governance. ISS has recommended votes against the re-election of Haas and Arm chairman Masayoshi Son, citing insufficient independence on the company's board. Arm's own filings show that Japan’s SoftBank beneficially owned about 86.4% of Arm as of May 21, giving the Japanese conglomerate control over most matters put to a shareholder vote and substantial rights over board composition. Arm qualifies as a “controlled company” under Nasdaq rules and therefore uses exemptions from some governance requirements that apply to companies without a controlling shareholder.

Haas's expanding relationship with SoftBank adds another layer of governance concern. He has served on SoftBank's board since 2023 and was appointed CEO of SoftBank Group International in April 2026, a part-time role overseeing some of SoftBank's portfolio companies. Arm itself acknowledges in its annual filing that Haas's and Son's overlapping positions across the two companies could create, or appear to create, conflicts of interest. SoftBank's 86.4% holding also gives it enough voting power to determine the outcome of Arm's ordinary shareholder resolutions in most circumstances, making rejection of the pay proposal unlikely without SoftBank's support.

The ambitious $2 trillion target — which would make Arm the UK’s first trillion-dollar company — comes as the company attempts a significant business expansion. The company introduced its Arm AGI CPU in March 2026, pushing beyond its longstanding role of licensing processor IP and compute subsystems into Arm-designed production silicon aimed heavily at AI infrastructure. Arm specifically cited that expansion when introducing the revised remuneration policy, framing the VCP around what its remuneration committee calls “exceptional, market-leading growth” over the next five years.

Huge valuation-linked CEO packages have also become increasingly prominent in the US. Most famously, Tesla shareholders approved a performance package for Elon Musk in November 2025 that could ultimately be worth close to $1 trillion, with awards tied to market cap and operating milestones, including taking Tesla to an $8.5 trillion valuation.

Taiwanese prosecutors are investigating Unimicron, one of the world’s largest PCB and chip substrate makers and a key supplier to Nvidia, Intel, Google, and Amazon, over allegations that it shipped China-made PCBs back to Taiwan and relabeled them as Taiwanese products, according to Nikkei Asia. Investigators raided the company’s headquarters in Taoyuan’s Guishan District and a manufacturing plant in Zhongli District on August 28, questioning 14 employees as suspects — including the general and deputy general managers of its PCB business — and four more people as witnesses.

Prosecutors say that the alleged conduct contravened Articles 216, 210, and 255 of Taiwan’s Criminal Code, which cover the use of forged private documents and false labeling of an item’s origin. Wang, the person identified as the PCB department general manager, was released on bail of NT$15 million (roughly $473,000), while a deputy general manager identified as Wu was released on NT$12 million (roughly $378,000).

Three others are said to have posted bail ranging from NT$300,000 to NT$5 million, and the remaining nine were released without bail. "There was strong suspicion that they had violated Taiwan's law covering the use of forged private documents and false labeling of goods," the Taoyuan District Prosecutors Office said in a statement. Unimicron told the Taiwan stock exchange that it’s fully cooperating with the investigation and that it doesn’t expect a material impact on its operations.

Since August last year, U.S. Customs and Border Protection has applied an additional 40% tariff on goods that it determines were transshipped through third countries to evade duties, on top of any other applicable penalties, and the agency has no authority to waive or otherwise mitigate the charge. If any relabeled Unimicron PCBs were to reach the U.S., that penalty would fall on the company’s American customers as importers of record.

The White House has identified 40 countries and territories that it says pose an elevated risk of illegal transshipment, with Taiwan flagged as a key concern. Taipei has been running major crackdowns on “origin washing,” where companies claim goods are made in Taiwan to obtain preferential tariff treatment, a crackdown that’s perhaps perfectly illustrated by the fact that prosecutors published names and bail amounts within 24 hours of raiding one of the country’s most important listed tech companies. After all, the “Made in Taiwan” label is ultimately a trade asset whose value rests on the fact that it’s not “Made in China.” Since its elevated risk designation, Taiwan is understandably keen to show Washington that it polices the difference itself rather than leaving it to U.S. Customs.

The products involved in this crackdown appear to be conventional PCBs, not the high-end ABF substrates used for Intel’s EMIB-T platform or Nvidia’s advanced data center accelerators. Unimicron’s offshore manufacturing remains in China for standard substrates, PCBs, HDI, and flexible boards, while its advanced CoWoS-related substrate capacity is based at its Yangmei factory in Taoyuan.

If the case concerns relabeling on individual products, the fallout will be limited to the Taiwanese prosecution. If, however, it turns out that China-made goods were transshipped through Taiwan to alter their origin before export to the U.S., that’s an entirely different story and could trigger CBP’s 40% transshipment penalty on the affected goods, along with potential retroactive duty reassessments, which would hit Unimicron’s American customers as importers of record.

When you serve a barely regulated emerging market worth trillions of dollars, you have to gear up your presence in politics beyond what usual lobbying or government affairs can do. This is exactly what Nvidia is doing by establishing its employees' federal political action committee (PAC), which will fund politicians whose positions are favorable to Nvidia's interests, reports Bloomberg.

The Nvidia employees PAC — which was registered with the Federal Election Commission on Thursday — will receive voluntary contributions from eligible Nvidia employees, who can provide up to $5,000 per year. The PAC will be permitted to contribute to federal candidates from both parties as well as party committees that express positions which align well with Nvidia's own goals, particularly in the fields of AI regulations, export controls, education, infrastructure spending, and workforce policy, just to name a few.

Nvidia reportedly told employees eligible to participate that decisions Congress makes over the coming years could have substantial consequences for the AI industry and everyday use of the technology. The company also noted that policymakers have increasingly focused on its industry and that decisions made in Washington affect both Nvidia's business and its customers' ability to obtain and deploy its technologies.

Nvidia has already substantially expanded its political operation. The company has spent more than $2.5 million on federal lobbying this year, an increase compared with the same period last year, according to lobbying disclosures seen by Bloomberg. In June, Nvidia hired Bruce Andrews, who previously headed government affairs at Intel and served as deputy secretary at the U.S. Commerce Department in Obama's government, as chief external affairs officer. In addition, Nvidia has hired five external Washington lobbying and government-relations firms to advocate for the company on a range of issues, including AI and trade policy, among others. The company also donated $1 million to the Trump Vance Inaugural Committee in January 2025.

Nvidia needs a PAC because lobbying and campaign contributions serve different purposes. The company can spend corporate money to lobby lawmakers, but it generally cannot use corporate treasury funds to contribute directly to federal candidates. Meanwhile, a company-sponsored PAC has a legal mechanism to collect voluntary contributions from eligible employees and direct that money to candidates and party committees from either party.

Meanwhile, unlike individual campaign contributions, donations made by the PAC will be publicly disclosed and subject to spending limits that do not increase with inflation. Furthermore, corporate PACs face growing resistance from lawmakers, according to Bloomberg. More than 270 House and Senate candidates have pledged to reject corporate PAC contributions this election cycle, the highest number since End Citizens United began promoting the commitment in 2018, Bloomberg claims. However, it is unclear whether these 270 are serious major-party nominees or current members of Congress, or some of the thousands of declared congressional candidates.

Nvidia is hardly alone in increasing spending on its influence in Washington, as most high-tech companies, now joined by AI giants, tend to spend millions on government relations and lobbying. The establishment of the PAC just highlights Nvidia's growing dependence on policies set in Washington.

X’s Global Government Affairs team posted on its account that it identified a 200,000-strong bot farm operating on the platform, with 200 of them posting information designed to influence public perception. According to the team, the accounts are suspected to have been created by Chinese operators, and that they’re using the accounts to amplify the negative impacts of AI data centers, especially on electricity prices.

“We identified a bot farm of approximately 200,000 accounts. Within this farm, we found 200 accounts posting in a manner that could manipulate a legitimate debate about American AI and energy policy,” the team said in its post on the platform. “These posts contained claims that AI data centers are driving up household electricity prices and straining the grid. Others included AI-generated cartoons that depicted data-center operators enriching themselves at the public's expense.”

Some of the accounts shared by the team show names like Thomas Jackson, Patricia Robinson, Sandra Thompson, and Kenneth Flores, making it seem like they’re owned by Americans, and they’re sharing news stories from legitimate sources like The Southern Maryland Chronicle.

For example, some of their posts share the story of how PJM Interconnection hiked its prices by 76% due to AI data center demand. However, they add commentary, and sometimes even include AI-generated images designed to inflame the emotions of someone just scrolling through their feed. One narrative they’re pushing is that the costs of putting up data centers are being borne by ordinary people as big tech companies enrich themselves.

It’s unclear who sponsored or sanctioned the China-linked accounts on X, but there have been reports of China-linked operations designed to divide U.S. opinion on AI. However, the resistance against data centers isn’t all driven by Chinese propaganda, as billionaire investor Kevin O’Leary once claimed. In fact, a recent poll suggested that the biggest driver of data center protests is based on “object-level” local environmental and economic harms, especially as many other projects have shown the negative impacts they had on the community.

The concerns that many residents have about data center developments in their area are indeed valid and true, but so is the threat of foreign intervention in domestic American politics. This is no surprise, though, as nation-states have always used propaganda and information to advance their own interests. The internet, social media, and artificial intelligence have made this easier in recent years, though, so both platforms and people need to be more vigilant than ever.

It has become a tradition that every single quarter Nvidia reports record results that outpace all of its quarterly results before that. This Wednesday was no exception as the company posted revenue of $96.2 billion, which was up 106% year-over-year, due to rising demand for its AI hardware. But such results come at a cost, as the company has to invest massively in its future. In the second quarter of its fiscal 2027, Nvidia had to commit to procuring memory worth up to $160 billion, which includes its memory supply pact with SK hynix.

Nearly $100 billion revenue per quarter

For the second quarter of Nvidia's FY2027, which ended on July 26, 2026, the company's GAAP revenue hit a record $96.221 billion, up 18% quarter-over-quarter (QoQ) and 106% compared to the same quarter a year ago. Nvidia's net income totaled $59.688 billion, up 126% year-over-year (YoY), as its gross margin reached 75.0%. Sales of Nvidia's Compute & Networking hardware reached $88.299 billion, up 18% sequentially and 114% YoY, whereas sales of its graphics hardware hit $7.922 billion, up 12% sequentially and 46% year-over-year.

"AI has reached its inflection point," said Jensen Huang, founder and CEO of Nvidia. "AI is doing useful work. Its tokens are productive and profitable. Now, compute is revenue. And demand is accelerating. […] We have a golden age of new AI labs and startups, multiple frontier labs scaling in parallel, a thriving open-model ecosystem and physical AI coming online […]. The AI infrastructure buildout is at full steam. Vera Rubin, now in full production, was built to power exactly this moment."

Nvidia's results were driven by sales of its data center-grade AI hardware as various customers bought $89.023 billion worth of equipment, an increase of 18% sequentially and a rise of 117% compared to the same quarter a year ago. Hyperscalers purchased $48.710 billion worth of hardware from Nvidia (up 102% YoY and 13% QoQ), while revenue from AI Clouds, Industrial and Enterprise climbed to $40.313 billion (up 138% YoY and 25% QoQ), an indicator that while hyperscalers still purchase more equipment from Nvidia, the ACIE segment is growing faster. Sales of Nvidia's Edge Computing products were $7.198 billion (up 27% YoY and 13% QoQ), which means that sales of graphics products for PCs were strong despite shortages of GPUs and memory.

Commitments total $279 billion

Nvidia expects demand for its products to remain strong in the coming years. To meet that demand, the company increased its long-term purchase commitments from $119 billion in Q1 FY2027 to $279 billion in the second quarter. Typically, Nvidia's long-term supply commitments included pre-payments and commitments for wafer processing and advanced packaging at TSMC, as well as for HBM memory made by DRAM makers. This time around, Nvidia explicitly says that the bulk of the commitments are 'primarily related to the procurement of memory.'

Such huge commitments indicate that the company projects massive demand for its data center AI products in the coming years. During the conference call with financial analysts and investors, it indicated that its customer forecasts point to doubling demand next year, but Nvidia currently believes its supply chain can support about 70% growth.

"Even though our demand is much greater than 70%, our supply allows us to confidently deliver 70%," Huang said. "The unconstrained would be a lot, a lot higher. […] We have secured a lot of supply, but we just need a lot more."

To that end, the $279 billion supply commitment should be interpreted as not a precautionary inventory-building, but a strategic move to ensure shipment growth. Nvidia is effectively reserving memory and other capacity because it expects demand to exceed what the supply chain can deliver through at least the end of FY2028, as its management explicitly says supply will remain a bottleneck at least through FY2028.

$108 billion per quarter envisioned in Q3

For the third quarter of FY2027, Nvidia expects revenue of approximately $108 billion, ± 2%, with no data center compute revenue from China included in its outlook due to uncertainties with export and import licenses. The company projects a GAAP gross margin of around 74% and expects GAAP operating expenses of approximately $9.2 billion.

Nvidia's 88-core Vera chip will be getting put to work for Elon Musk twice over, first and foremost as the standalone CPU orchestrating Grok's AI agents in SpaceXAI's data centers and, from the fourth quarter of 2027, inside the company's first Starmind satellite. Nvidia announced the deployment yesterday, making SpaceXAI the second hyperscaler after Meta to commit to Vera outside full Vera Rubin racks, with Musk supplying the launch window in a post on X. Nvidia claims the chip completes agentic, reinforcement learning, and data processing tasks up to 1.8 times faster than x86 processors, but that figure hasn't been independently verified.

Agents spend much of their runtime off the GPU. A model that writes code, for example, calls tools, queries databases, and parses results by leaning on the host CPU between every inference pass; idle GPUs waiting on that work are wasted capital. "Vera gives us the CPU performance and memory bandwidth to run enormous amounts of orchestration, code, and data processing while keeping GPUs doing what they do best," Mike Nicolls, president of SpaceXAI, said in the release.

Meta was the first company to announce a large-scale standalone Vera deployment, confirming in February that it would run Grace-only servers in production with Vera to follow as soon as 2027. Nvidia has since disclosed shipping hundreds of thousands of standalone Grace servers and more than 2.5 million Grace CPUs in total, and the SpaceXAI deal extends that dominance directly into territory held by AMD's EPYC and Intel's Xeon lines.

Vera pairs 88 custom Olympus cores on a monolithic die with spatial multithreading and LPDDR5X memory delivering up to 1.2 TB/s of bandwidth. Nvidia's performance claims for the chip remain contested, and AMD has countered that its 256-core Zen 6 Venice processors beat Vera by 3.3 times in rack-level performance. Neither company disclosed how many Vera CPUs SpaceXAI will deploy, the value of the deal, or when the data center rollout begins; the only date attached to the announcement is the satellite launch window.

Musk said earlier this month that Starmind launches would begin in 2027, and his X post following the press release narrowed that to the fourth quarter, with what he described as significant scale-up following in 2028. The terrestrial NVL72 combines 72 Rubin GPUs and 36 Vera CPUs in a fully liquid-cooled rack, and an orbital version has to be reworked for radiation exposure, heat rejection through radiators rather than facility water loops, launch vibration, and the absence of any hands-on servicing.

SpaceXAI's first-generation AI1 satellite design carries a 120 kW compute payload, peaking at 150 kW, on a craft wider than a Boeing 747. The company has also acknowledged that orbital compute at the scale it's targeting requires significantly more chips than it currently has access to, a constraint the Vera Rubin commitment doesn't itself address.

Five months after the arrest of Supermicro co-founder Yih-Shyan “Wally” Liaw and two other co-conspirators for the alleged smuggling of Nvidia hardware into China, the company announced that it has completed its independent investigation and released its findings to the public, resulting in the termination of several employees. Supermicro said that the investigation, which was handled by an external law firm and conducted by an “independent forensic accounting consultant,” finds that neither the company nor its current senior executives were part of the alleged AI chip smuggling. It also said that it’s adopting all the recommendations to enhance its export compliance programs, although it did not directly admit that it was lacking in that department.

“The investigation team reviewed the customer transactions that were the subject of the federal indictment, as well as transactions with a selection of other customers who bought restricted products, and did not find any evidence that any current member of senior management had knowledge of the alleged diversion scheme or of any actual diversion of restricted products by the Company,” Supermicro said in the statement. It also added, “The Company’s compliance personnel have acted in good faith, with the support of management, to mitigate the risk of the Company’s products subject to export controls being diverted to restricted parties or locations.”

This odyssey began in March when the U.S. charged Liaw alongside Supermicro sales manager Ruei-Tsang “Steven” Chang and third-party broker Ting-Wei “Willy” Sun with conspiracy to unlawfully divert cutting-edge U.S. artificial intelligence technology to China. The accused aren’t operating a small-time smuggling operation, either — reports estimate that the three have smuggled hardware worth $2.5 billion since 2024. That massive amount has got shareholders worried that a huge chunk of the company’s sales come from illicit sales, resulting in some investors suing the company for securities fraud. Because of this, the company’s independent advisors also looked into this issue and said that it “did not find any evidence that the Company’s previously issued financial statements could not be relied upon based on the potential diversion of restricted products.”

Even though the third-party investigation exonerated Supermicro’s senior executives, it also resulted in the termination of several employees. The affected people were from the sales, technical support, and business development departments, although they were fired for breaking the company’s policies and code of conduct — the company said these moves were made "in connection with the investigation." Notably, none of the personnel were from its compliance department, and it’s also unclear how many people were dismissed.

Supermicro also said that it’s enhancing its export compliance program, which Nvidia CEO Jensen Huang said it must fix. Even though the company was never accused of wrongdoing and wasn’t part of the defendants in the case against the alleged smugglers, the fact that some of its employees were able to run a massive diversion scheme right within the organization raises major questions about the effectiveness of its compliance department. It said that it has already made changes that were recommended by its General Counsel and Chief Compliance Officer even before the third-party investigation concluded, and that its independent directors “will oversee implementation of the remaining recommendations.”

The high demand for AI chips in China has meant the smuggling operations are quite lucrative, even as the U.S. is tightening its grip on export controls and Chinese authorities are commanding that its tech companies prioritize locally made Chinese chips instead of American AI GPUs. Nevertheless, the race to build ever more powerful AI models means that there is such a massive demand for the most advanced AI GPUs from Nvidia that some people are looking for ways to circumvent these bans and make “easy” money.

Loudon County, Virginia, located just 22 miles west of Washington, D.C., has the greatest concentration of data centers in the United States. According to The New York Times, after years of booming data center construction that has brought lots of benefits to the local region, the county is beginning to rein in data center construction in response to local residents' complaints.

It all started when a federal government demand led to the installation of fiber internet lines in the area, owing to its proximity to Washington, D.C. This grew even more during the dot-com craze of the late ‘90s, when many companies built a ton of fiber connections in the region. This made it ideal for building early data centers in the area, with AOL moving its headquarters in the region in 1996. By the year 2000, the county voted to categorize data centers as office parks, meaning companies can build these structures with little oversight and approvals.

This incentivized tech giants to build data centers in the area; by 2007, there were already 29 such facilities in Loudoun, with the number growing almost ten-fold nearly 20 years later. Interestingly, it seemed that the negative impacts of these projects in the area were little to none. In fact, the people of Loudoun appreciated them, as they brought in a lot of money for the county. Data centers brought in a $150 million income in 2015, but this number has grown to $1.1 billion in 2025. This cash windfall allowed Loudoun to cut property taxes to just $0.805 per $100 of assessed value — that’s less than 0.8%, making it among the lowest in the United States, especially for a suburban area.

Aside from that, the tax windfall from data centers allowed the county to fund more schools, with two new ones opened in the area, plus another one under construction, build a $102 million recreation center that has multiple pools and hydro massage chairs, plus spend $22 million converting a former presidential estate into a public park. This also allowed the county to expand its fire and emergency services, and ensure that its roads, bridges, and tolls are in excellent shape. Because of this, many residents support data centers in the region; in a July town hall meeting discussing it, some people attended wearing shirts that said: “I Support Data Centers Because I Like: Lower Taxes, Excellent Schools, Better Job Opportunities, and More.”

This is a stark contrast to what the rest of the country is seeing when it comes to data centers. New developments have raised various issues nationwide, from electricity price hikes up to 76% in the biggest power region of the U.S. and excessive water consumption that caused low water pressures for neighboring communities to 24/7 noise pollution that basically made the area unlivable and allegations of air pollution brought about by unpermitted gas turbines needed to power the data center. It’s for these reasons that many people are protesting the development of these projects in their communities, and several counties and states have passed data center moratoriums.

Despite widespread support for data centers in Loudoun, people are starting to push back against more recent developments. Loudoun Board of Supervisors member Juli Briskman, who is among the people in charge of its land, zoning, and economic policies, said, “It’s gone way too far. We’ve become addicted to the data centers for their tax revenues, but at what cost?” Some residents have also started complaining about data center developments in their vicinity. A Vantage data center, which has started operations recently, was the center of a noise complaint because of its diesel and gas turbine generators, while another resident in nearby Ashburn is raising an issue about Dominion Energy planning to put up a 185-foot-tall high-voltage electricity transmission tower in her backyard. There have also been reports that another tech company is buying over 100 homes in a luxury community for $4 million apiece, which is double their current market value.

Because of these issues, Loudoun ended its policy of zoning data centers as office parks, meaning anyone who wants to build a project in the area must now go through an approvals process from the public. This will make it significantly slower to get projects like these off the ground, and there’s also no guarantee of approval. Just last month, Amazon applied to build four more data centers in the region, and some board members have already signaled that they will reject the project.

When done right, data centers can bring economic prosperity for the community that they are in, which is exactly what Loudoun County was able to achieve. After all, data centers aren’t just about AI — they’re also used to serve the digital economy and keep the internet running, so that online services like Facebook, Instagram, Netflix, Spotify, Google Maps, Uber, and more can operate smoothly at scale. However, the massive processing power demanded by artificial intelligence workloads means that data centers serving its needs use up tons more power and water, which can make living near one untenable for most residents unless the local government takes steps to protect their interests.

Spirit Airlines, which declared bankruptcy and shut down on the 2nd of May this year, is selling all its assets in bankruptcy court auctions to pay off its roughly $8.1 billion in debt. According to Bloomberg Law, Google LLC beat out Mercor.io Corp. — an AI-focused recruitment firm — to the airline's data, with the AI tech giant offering $10 million, $2.5 million higher than the latter’s $7.5 million bid. Nevertheless, the U.S. Bankruptcy Court for the Southern District of New York named Mercor.io Corp. as the backup buyer in case the Google deal falls through.

Google said it planned to use the massive amounts of data it purchased for training its AI LLMs, and the amount of data that the tech giant got its hands on is indeed a lot. Court records reveal that the Google purchase includes 100 million emails, 500 million Microsoft Teams chats, 7.2 billion records for competitors' flights, 7.5 billion passenger transaction records from 2008, and more than 175,000 employee records from 1986. Aside from this, the company will also get information on revenue, aircraft operations, employee productivity records, audits and fraud, marketing campaigns, human resources records, project management, and pricing curve data, among others.

This could be a cause of concern for anyone who’s ever transacted with the airline, either as a customer, employee, contractor, or even investor, especially as AI is known for its privacy problems. However, the company will not get access to personal data, including the 97.5 million passenger profiles that the airline kept or the 50.2 million customer records from the Free Spirit loyalty program. Furthermore, the court said that all the data being turned over to Google will be “rigorously scrubbed of any personally identifiable information by a third party before receipt.”

The tech giant is seemingly keen on getting its hands on unique data, especially as many companies are now suspected of acquiring thousands of books to train their AI models after they’ve already scraped huge swathes of the internet. Spirit Airlines data is valuable because it’s likely not readily available on the internet and contains specialized information gathered from decades of operation as an airline. Google can then use this to create AI models focused on aviation and offer its services to airlines.

We’re still unsure how AI will fit inside aviation operations, especially as it’s a conservative, safety-focused industry. Nevertheless, Google and other AI companies are probably keen on entering it, especially as air travel is only projected to grow in the coming years.

Privacy concerns and multiple incidents have led many citizens to take it upon themselves to block or disable Flock cameras. They often do this either by placing black trash bags over them or by spraying paint or insulating foam onto their lenses. Now, the former can be dangerous, especially if you don’t have equipment, as you need to reach high enough to cover the camera and secure the plastic bag over it. The latter can get you into deeper trouble, as paint or foam can damage the camera. So, 3D printing enthusiast SquidInk decided to create an easy-to-use model that would take seconds to install without damaging the camera and posted it on Maker World.

While the public was initially concerned about their privacy with Flock’s AI-powered cameras, this concern eventually turned into outrage after it was discovered that some police officers had been misusing the system. There were also a couple of high-profile incidents where procedural errors led to the mistaken apprehension of innocent people. Because of these incidents, some jurisdictions have voted to remove these cameras, to the chagrin of some of their most ardent supporters. As for towns and cities that voted to keep their Flock AI cameras operational, some citizens are taking matters into their own hands and deliberately blocking these cameras to prevent them from capturing video. Note that actions like these are probably illegal and will get anyone caught doing so in hot water. Possible charges include vandalism, criminal mischief, property damage, tampering with public infrastructure, obstruction, and more.

The Flock Sock itself doesn’t encourage anyone to commit a crime. Its description says, “The Flock Sock is a slip on cover designed to help protect a Flock camera from the harmful radiation of the sun. Your city spent their very own hard-earned tax dollars scattering these cameras everywhere to keep you safe, all it cost you was a little privacy. The very least you can do is help protect these valuable civil servants from getting a bad sunburn.”

The creator also said that Flock commonly uses three different models, and that they’re working on profiles for the other two so that there’s a 3D-printable Flock Sock for every Flock camera you may find in the wild.

Aside from being easy to print, it’s also easy to use and deploy. It slides onto Flock cameras in seconds, and you can easily lift it into position with a 1-inch broom handle through the built-in adapter. They also highlighted that it’s 100% non-permanent, saying, “No glue, no screws, and zero structural changes. Because it pops off instantly with absolutely no damage caused and costs exactly $0 to revert, it conveniently avoids some of the troublesome labels that Uncle Sam might stick to you. It's just a removable accessory.” While SquidInk recommended using ABS/ASA for its excellent heat and UV resistance, they also suggested using PLA “if you prefer your Flock Sock to develop a long term relationship with the summer heat.”

Again, tampering with Flock cameras in your city may get you in trouble, as it most likely constitutes a crime or misdemeanor. Nevertheless, public anger at Flock and its misuse has reached the point that a few are taking physical action against the cameras.

Oracle plans to cut more jobs this month, with reductions on some teams reaching double-digit percentages, Business Insider has reported, citing people familiar with the plans and an internal document. The company wants payroll lowered before its second fiscal quarter opens on September 1, and managers have been told to compile lists of affected employees. A new round would extend a year of deep cuts at the company, which shed 21,000 full-time positions, or 13% of its workforce, in the fiscal year that ended May 31 while borrowing $43 billion to fund AI data center construction.

Oracle's 10-K, filed June 22, capped the total expected cost of its Fiscal 2026 Oracle Restructuring Plan at $2.1 billion. The company recorded $1.8 billion of that in fiscal 2026, a 391% increase over the $374 million booked a year earlier, leaving roughly $300 million of headroom under the existing plan. Cuts at the scale Business Insider describes would either need to fit inside that remainder or push Oracle into its second new restructuring plan in three years; the filing describes the prior 2024 plan as substantially complete since May 2025.

Headcount stood at approximately 141,000 full-time employees as of May 31, with around 49,000 of those in the United States. Oracle attributed part of the fiscal 2026 decline to internal AI adoption and told investors that further reductions would follow as deployment grows, having already eliminated roughly 10,000 positions in a single wave earlier this year.

Company capex hit $55.7 billion in the fiscal year 2026, up from $21.2 billion the year before, leaving Oracle $23.7 billion short of covering its spending from the cash it generated. The company raised $43 billion in debt and $5 billion through stock sales during the year, and it expects to secure approximately $40 billion more through borrowing and equity issuance in fiscal 2027. Interest expense climbed to $4.6 billion from $3.6 billion a year earlier, so the annual growth in Oracle's interest bill alone now exceeds half of what it paid in severance and related restructuring charges all year.

Cloud infrastructure revenue grew 77% in fiscal 2026, and total revenue rose 17%, figures Oracle has previously pointed to when defending the spending. The stock is down more than 20% this year, and shareholders sued the company in January over statements about how much it would need to borrow to meet its $300 billion OpenAI commitment.

Oracle declined to comment and hasn’t confirmed the plans.

Apple filed a lawsuit against OpenAI in July, alleging that the latter stole trade secrets through former Apple employees. The startup has finally publicly responded to the lawsuit today, posting a blog post on its website titled, “Apple is getting this wrong.”

“Apple is one of the greatest companies of all time, and built a reputation for obsessing over the smallest details. This careless, aggressive and oddly personal lawsuit sadly doesn’t live up to that reputation,” the company said in its blog post. It also added, “Apple’s request for a preliminary injunction is both based on false information and completely unnecessary because we do not have, nor want, any of their trade secrets.”

The case names OpenAI technical staff Chang Liu, chief hardware officer Tang Tan, OpenAI, and io Products as defendants. Liu worked as a senior electrical engineer at Apple, while Tan was its former vice president of product design for the iPhone, AirPods, and the Apple Watch. Interestingly, io Products, which was acquired by OpenAI last year, was founded by Tan alongside former Apple Chief Design Officer Jony Ive and other former Apple heavyweights.

The tech giant requested a preliminary injunction to stop the accused from accessing, acquiring, using, or disclosing the alleged stolen trade secrets. Cupertino said in its filing, “Apple will be irreparably harmed absent a preliminary injunction.”

OpenAI publicly responded to this legal request through its blog post, pointing out that many of its allegations were actually based on miscommunications and false information, and that this move is completely unnecessary. But whether what the AI tech giant claims is true or not, its research and operations on consumer hardware would likely be impaired if the judge grants Apple’s request.

Although OpenAI’s primary product is ChatGPT and its other LLM-powered services, it’s been rumored that it’s also working on AI-powered hardware. Its first product is expected to be some sort of portable smart speaker with built-in cameras and sensors. Although this isn’t an iPhone replacement, like the botched Humane AI Pin, some experts say this move threatens Apple’s standing as the biggest consumer electronics company on the planet. This is especially true as it still lags behind other tech giants when it comes to artificial intelligence, even though AI enthusiasts love using Apple silicon with its Unified Memory architecture.

Apple’s preliminary injunction is just the opening stages of what might be an epic showdown between two tech giants. It will likely take months (or even years) before this case reaches a judgment or a settlement, meaning a preliminary injunction will definitely have a massive impact on OpenAI’s hardware dreams.

Elon Musk’s Colossus data centers that sit near the border between Tennessee and Mississippi will finally be removed starting this month. According to the company, the 69 temporary mobile turbines, which have been the subject of a lawsuit that claims they have been causing pollution, are going to be completely removed by July 2027, meaning it will take the company 12 months to withdraw the trailer-mounted generators from its premises. This may sound confusing, as they’re “portable” generators, after all, but it seems that SpaceXAI is removing them in phases as its 1.2GW power plant slowly comes online.

SpaceXAI achieved one of the fastest data center deployments ever after it set up 100,000 Nvidia H200 GPUs in 19 days — something that Nvidia CEO Jensen Huang said usually takes four years or more. Musk achieved this by bringing in his own power instead of waiting to get connected to the grid, which was considered a novel idea at that time. Today, a few data center operators, like OpenAI, are following Musk’s footsteps and deploying their own turbines to power their servers without relying on other providers.

But even though the idea feels innovative, the community surrounding the Colossus 1 and Colossus 2 data centers has been complaining about the pollution that these mobile turbines bring. They say that these turbines didn’t have the required permits to operate, although the company argued that the mobile and temporary nature of these units exempted them. The EPA said earlier this year that these units aren’t exempt from permits, but SpaceXAI continued to operate them anyway. It has even got to the point that the NAACP filed a case over these unpermitted turbines, although the DOJ weighed in, saying that removing them would put national security at risk as Colossus 2 “supports mission-critical operations.”

Despite that, it seems that SpaceXAI has finally settled into an agreement with the Mississippi Department of Environmental Quality. It’s if the 1.2GW power plant replacing these mobile turbines is the same one that Musk is importing from overseas, but the important part is that it’s approved under a Clean Air Act permit. Aside from that, the company also said that it’s equipping all its mobile turbines with “advanced emission control technologies,” which should reduce the environmental impact of its power sources.

Tech enthusiasts are a passionate bunch, and the rich ones among them are willing to put their money where their mouth is. This is exactly what we see with a signed Steve Jobs business card from 1983, which is posted on RR Auction and is going for $70,741 at the time of writing. What made this relic special is that Job’s business cards from 1983 are a rare commodity and remain in high demand from collectors. It also received a Gem Mint 10 grade — the highest possible rating from PSA/DNA and is certified to be authentic.

RR Auction says that it has auctioned off 15 Steve Jobs business cards in its history, but only four of those come from 1983. This is also only the second one to bear the signature of Apple’s founder, which was put on the auction block in 2024 and fetched an eye-watering $180,000. The card on auction right now isn’t exactly perfect, with the website describing it as “In fine condition, with light soiling and staple holes to the upper section, none of which affect the bold signature.” Still, there’s at least 16 bids on the item, and the next bid is currently listed at $77, 816.

This isn’t the first time that an item related to an iconic founder has fetched thousands of dollars on the auction block. Just last month, Sotheby’s estimated that Nvidia CEO Jensen Huang’s iconic Tom Ford leather jacket, which costs $9,000 if you buy it new, would get up to $60,000. However, when the hammer finally closed the auction, the winning bid hit $960,000, which, we believe, is driven by Jensanity.

Unfortunately, if you’re not into the personal effects of CEOs and want something more substantial, you’ll probably have to fork out a lot more money. One example we have is the Apple-1 ‘Prototype Board #0,’ which sold for $2,750,000. Aside from costing a lot of money, these are rare finds, and you’ll have to wait years, if not decades, to get a chance at owning something so exceptional. But if you have a hole burning in your pocket and want to start a tech-related collection, but find the Steve Jobs business card a bit above your budget, an unreleased batch of 97 Duck Hunt and Super Mario Bros. NES cartridges has recently been discovered at a retro shop, most of which are graded 9.6 or higher by PSA. Three examples are about to enter auction on August 12, and they’re estimated to start at four figures, which might make it more “attainable” to fledgling collections.

Amazon, Google, Meta, and Microsoft have spent more than a trillion dollars on AI infrastructure, including data centers, the chips inside them, and the power needed to run the facilities, since 2023. The Financial Times said that these four big companies have already hit $1.1 trillion in capital expenditure based on their latest earnings reports, and that an additional $745 billion is expected to be added to this figure just this year.

“There is basically no end in sight for the growth in capex,” RBC Capital analyst Rishi Jaluria told the publication. “Investors need these companies to toe the tight line between investing in AI and not compromising the things that have made them successful.” This massive investment has upended several other industries — namely electricity prices and memory and storage chips. The massive power demand that data centers have put on the power grid has forced many U.S. utility companies to spend billions of dollars to upgrade their respective infrastructure, which they then passed on to all consumers, not just the big ones that forced the upgrade.

This, alongside other environmental issues, has caused many Americans to push back against data center projects near their communities. The White House instituted the “ratepayer protection pledge” and made AI hyperscalers, utility operators, data center companies, and individual states promise that they will protect the average consumer from electricity cost increases. But so far, no state has taken a step to codify this pledge into law. Oregon actually enacted the POWER Act, which resulted in a 30% increase in the power bill of users that consumed more than 20MW while slashing the bills of residents by 1.3%, but the state did this in 2025, way before President Donald Trump called the tech giants into the White House and told them to “pay their own way.”

The mountains of cash that these tech giants are pouring into AI are also affecting the memory and storage chip industry. Since these AI hyperscalers have a lot of liquidity from investors, they are willing to pay top dollar for the HBM they need to run their data centers. Because of this, it made sense for Micron, Samsung, and SK hynix to prioritize them over DRAM, especially as they can charge a premium for these chips and there are customers who are willing to pay at those prices. This resulted in a shortage of consumer memory that started in 2025 — while this initially affected PC builders and enthusiasts, it has started to affect other industries that require memory as well, including cars and smartphones. Even Apple, which historically had huge sway over its suppliers, was forced to increase prices because of the shortages.

Aside from skewing other industries, the massive CAPEX the big four are going into is alarming some experts, warning that the promises and contracts they’re making are leading to “hidden debt” not listed in their balance sheets. The amount, worth around $1.65 trillion, is annotated in their quarterly financial statements as future obligations that will only come into play as the related asset or service comes online. The current value is 122% of the actual debt reflected on their balance sheets, which could give investors the wrong impression that they have fewer obligations than they actually have.

While the amount of money that the big four are spending on AI might seem dizzyingly high, we must note that these companies are raking in massive amounts of cash quarterly themselves. Microsoft’s latest quarterly revenue is $90 billion, while Meta made $60 billion in the same period. Alphabet (Google) announced revenue of nearly $120 billion, while Amazon made $200 billion. That is a total of nearly $470 billion for these companies in just the last quarter.

Still, that does not mean that they can just keep on spending on AI. For example, even though Google’s cloud business had a revenue of $11 billion last year, its price dropped after it announced that it spent more than it made last quarter — the first time this happened in the 20 years since it went public. Meta is also planning to rent out its AI compute, apparently following in the footsteps of Amazon, Google, and Microsoft, which have growing cloud businesses. However, this announcement caused a drop in its stock price. “They are a bit all over the place,” SLC Management managing director Dec Mullarkey told FT. “For investors it’s no longer growth at any cost; they want to see the spending flowing through to results, like at the Big Three.”

Google's parent company Alphabet recently reported negative free cash flow of $5.9 billion for the second quarter of 2026, the company's first cash-negative quarter since its 2004 IPO, after capital expenditures doubled year-over-year to a record $44.9 billion and exceeded the $39.1 billion its operations generated as it continues its rapid buildout of AI data centers, according to its earnings release.

CFO Anat Ashkenazi raised full-year capex guidance to between $195 billion and $205 billion, up from $180 billion to $190 billion, and disclosed that Google delivered TPU systems to customers' data centers for the first time, a shift from renting the chips exclusively through Google Cloud.

The quarterly deficit is small compared to the sums moving through the business, and the firm's trailing 12-month free cash flow remains positive at $53.3 billion. Back in February, Alphabet raised its guidance, but since then, spending has exceeded the cash the business generates due to its AI buildout, and Alphabet is covering the difference with borrowed money and new stock.

Servers first, buildings second

Approximately 60% of the quarter's technical infrastructure investment went into servers, with the remaining 40% split across data centers and networking equipment, Ashkenazi told analysts on the earnings call. That ratio inverts the usual assumption that hyperscaler capex is dominated by construction. Most of Alphabet's marginal dollar now buys compute, primarily its own TPU-based systems, rather than other forms of infrastructure. Depreciation of property and equipment rose to $7.1 billion in the quarter from $5.0 billion a year earlier, and Ashkenazi said infrastructure spending will keep pressuring the P&L through higher depreciation and energy costs.

"We're still in a supply-constrained environment," Ashkenazi said on the call, repeating a characterization the company has used for several consecutive quarters. Demand is running far enough ahead of Alphabet's own build schedule that the company is renting third-party capacity as a bridge while its data centers come online, an arrangement Ashkenazi said will create modest margin pressure for its Cloud segment in Q3. The construction pipeline behind the 40% includes a $40 billion, three-campus program in Texas through 2027 in November, representing the company's largest investment in any state, and a $1.5 billion expansion of its Jackson County, Alabama campus, announced in June.

TPU sales turn capex into inventory

Google began recognizing revenue from TPU system sales in the quarter, with Ashkenazi telling analysts the systems were "delivered to customer data centers for the first time in Q2" and that "the vast majority of the revenues from these agreements will be realized in 2027." According to Google's balance sheet, inventory stood at $10 billion on June 30, roughly four times the $2.4 billion recorded at the end of 2025. A meaningful slice of the quarter's cash outflow bought hardware that sits on the balance sheet today and will be sold to customers next year, bringing cash back in. Money spent on data centers doesn't return in the same manner; instead, it is written down over the years of use.

Anthropic is anchoring a great deal of Alphabet's external demand, with its October 2025 agreement giving the Claude developer access to up to one million TPUs and more than 1 GW of capacity coming online this year, and an April securities filing from Broadcom, Google's TPU co-designer, added roughly 3.5 GW of TPU capacity from 2027 while locking Broadcom into future TPU generations through 2031. Meta entered talks for multi-billion-dollar TPU deployments in its own data centers last November. The current flagship, the seventh-generation Ironwood TPU, carries 192GB of HBM3E per chip and scales to 9,216-chip pods that Google rates at 42.5 FP8 exaflops.

Every TPU Google manufactures serves four functions: training and serving Gemini, running Search and YouTube inference, renting to Cloud customers, and now shipping as sold hardware. No other hyperscaler's capex spend works that many jobs, and none of the others has a chip business generating third-party revenue at this stage.

A $98 billion liability

Alphabet issued Class A, Class C, and mandatory convertible preferred stock in June for net proceeds of $49.6 billion, earmarked in the release for "capital expenditures to scale AI infrastructure and global compute," and sold $20.3 billion of senior unsecured notes during the quarter. Long-term debt reached $98.2 billion on June 30, up from $46.5 billion at the end of 2025 and from roughly $16 billion a year before that, a run-up Ashkenazi acknowledged on the call. The February bond program alone raised more than $30 billion across multiple currencies, including a 100-year sterling tranche, it was reported at the time.

Together, the four largest hyperscalers plan a combined 2026 capex of around $725 billion, up 77% on 2025, and Alphabet's new range now tops the group alongside Amazon's roughly $200 billion. Meta raised its own 2026 forecast to $125 billion to $145 billion in April, citing component pricing and competition for land, power, and labor. Alphabet's headline Q2 net income of $112.1 billion overstates the reality somewhat, however, as $99.0 billion of other income came primarily from unrealized gains on equity securities, contributing $6.26 of the $9.11 in diluted EPS. Operating income, the cleaner measure, rose 30% to $40.8 billion.

Google Cloud grew 82% to $24.8 billion in the quarter with an operating margin of 35.6%, and backlog reached $514 billion, up more than $50 billion sequentially, with just over half expected to convert to revenue within 24 months. Those contracts are the collateral behind the spending, with the buildout chasing demand Alphabet has already booked rather than demand it hopes to find. Ashkenazi said free cash flow "will remain under pressure" and confirmed capex will rise significantly again in 2027, so the question the next few quarters will answer isn't whether Alphabet returns to positive territory in any given period, but whether operating cash flow, up 41% year over year in Q2, can keep growing faster than a spending that shows no sign of slowing down.

Five U.S. tech giants heavily invested in AI and its related infrastructure reportedly have an estimated $1.65 trillion in hidden debt, with the figures annotated in their quarterly financial statements instead of being listed in their balance sheets. According to Nikkei Asia, this is higher than the $1.35 trillion officially listed, meaning investors could be caught unaware once the hidden figures come to light.

The publication says that Meta has a high off-balance-sheet-to-recorded-debt ratio, with the company owing $420 billion in unlisted debts compared to the $140 billion written on the balance sheet. Oracle purportedly also has a massive $273.3 billion of hidden debt, which is a 2,900% jump from the hidden debt it had from 2022.

This may sound strange, but it’s actually an accepted accounting practice. The “hidden debt” stems from long-term contracts that have been signed but have not come into force yet, which, Nikkei says, is mostly related to the billions of dollars promised to data center operators. The AI race has got many hyperscalers signing contracts and agreements with data center operators, saying that they will pay for the compute they generate once their project goes online.

While any institution promising to pay any amount of money for services or goods delivered is obliged to list them as a liability, the fact that these data centers haven’t started operations means that these agreements are off-the-books at the moment. But when these projects come online, the contracts that the tech giants have signed will come into force, and they’ll have to pay for the compute that these sites will deliver, no matter if there is demand or not.

Nevertheless, these tech companies aren’t just pouring money into future contracts just for the sake of it. Alphabet, Amazon, and Microsoft reportedly have a cloud service backlog worth $1.45 trillion, meaning these are services yet to be rendered and paid. Amazon Web Services CEO Matt Garman also told the publication that the investments that the company is getting into are “not speculative.”

While this may seem like a good way to secure capacity — sign customer contracts that guarantee demand and then enter into long-term agreements with data centers to get the compute needed to deliver the services- it opens these tech giants to massive amounts of risk. That’s because if the demand fails to materialize, then they’d be left paying for excess compute without having any customers to sell them to. What’s more alarming is that Nikkei says that these investment expenditures are exceeding their earnings, meaning these big tech companies are increasingly relying on corporate bonds and new shares to fund them.

Even though demand for AI compute is increasing, it’s still a relatively new and unproven technology, with many experts saying that it should benefit more people to avoid a bubble. The cost of using AI for nearly everything, called “tokenmaxxing,” has also caught some companies by surprise, with agentic AI eating up annual AI budgets in a matter of weeks. Because of this, some companies are reducing their use of AI or are switching to more affordable models from China. This uncertainty, paired with the way tech companies “hide” these liabilities, is quite concerning, as they would appear to have less long-term obligations than they actually do.

This isn’t the first time that an industry giant has used similar accounting techniques. The publication cited Enron’s 2001 collapse, which was due to the company hiding its troubled assets through special purpose entities and marking unrealized gains from trading contracts into its current income statements. While the tech giants are not hiding underperforming assets off their balance sheets and committing fraud, they’re still using a similar mechanism to list their upcoming obligations. Although these are technically not debt, they still behave like one, and the way they’re reported is what’s concerning some experts.

"Oscillator-based computing" is a term that doesn't make many headlines, but this area of computation is evolving and showing promise. The latest impressive development comes from an experiment in which boffins managed to synchronize 105,000 nano-oscillators in just 45 nanoseconds, reportedly using very little energy.

In layman's terms, the entire grid of tiny magnets, once perturbed, synchronized itself entirely within 45 ns, all just using the magnets' inherent spin — think of ripples on a water surface. Each oscillator measures 10-20 nm across, and the 105,000-count result is nearly a 1000x upgrade over the previous demonstration with 64 oscillators, proving that the technology can be scaled. In this new experiment, synchronization time barely increased with additional oscillators: it was 10 ns with 100 oscillators and rose only to 45 ns at 105,000.

What this means for computing is that grids can solve certain classes of problems that lend themselves to representation via propagating waves, directly or indirectly. Broadly speaking, most anything involving waves, statistics, approximation, and pattern recognition is eligible. The article mentions Ising machines and reservoir computing as being implementable by oscillator grids. At some point, the grids could become programmable by manipulating the oscillators' frequencies, phases, and coupling strengths. The result is then read by measuring how the grid settles into a synchronized state.

Going from there, practical applications include high-speed communication networks, financial and scientific modeling, real-time data analytics, and even AI acceleration. The research paper specifically notes that the grids could operate at tens of GHz and spend comparatively little energy doing so. The 45-nanosecond figure for the oscillator grid to stabilize would be roughly analogous to the time it would take a regular CPU to perform one calculation across an entire matrix.

Unlike quantum computing, which requires extensive and difficult error correction to maintain coherence, the oscillator array produces an exceedingly clear signal once it settles. The quality factor of the oscillator experiment was over one million, meaning the resulting wave frequency was well-defined and easy to read — think of the exact pitch carried by a tuning fork. To get the full details, be sure to read the research paper here.

AI tech giant Nvidia, which builds some of the most coveted AI chips in the world, has reportedly created a new “whitelist” of verified companies to help prevent its products from getting smuggled into China. According to the Financial Times, this roster cuts the number of authorized clients by more than half, with those remaining having passed tougher compliance inspections to ensure that they are genuine businesses, not shell companies designed to forward Nvidia GPUs and servers into China. Some of the steps that Nvidia took to help safeguard its chips reportedly included sending staff to customer data centers, contract verification, and interviewing end users.

Sources told the publication that the company made this move after Washington pressured it into tightening its legal compliance, which comes months after the arrest of Supermicro co-founder Yih-Shyan “Wally” Liaw, alongside two other suspects, for allegedly smuggling $2.5 billion worth of Nvidia hardware into China. This clampdown also extended into Singapore, which saw the seizure of a $42-million mansion tied to alleged AI GPU smugglers, and Taiwan, where authorities raided the offices of Supermicro and two supply-chain partners as part of a chip smuggling probe. Nvidia was not immediately available for comment on the news.

Although the U.S. has banned the latest AI GPUs for export into China since 2022, various investigations showed Chinese companies could still easily get their hands on these coveted chips until recently. Washington’s and its allies’ crackdown on AI GPU smuggling have cut supply in China, which is now making it harder for AI companies to procure the processors they need. President Donald Trump took a 180-degree turn in December 2025 and finally allowed Nvidia to export its H200 GPUs to select customers in the region, which would have alleviated the situation. However, Beijing refused to allow Chinese companies to buy these AI processors — instead, it’s banking on domestic semiconductor manufacturers to make up for the shortfall, but it’s apparently still not enough. One tech executive even told the Financial Times that all domestic suppliers are sold out and that they’re even considering less powerful chips, as long as they could be put to use.

As Nvidia reportedly cleaned up its verified list of clients and made it harder for non-vetted companies to acquire its chips, the company has also told its partners to fix their export control compliance. “We insist our partners are compliant,” Nvidia CEO Jensen Huang told the media last May after Taiwan started its operations against AI chip smuggling into China. “We hope that they will enhance and improve their regulation compliance and prevent that from happening in the future.”

Microsoft’s emissions for fiscal 2025 (FY25) rose by 25% from the previous year, even as the company’s 2030 deadline to become carbon-negative draws closer. According to the company’s 2026 Environmental Sustainability Report, released on Thursday, July 9, the backward step was driven primarily by the rapid expansion of its data center infrastructure and its decision to stop using short-term renewable energy certificates, which reduced its reported footprint without necessarily adding new clean electricity to power grids.

Microsoft reported approximately 20.3 million metric tons of carbon dioxide-equivalent emissions across its operations and supply chain, up from 16.2 million tons in fiscal 2024 and nearly 58% above its 2020 baseline. Electricity consumption increased by 24% during the year as the company built the computing capacity required for its cloud and AI businesses. Regardless, Microsoft says it remains committed to becoming carbon-negative, water-positive, and zero-waste by 2030. It also reported meeting its 2025 renewable-electricity target, replenishing more water than it withdrew globally, and exceeding several waste-recovery targets

The report’s foreword, written by Microsoft Vice Chair and President Brad Smith and Chief Sustainability Officer Melanie Nakagawa, focused heavily on the collision between the company’s headline sustainability goals and the realities of AI. Microsoft established the goals in 2020, a few years before the current scale of AI’s capabilities and the corresponding high environmental demands began to manifest.

While AI is inarguably a world-changing technological revolution, it is raising serious environmental concerns that begin right at the raw material sourcing and the complex semiconductor fabrication stages. The impact continues even after the processors have been compiled into supercomputers in massive data centers, with issues related to land use, energy consumption, noise pollution, and water consumption. Residents are increasingly opposing the building of these data centers in their communities due to these issues.

Microsoft is exposed at nearly every point of the AI chain. It procures servers and custom AI chips; owns and operates a massive, global network of over 300 data centers across 34 countries that powers the Azure cloud platform; and supplies the computing infrastructure behind products such as Copilot and its partnership with OpenAI. Scope 3 emissions from construction, purchased hardware, suppliers, and other value-chain activities remain the largest part of its footprint. Meanwhile, electricity-related Scope 2 emissions grew from nearly 2% of the total in 2024 to 13% in 2025.

Microsoft acknowledges that environmental solutions are not expanding as quickly as AI infrastructure. “This tension is real,” the foreword states. “It is forcing sharper questions: Where do we need to move faster, invest differently, or rethink our approach?” The company argues that the answer is not to retreat from AI, but to combine carbon-free electricity, carbon removal, sustainable fuels, lower-carbon construction materials, hardware reuse, and efficiency improvements into a single portfolio rather than treating each environmental target separately.

Its decision to stop buying non-additional, unbundled renewable energy certificates forms part of that change. These certificates can allow a company to claim renewable electricity already being generated elsewhere. Microsoft says it will instead prioritize longer-term agreements that help add additional carbon-free generating capacity to the grid, even though doing so will increase its reported emissions in the near term. Its renewable-energy agreements now cover up to 40 GW across 26 countries, with approximately 19 GW operational.

The company is also modifying the data centers themselves. It introduced a closed-loop liquid-cooling design that CEO Satya Nadella says enables AI data centers to use about as much water annually as a restaurant. Microsoft is experimenting with microfluidic channels etched into silicon, zonal cooling that reserves colder liquid for the hottest equipment, and lower-carbon concrete, steel, and mass timber for its construction. These efforts have not exactly quelled anti-data-center sentiment around its data centers. The company faced protests over a planned facility near Granger, Indiana, while residents living near its $7.3 billion Fairwater AI complex in Wisconsin have filed a lawsuit alleging persistent noise, dust, traffic, and light pollution.

Away from carbon, the report records clearer progress. Microsoft replenished 14.2 million cubic meters of water, exceeding its global withdrawals for the first time, and reduced average data center water-use effectiveness by 25% from its 2022 baseline. It achieved a 92% reuse and recycling rate for retired cloud hardware, diverted 90.5% of construction and demolition waste from disposal, and reduced single-use plastics in primary product packaging to 0.07%. It also legally protected 16,266 acres of land, approximately 36% more than the land estimated to be occupied by its operations.

The report is equally candid about where Microsoft is falling behind. The company's most important commitment—becoming carbon-negative by 2030 — is moving further away rather than closer. Total greenhouse-gas emissions climbed 25% year over year and now sit roughly 58% above the company's 2020 baseline, largely because AI infrastructure is expanding faster than its decarbonization efforts can offset. Scope 2 emissions also jumped sharply, rising from nearly 2% of Microsoft's footprint in FY24 to 13% in FY25 as electricity demand from new data centers surged. While Scope 3 emissions remain the company's largest source of carbon pollution, the report says the growing contribution from purchased electricity underscores how increasingly difficult it is to power AI infrastructure with clean energy alone.

A data entry error in Flock’s system has resulted in a car reviewer getting boxed in by police cars in a parking lot on suspicion that he was driving a vehicle with stolen tags. The Drive reviewer and Director of Content and Product, Joel Feder, was driving a $155,000 loaner Range Rover when police surrounded his vehicle.

When he asked why he was stopped (and by four police cars, nonetheless), the officers said the car’s plate had been reported stolen and that they’d been tracking him for days using the Flock app. After about an hour of trying to figure out why he was stopped, it turned out that a different plate with similar characters had been misplaced and had to be reported stolen in California, which triggered a nationwide alert on Flock.

The core of the issue is that the New Jersey plates on the Range Rover read 34 10 DTM, with the number 10 written in smaller font. This is a non-standard design used by New Jersey for manufacturers, with VEHICLE MFR written on the bottom of the tags. The missing plate was 34 03 DTM, but unfortunately, the LAPD police report only listed 34 DTM.

Another issue with the Flock system compounded this reporting error. Since the New Jersey manufacturer tags weren’t standard, it only read the larger numbers and letters and disregarded the smaller “10” on Feder’s plate. Because of this, it flagged all vehicles with the 34 ## DTM plate as stolen and alerted partner police forces whenever it detected a similar plate on the road. Feder even said that four other vehicles with a similar plate were being tracked throughout Minnesota, and it just so happens that he was the first to be intercepted.

The police said they had been tracking the vehicle for days using Flock’s AI cameras, but kept losing it because Feder parked it in his covered garage. So, when he stopped at a retail store, the authorities jumped on the chance and boxed him in to ensure that he did not escape. Thankfully, the issue was resolved on the spot with the officers, although it took an hour to verify with Jaguar Land Rover that the car or the plates Feder had were not stolen. Still, the journalist was advised to go straight home, as other police agencies using Flock might not be aware of the situation, which could lead to him getting stopped again on suspicion of driving a stolen luxury car.

These two errors compounded together to create a rather harrowing experience with the police. Thankfully, the incident did not turn into something serious, especially as the Plymouth Police told Feder that the cops would have stopped him with guns drawn if he were in Minneapolis.

This event adds to the numerous controversies that Flock AI has been facing, with one of the biggest issues the company faced recently being when several police officers were arrested for misusing the service to stalk romantic partners. This has led citizens to push back against the service, especially as news like this makes them lose trust in the authorities. It has even gotten to the point where a Texas town council member broke into a tantrum, proposing a total ban on cellular and GPS devices, after community pressure led to the cancellation of the service.

Apple filed a federal lawsuit against OpenAI on Friday, accusing the AI company and its chief hardware officer of stealing its trade secrets.

"OpenAI and its cohorts, led at least in part by former Apple employees, have recruited candidates from Apple, extracted their knowledge of Apple’s sensitive and confidential information, and then continued to exploit that knowledge once they arrived," the complaint reads. "As a result, OpenAI has misappropriated Apple’s trade secrets and confidential information in a variety of ways."

The suit, filed in the Northern District of California, names OpenAI technical staff member Chang Liu, chief hardware officer Tang Tan, OpenAI, and io Products as defendants. The last of that group is notable because it was founded by Tan in collaboration with former Apple design head Jony Ive, Evans Hankey (Ive's successor at Apple), and former Apple designer Scott Cannon. Notably, the complaint seems to attempt to avoid naming the founders, though Ive's name is cited in a URL.

Tan previously served as a vice president of product design at Apple, working on the iPhone, AirPods, and Apple Watch. Liu served at Apple as a senior electrical engineer.

In the complaint, Apple alleges that it reached out to OpenAI in February with concerns, but that OpenAI did not respond. Apple claims that Tan attempted to gain secrets from Apple employees, including asking prospective job candidates to bring components for "show and tell" sessions and used his knowledge of the company to squeeze more information out of candidates. The suit claims that Liu never returned a company laptop, and used an authentication bug to access Apple files.

Apple also claims that OpenAI told incoming employees how to leave their former job, suggesting they stay as long as possible and not disclose their former employer in order to continue to access confidential information.

"At every level, from members of its Technical Staff to its Chief Hardware Officer, and in coordination with business partners, OpenAI has been stealing Apple’s trade secrets and confidential information," the suit reads. "As a natural result, OpenAI’s nascent hardware business now rests on the shakiest of foundations, rotten to its core by its illegal reliance on misappropriated trade secrets."

OpenAI did not immediately respond to a request for comment from Tom's Hardware. Apple's lawsuit claims that over 400 former Apple employees currently work at OpenAI.

Apple is rumored to be working on a number of AI-powered hardware projects, including AirPods with cameras, a pendant, and home robots. It's less clear what hardware OpenAI may be working on, though The Information suggested the company has a HomePod-style smart speaker in the works.

Apple is requesting a jury trial, damages, attorney fees, and orders that the OpenAI may not use Apple's trade secrets, among other injunctions.

In May, Bloomberg reported that OpenAI was considering legal action against Apple because it expected deeper integration and more users from ChatGPT features built into iOS.

If the trial does go to court, it's sure to be a dramatic one, potentially dragging several former high-level Apple employees into testimony through discovery and testimony.The trial, Apple Inc. v. Liu et al, is case 5:26-cv-07078 in the United States District Court in Southern California.

Elon Musk has received the go-ahead from the Federal Trade Commission (FTC) to acquire Mesh Optical Technologies, an AI infrastructure startup that develops light-based networking hardware for data centers. Records published by the FTC on June 25 show that the regulatory body granted early termination of its antitrust review of the transaction, permitting Musk to procure Mesh. While the deal is yet to be finalized, with no official statement from either party, the government's green light indicates it’s all but done, as this was the last hurdle.

Interestingly, Mesh was founded by three former SpaceX employees who helped develop the Starlink optical communication links that keep thousands of satellites interconnected. So, why is Musk — who is simultaneously building the world's largest multibillion-dollar semiconductor manufacturing facility and an 11-million-square-foot orbital data center factory — seeking to own a company founded by his former employees? The answer appears to be optical interconnects, a critical technology that connects all three.

The connection problem: AI's latest bottleneck

As AI continues to grow in capability and user base, so do the enabling AI clusters, many of which now comprise tens to hundreds of thousands of processors. The hardest problem in scaling an AI cluster has evolved beyond making the chips faster to moving data between them. Training and inference tasks on frontier AI models are split across thousands of GPUs using parallel-computing techniques, requiring the processors to exchange enormous volumes of data every fraction of a second.

While per-chip compute capacity has raced ahead, the bandwidth linking those chips has not kept pace, a mismatch the industry refers to as the "I/O wall." The processors mostly communicate via copper interconnects, which currently dominate AI clusters. However, copper presents inherent limitations. As per-lane signaling climbs toward 200 gigabits per second (Gbps), attenuation, crosstalk, and the skin effect all worsen at higher frequencies, driving up power and corrupting the signal until passive copper becomes impractical beyond a meter or two.

To overcome these constraints, the industry is increasingly turning to optical networking, bringing the technology closer to the processor. Optical links use transceivers to convert a chip's electrical signals into light for transmission over fiber, then convert them back into electrical signals at the receiving end. They can carry far more data over much longer distances while consuming less power than equivalent high-speed copper connections, making them increasingly essential as AI clusters grow larger. Chipmakers and networking vendors are racing to deliver faster 800G and 1.6T optical transceivers while shortening electrical paths with co-packaged optics, which place the optical engine alongside the switch ASIC (application-specific integrated circuit).

This shift has transformed optical interconnects from a supporting technology into one of the industry's most strategically important AI infrastructure markets, attracting billions of dollars in investments and resulting in major partnerships for new and existing industry players. One such player is Mesh, the optical hardware startup that has drawn the interest of the world’s richest man.

A mesh solution to Musk’s ambition?

Elon Musk has been one of the most aggressive players in the AI industry. After co-founding OpenAI, he went on to launch a proprietary company, xAI, before turning his focus to building data centers. In less than two years, xAI deployed the Colossus supercomputer with over 200,000 Nvidia Hopper- and Blackwell-generation accelerators. Colossus 2, with a long-term target of 1 million GPUs, is already operational. For Musk, however, buying the chips was not enough. Why not build them, too?

Characteristic of the world's richest man’s preference for complete vertical integration, SpaceX — in collaboration with Tesla and xAI — is now building Terafab, a vertically integrated, multi-billion-dollar semiconductor manufacturing facility aimed at producing chips capable of delivering an unprecedented over 1 terawatt of AI compute capacity annually. Located in Austin, Texas, the colossal facility aims to consolidate every stage of chip production under one roof, handling everything from logic and memory fabrication to advanced packaging and testing. An ambitious project that we've also analyzed for its feasibility.

The facility's output will serve to meet the chip needs of the broader AI industry, as well as those of Musk’s xAI, self-driving vehicles, Optimus humanoid robots, and SpaceX's orbital AI data center plans. Musk says 80% of Terafab's total compute output is ultimately destined for Earth orbit to support SpaceX's orbital data centers.

“But there aren't any data centers floating around in space,” observers may point out. Introducing Gigasat, Musk's 11-million-square-foot fix for that reality. Gigasat is yet another massive facility under construction, this time for manufacturing everything needed for SpaceX’s AI1 satellite, the company's most likely world-first orbital data center with 150 kW of compute.

At first glance, everything seems in place for the next generation of Ultra-capable AI infrastructure. However, there is one critical missing piece in this stack, one that we've established earlier. Hundreds of gigawatts of extremely powerful silicon are not particularly useful if the data can't move between the dies fast enough in AI clusters, whether on the ground or in space. The industry-prevalent copper hits a wall long before you reach the scale Musk is chasing. Hence, the need for the missing piece: optical interconnects.

This brings us to Mesh, a manufacturer of precisely that missing piece. Mesh Optical Technologies is a US optical communications startup that develops high-speed optical interconnect hardware — optical transceivers that convert a chip's electrical signals into light for high-speed transmission over fiber — for AI data centers and space communications.

Its flagship product, the Alpha C1, supports 800G and 1.6T data rates and reportedly draws about a third of the power of competing modules, using a flip-chip die-bonding process the company says makes the optical engine repeatable at the volume — potentially millions of links — that AI clusters demand.

These are the characteristics needed to seamlessly interconnect the next-generation terrestrial AI supercomputers and, potentially, future space-based computing platforms, which Terafab aims to deliver. An added benefit is the space-related experience of the three Mesh founders, who happen to be ex-SpaceX employees who helped build the laser-based inter-satellite links that connect Starlink's constellation.

Again, in typical Musk fashion, rather than simply buying the hardware, he is moving to acquire the entire company, gaining full control of its R&D and supply chain. Should the deal — which is all but done — go through, Musk will own the full stack of critical infrastructure needed to power the future of the AI industry.

Smart money is flowing to optical interconnects

The SpaceX ecosystem is just one of many entities that recognize the immense technical and economic importance of optical networking in AI. AI chipmakers are actively investing in the optical supply chain to secure manufacturing capacity and prevent hardware bottlenecks.

Nvidia alone has committed a reported $4 billion across component makers Coherent and Lumentum to lock up supply. Elsewhere, several hyperscalers, including Microsoft, Meta, and OpenAI, have teamed up with hardware giants Broadcom, AMD, and Nvidia to establish an Optical Compute Interconnect (OCI) Multi-Source Agreement (MSA) group, with the goal of developing protocol-agnostic scale-up interconnection technology for AI clusters.

To counter chipmakers' dominance, entities such as Japan's NTT established the $500 million IOWN (Innovative Optical and Wireless Network) Fund. This fund explicitly targets the creation of an open photonic ecosystem to accelerate the global transition from copper to light-based AI clusters.

Then there are the smart-money moves by investors, as well as the rising balance sheets of companies. Lumentum stock reportedly soared 339% in 2025 and delivered an additional 135.4% return in the first five months of 2026 alone, while Fabrinet, Cisco, and Coherent all recorded significant revenue surges attributable to optical hardware sales, meaning that Musk's move to acquire Mesh is extremely prescient, given Terafab's ambition.

While most of the Western world has been grappling with publishers and big tech companies about digital ownership, a Redditor who claims to be married to a Chinese lawyer and certified Chinese-English translator said that multiple Chinese families have successfully sued “for the right to inherit their deceased relatives’ game accounts.” u/Slawrfp shared summaries of three rulings favoring a gamer’s estate with regards to digital ownership on a subreddit. These cases go beyond game ownership, too, as they also tackled digital assets, in-game purchases, Bitcoin, and even social media accounts.

“Chinese courts view game accounts and microtransaction purchases as something of monetary value, and therefore gamers have rights related to those assets,” u/Slawrfp wrote. “Chinese courts reject the idea that standard non-transferability clauses can stop you from inheriting or bequeathing a game or even individual microtransactions (of the same nature as CS:GO knives or skins in other games) and have made this ruling in multiple cases.”

u/Slawrfp cited several cases — the first one is called “the Golden Blade case," which arose out of a dispute between two parties in 2009. The issue started when the wife (Li Lan) of a deceased gamer (Lu) wanted to sell the “Golden Blade” he acquired in the game Zhengtu, a now-defunct MMORPG. However, Lu required the cooperation of his “in-game wife,” Yang Yuan, to get the item, and therefore argued that she should get ownership.

In the end, the court ruled that since Lu put in the effort, paid for internet access, loaded up with in-game credits, and that buyers were willing to acquire the item for around RMB 50,000 (around $7,350 at the current exchange rate), then it had the attributes of property and could be inherited by his legal wife. Aside from that, DeHeng Law Offices [machine translated] said that the “in-game marriage” between Lu and Yang had no legal bearing, so Li Lan stands as the inheritor of Lu’s properties. But because Yang spent a similar effort in helping Lu to acquire the artifact, its ownership belongs to both, so both Li Lan and Yang Yuan are entitled to 50% each of the asset’s price.

Another case in 2024 tackled a deceased user’s Bitcoin holdings, a gaming account worth nearly $30,000 (RMB 200,000), and a social media account. According to Chinese lawyer Wang Lianghua on the Chinese social media platform Toutiao [machine translated], the inheritor’s lawyer argued that virtual property has attributes of legal property because it could be traded, has value, and could even generate profits, which meets the “scarcity, disposal, and value” definitions of property. On the other hand, the platforms holding these digital assets argued that ownership belongs to them based on the agreements that the user accepted when signing up for the account.

The court judged that virtual assets, including Bitcoin, game equipment, social media commercial rights, and domain names, among others, are included in the deceased’s estate and are inheritable, and that operation of social media accounts can also be passed on to the heirs. However, private content, such as chat records and other “purely personal interests,” cannot be passed on and are instead archived by their respective platforms. Lastly, the “inheritance prohibition” included in most license agreements is invalid as they violate statutory rights — platforms are required to assist with inheritance requests and could ask for supporting documentation as well as charge reasonable costs.

Aside from these cases, there was another one where a mother lost her son and asked a gaming platform to give her access to his accounts. The court ruled similarly as the previous case, saying that the gamer’s accounts, character data, virtual items, and other assets are virtual property, and thus, inheritable. The company was then obligated to cooperate with the mother and transfer all inheritable rights to her.

These court cases offer a stark contrast in most of the rest of the world, where publishers could cut you off from your media library the moment their licensing contracts expire. The Steam subscriber agreement also prohibits the transfer of a Steam account — and with U.S. courts counting games as digital licenses, then Valve cannot be compelled to pass them on to the user’s heirs. Digital rights are a hot topic among gamers and consumers, especially as many big tech companies transition from selling physical copies of games to going all digital, and preservationists fight to keep game archives alive.

OpenAI CEO Sam Altman said during a staff Q&A meeting that its latest model, GPT-5.6, is available in limited preview to only a small group of customers handpicked by the U.S. government. According to The Information, the federal government, specifically the Office of the National Cyber Director and the Office of Science and Technology Policy, asked the AI tech company to stagger the release of its latest model. While Altman did not mention how long the delay for the general release of GPT-5.6 will be, he said in a memo that he hoped it would happen in a couple of weeks. In the meantime, the U.S. government is granting access to the latest model on a case-by-case basis only.

Despite OpenAI’s agreement to the delay, sources say that Commerce Secretary Howard Lutnick called Altman to warn him against releasing GPT-5.6 to the public without prior approval from government agencies. “We’ve made clear to the U.S. government that this is not our preferred long-term model and will work with them and others in industry to achieve a more sustainable approach for future releases,” the OpenAI chief said in the Thursday memo.

This wasn’t the first time that an American AI lab has delayed the release of its frontier model due to security concerns. Back in early April, Anthropic released Claude Mythos Preview to select key institutions first, allowing them to prepare for the general release of the powerful AI model. It eventually built Fable 5, a watered-down version of Mythos with built-in safeguards to prevent misuse, and released it in June 2026. However, the U.S. government disagreed with the company’s belief that it was a safer model and put both Fable 5 and Mythos on an export control list just three days after it dropped. This meant that foreign nationals, even those who work for Anthropic, are banned from accessing the model. Since the company cannot enforce compliance, it just decided to pull the model completely from the market.

The increasing advancement of AI models has the White House scrambling to prevent them from falling into the wrong hands. This is especially true as it continues to compete with rival China for supremacy. Although the U.S. has taken steps like export controls to slow Beijing’s progress, many industry leaders believe that it’s only a matter of time before the East Asian country catches up. So, even though the Trump administration initially promised that it would reduce regulations to help AI advance much more quickly in the country, President Donald Trump has changed his tune and signed an executive order earlier this month that asks U.S. AI labs to give the government access to their latest models 30 days before it gets a general release.

However, this move has got some industry experts concerned. “…this escalation of government intervention is nothing to celebrate. It is horrible for the broader AI ecosystem,” Head of AI Policy and think tank Abundance Institute and former FTC Chief Technologist Neil Chilson said in their blog. “Continued arbitrary, unexplained deployment of export control authority will make companies slow-walk new models, depriving the public of powerful new tools. Every AI model, like all software before it, will have vulnerabilities that require patching. The US government should not hang a Sword of Damocles over every lab’s head, with no indication when it might drop or why.”

Meta has suspended an internal AI training program after an internal data leak exposed sensitive employee information company-wide, according to a Business Insider report on June 22. The program, introduced in April, was designed to help Meta train AI systems on real employee workflows by gathering data, but has now triggered internal backlash over privacy and data security.

Screenshots obtained by Business Insider showed that data collected through the program was more broadly accessible within Meta than intended. The exposed information reportedly included private employee conversations, performance-related data, transcriptions, and activity records. Meta classified the incident as a SEV 2, on an internal scale of 0 to 5, where SEV 0 is the most severe.

A Meta spokesperson confirmed that the company has paused the program while it investigates the incident. "We have carefully designed this program with privacy safeguards, and while we have no indication at this time that any data was improperly accessed by Meta employees, we're pausing it while we investigate," the spokesperson told Business Insider. The incident does not appear to be an external hack but rather an internal data mismanagement.

Meta introduced the program, called the Model Capability Initiative, to monitor employee behavior for use in improving its AI models. The program, which the company reportedly made mandatory for most staff, collected data on employees’ work activities, including keystrokes, mouse movements, conversations, transcripts, and performance-related information.

Employees were reportedly uncomfortable with the idea of their keystrokes and mouse movements being recorded for AI training. Now they're finding out the data may not have been properly protected, and was widely accessible across the company rather than restricted to intended viewers.

Screenshots reviewed by Business Insider reportedly showed employees criticizing the failure to lock down the data from the start. “I am incensed,” one employee wrote in an internal group, according to the report. Another said there was no evidence of malicious access, but called the lack of promised restrictions “super frustrating.”

The episode is the latest in a frustrating stretch for Meta's workforce. The company has cut thousands of jobs in part to fund AI infrastructure behind more powerful AI systems; the same class of systems that Meta and other companies are deploying to replace workers. Building these models also requires vast amounts of training data, and Meta turned to its own employees to supply it, a move most employees were reportedly against. Now these employees have learned that the data they were compelled to hand over was not adequately secured, leaving it exposed to much of the company.

The U.S. Department of Justice (DOJ) has filed a memorandum in response to NAACP’s lawsuit against Elon Musk’s xAI (now SpaceX) Colossus 2 data center. According to Wired, the federal government, through the DOJ, said that stopping the natural gas turbines needed to run the xAI data center “threatens American national, economic, and energy security by seeking to shut off the power supply for artificial-intelligence innovation that supports the Department of War’s military operations.” It further said that Grok is one of only four AI models the military and security agencies use to “support mission-critical operations across Secret and Top-Secret classified networks.”

Due to those purported national security interests, DOJ lawyers have joined xAI and the state of Missisippi in requesting that the lawsuit be dismissed.

The NAACP, through the Southern Environmental Law Center (SELC), sued xAI last year after an investigation discovered that Musk’s Colossus supercomputer facility used “illegal” generators to power its AI GPUs. The Memphis supercluster was launched in just 19 days — a major feat given that most projects of this scale usually take four years, according to Nvidia CEO Jensen Huang.

The site officially powered on in July 2024, but it wasn’t May 2025 that it became fully operational after it received 150MW of power from Memphis Light, Gas, and Water (MLGW) and the Tennessee Valley Authority (TVA). But instead of waiting months to get connected to the grid, xAI bridged the gap with mobile generators to get the electricity needed to run the hundreds of thousands of power-hungry GPUs.

It turns out that xAI failed to secure the permits needed to run the majority of these units. It’s been reported that the company applied for 15 portable turbines, but thermal images show at least 35 units on site. The company is allegedly using a loophole that allows it to run these units for 364 days without needing paperwork, but the Environmental Protect Agency (EPA) has since closed this loophole.

Aside from the offending generators in the first Colossus site, which is rented out to Anthropic, 27 natural gas turbines at Colossus 2 were cited as noncompliant in the initial lawsuit filed in April 2026.

However, as of May 2026, the SELC says that 57 turbines on the site are operating on site without a permit. According to the nonprofit, this resulted in a 111% increase in nitrogen oxide exhaust, an 83% jump in PM2.5 pollutants, and an 88% uptick in formaldehyde emissions since these generators were added. The lawsuit argues that these emissions endanger public health, and that continued use of the turbines “increases risks of asthma attacks and heart disease” in the surrounding communities.

In response to the DOJ's filing, the SELC issued the following statement: “With this filing, the Trump administration is launching an unprecedented attack on the public’s ability to defend themselves from illegal pollution. This is a blatant attempt to let well-connected corporations like xAI unlawfully pollute without any consequences, putting communities across the country at risk and threatening to open the door to large-scale pay-to-pollute corruption in the process,” SELC Litigation Director Kym Myer said. “The Department of Justice’s frivolous arguments fly in the face of decades of well-established legal precedent and we look forward to fighting them in court.”

The case is National Association for the Advancement of Colored People et al v. X.AI Corp. et al, filed in the United States District Court for the Northern District of Missourt.

Oracle's Project Jupiter data center is definitely an ambitious one, as its area spans 1,400 acres, or around 1,601 football fields, using a standard measuring unit. The build location is Doña Ana County, a rural desert area in the state of New Mexico with limited water supplies. As has become a common theme lately, the data center's water usage has become the focal point of a heated debate between residents, the county, and the developers, as detailed in an NPR report.

Residents are naturally concerned that an already-scarce resource will be drained further still, especially considering that the area's underground water level has been steadily dropping in recent years, forcing farmers to dig deeper wells to find a supply. Furthermore, the region is one of many affected by a Supreme Court decision meant to avoid draining the Rio Grande. New Mexico must reduce groundwater consumption by 5.9 billion gallons per year for 10 years. In Doña Ana and other affected areas, this means planning out the retirement of farmland, with all the economic and social impact that entails.

With all that going on, plus the overall zeitgeist around AI data centers, Jupiter's buildout generated quite the discussion. Most of the residents' concerns appear to come from the older build projects that included a power generation setup comprised of natural gas turbines and diesel generators, estimated by third parties to require at least a million gallons of water a day. However, Oracle claims it dropped that plan entirely in late April, turning instead to a solid-oxide fuel cell power plant that also has far lower carbon dioxide emissions.

Regarding the cooling for the data center itself, the firm has bought the water rights from a sod farmer who reportedly wasn't using them in full. Oracle says it's going to use a closed-loop system that will require a one-time fill of around 11 million gallons of water, spread across four buildings, and a maximum of 4,000 gallons per year for top-offs. The fuel cell system seemingly needs a 1-million-gallon initial fill and 168,000 gallons a year for top-offs, which Oracle says is less than the yearly water consumption of two average households. In an op-ed about the situation, the company calls these figures "negligible."

For once, the company may actually have a point. Those figures sound large in isolation, but according to a report for 2020, the county's farming used 410,000 acre-feet of water, equivalent to about 366 million gallons a day. The remaining daily usage for the county works out to approximately 45 million gallons a day. Although there's no shortage of stories about data centers draining local water supplies, their global usage is a figurative drop compared to activities like mere landscaping and golf courses, let alone industrial and farming use.

Oracle's revised plans and figures are all pretty recent, however, and Doña Ana residents claim they were barely given any time to properly analyze the proposals, or offered information about specific areas of impact for the drainage, particularly when the project proposal kept changing throughout the past year. State Rep. Micaela Lara Caden criticized the process, stating that it was "a $165 billion vote on a proposal that we knew about for less than a month".

In a council meeting last year, attendees asked the vote to be delayed, only to see four out of the five commissioners giving it a yay, prompting shouts of "recall!" by the audience. Susana Chaparro, the commissioner who voted "no," still holds reservations to this day, a sentiment shared by environmentally-minded people in the county. A local chile farm owner believes the county needs the project, but reportedly described the manner in which the county presented the project as "a fiasco."

Doña Ana is an embattled region, however, and Oracle pledged $360 million for schools and infrastructure, $50 million to upgrade a water utility that was found not to have been filtering out arsenic, and $12 million straight into the county's coffers. For a modest county with just over 220,000 residents and 40 settlements lacking paved roads and sewers, these figures represent a nigh-believable windfall. Manny Sanchez, the county commission's chairman, reportedly stated that "we've never had that type of money here in Doña Ana County."

A Meta data center project is reportedly causing issues in Morgan County, Georgia, where the community’s water supply has turned turbid right after it was constructed. Rep. Alexandria Ocasio-Cortez (D-N.Y.) showed the muddy water to the Environmental Protection Agency (EPA) Assistant. Administrator for Water Jessica Kramer during a congressional subcommittee hearing, asking if the office is looking into how data centers affect water quality across the nation. You can see the exchange in the embedded post below.

AOC: This is what drinking water in Georgia looks like after Meta began data center construction in the community.

— @acyn.bsky.social (@acyn.bsky.social.bsky.social) 2026-05-22T15:02:01.633Z

“This is the current drinking water in Morgan County, Georgia, right after a data center was constructed, the Meta data center was constructed. The only difference between the clean water and this was that data center,” Rep. Ocasio-Cortez said during the hearing while showing the jars of dirty water. She also added, “These families now have to ship, in a rural area, have to ship water to their house in order to cook and bathe themselves. Now I'm curious if the EPA plans any investigations on how data centers are affecting water quality and availability. I understood what you said about the rule, but are there going to be any open investigations on this issue?”

Kramer, for her part, said that she will investigate the issue as soon as she gets back to her office, saying, “It is a priority to ensure that water quality standards established by EPA are being met. And so, we'll be looking into that, certainly.”

A video by More Perfect Union, a progressive media and advocacy group, on YouTube Shorts showed that the residents in this rural part of Georgia use private and community wells, taking water directly from under the ground. However, their only source of water has allegedly become undrinkable since the data center construction began, and they also pointed to a significant groundwater recharge area, where water from the surface collects underground. The county government protects these areas as surrounding communities rely on them as a water source, and the nearby areas must be managed to minimize the threat of pollution.

It’s currently unclear what caused the water quality to drop in Morgan County. While it happened after the Meta data center construction began, correlation does not automatically equate to causation. One possibility is that the turbid water coming out of the wells of Morgan County residents is a sign that the water table is getting too low, and their pumps are now taking in water from the well bottom, where mud and sediment settle. When you combine that with reports of data centers using up a ton of water, then it is understandable that some in the community would blame the data center project for their water woes.

This also isn’t the first time that a data center project has allegedly created a water supply issue. Another massive project located in Georgia has reportedly secretly siphoned off 29 million gallons of water in a year and three months, resulting in low water pressure for residents. There have also been many concerns about these sites driving higher electricity prices for large swathes of the U.S., as well as possibly cutting out the lights for an entire town. We’ve also seen noise complaints coming from these developments.

All these issues have got many people complaining about these developments, with 7 out of 10 Americans now opposing data center developments near their homes. And even as AI tech companies and hyperscalers are pushing for more compute, more jurisdictions are passing data center bans all over the country.

Following a last-minute deal yesterday between Samsung Electronics and its South Korean workers’ union, the company will reportedly distribute 40 trillion won ($26.6 million) in bonuses to chip employees. According to a Bloomberg report, the bonus, which will vary by employee, will result in an average payout of 513 million won (~$339,000) per employee in Samsung’s semiconductor division, based on proposed terms and projected 2026 operating profits. Other estimates put the figure at around 600 million won (~$396,000).

As part of the tentative deal — which narrowly averted a strike originally scheduled to begin May 21st — Samsung has reportedly agreed to distribute 10.5% of its profits as employee bonuses in the form of stock, plus another 1.5% in cash. The union initially requested 15%. Addressing another major union demand, the new bonus program will continue for 10 years — rather than a one-off payment — provided specified profit targets are met.

The union plans to vote on the deal internally over the coming week. Should the deal pass, employees will likely receive the bonuses in early 2027. The agreement permits employees to sell one-third of the shares right away, and the remainder in installments over two years, according to Bloomberg.

The deal comes after months of escalating labor unrest centered on employee bonuses. Labor unions demanded a revision of Samsung’s bonus structure that would allow employees to earn more, as the company’s profits surge amid the AI-driven semiconductor boom. Bloomberg estimates Samsung’s 2026 operating profits will multiply sevenfold to 330 trillion won (~$218 billion).

The unprecedented profits are projected as the AI infrastructure boom has transformed memory chips — once a cyclical commodity business — into one of the most lucrative industries on earth. Demand for High Bandwidth Memory (HBM) and other AI-oriented components has triggered what analysts are calling a semiconductor supercycle. The workers at the center of this boom argue that since they are active facilitators of the hardware, they deserve a share of the profits. Samsung is notably not the first major Korean chipmaker to reach this conclusion. Last September, SK Hynix settled with its own union to allocate 10% of annual operating profit directly to employees as performance bonuses for the next decade, while removing caps on bonuses.

The payouts themselves are extraordinary by almost any conventional corporate standard — but then again, so are the profits currently flowing through the AI semiconductor ecosystem. Reports suggest the payouts are having a broader impact on the industry. Jobs at Samsung and SK Hynix were already coveted in South Korea. However, with potential bonuses that can exceed the lifetime earnings of workers in other sectors, competition for roles is sky-high. The bonuses are also reshaping decision-making within the companies themselves. We recently covered reports that Samsung and SK Hynix employees were considering terminating prestigious overseas training opportunities to remain eligible for bonuses.

Bandera, Texas, a small town of around 900 residents located about 40 miles northeast of San Antonio, Texas, opted to cancel its Flock AI contract. Three of the five-member town council voted to end the AI company’s services, after months of complaints from people who are wary about AI-powered government surveillance. However, one of the two people who wanted the security program to continue has publicly crashed out: According to 404 Media, councilor Jeff Flowers proposes that the town go back to a pre-digital age if its people want complete privacy.

“For months, I have listened to the outcry regarding License Plate Recognition (LPR) technology. I have seen the eyerolls, and I’ve even been met with ‘Nazi rhetoric,’ the dangerous claim that believing in accountability and community safety is somehow equivalent to totalitarianism. Comparing a neighbor’s desire for a safe street to a dark chapter of history is a classic case of comparing apples to oranges; it is a distraction used to avoid the reality of the threats our town faces today,” Flowers wrote in the local newspaper.

He also added, “Let’s take Bandera back to 1880 properly. No double standards, no hypocrisy. If LPRs are ‘unconstitutional’ and invade our right to ‘public’ privacy, we need to be courageous enough to go all the way. I look forward to the ‘Privacy First’ crowd showing up to support these bans [...] just remember to leave your phones at home.”

The town received a grant from the state of Texas to have eight Flock Safety AI license plate readers installed, but it turns out that its people do not want it. One resident said during a town hall that the community did not vote on the installation of these cameras, with another saying, “We don’t need to implement mass government surveillance in our town.” Aside from the protests during town meetings, the cameras themselves were repeatedly vandalized and had their poles cut down. The town had to pay for these repairs, meaning keeping the cameras operational is costing it extra.

Flock’s AI-powered license plate readers are in the center of several debates about security and privacy across the nation. While law enforcement agencies have praised the central database system used by the company, it’s also the same feature that has many people concerned. It’s feared that the authorities will use the data gathered by these cameras for targeting minorities and protesters, especially as reports have surfaced that immigration authorities have allegedly accessed the data gathered by the company without informing local police.

Bandera isn’t the only municipality to have turned off their Flock cameras. TechSpot says that at least 53 other jurisdictions located in 20 states have rejected the surveillance system in just the past six months. Flowers is framing the townspeople’s rejection of the AI-powered LPR system as a pushback against technology — but residents’ concerns aren’t just about privacy: they’re also about trust.

Samsung Electronics has narrowly avoided an 18-day strike at its South Korean chip operations after reaching a last-minute tentative wage agreement with its labor union on Wednesday — just hours before workers were due to walk out.

The union, representing nearly 48,000 members, said it would suspend the general strike planned for May 21 to June 7 and put the deal to an internal vote. Voting is expected to run from May 22 to May 27, though some notices put the window at May 23 to May 28. If members approve it, the tentative agreement becomes formal; if they reject it, the strike threat could return.

The deal followed last-minute talks involving Samsung management, union leaders, and South Korea’s labor ministry. Labor Minister Kim Young-hoon helped restart negotiations after earlier discussions broke down. Samsung’s Device Solutions negotiator, Yeo Myeong-gu, and union leader Choi Seung-ho signed the tentative agreement in Suwon.

Exact terms of the agreement have not been fully disclosed, but the dispute centered on performance bonuses. The union had pushed for Samsung to allocate 15% of annual operating profit to employee bonuses and scrap a 50% annual salary cap on performance payouts. Samsung had resisted those demands, arguing that profit-sharing across its businesses was complicated because its booming memory division and weaker logic/foundry operations were performing very differently.

The breakthrough caps months of escalating labor unrest. Dissatisfaction grew among workers as Samsung’s semiconductor profits surged on AI-driven memory demand, with workers comparing their payouts to those at rival SK Hynix, which has offered more generous bonus structures.

After earlier talks collapsed in February and March, the union threatened a May general strike. Further negotiations were scheduled for May 11 and 12, but the penultimate talks broke down again on May 12 without a deal. Leaked transcripts from the talks alleged that Samsung offered memory workers a 607% bonus worth $477,000, while logic chip staff were to get as little as 50%. The union rejected the proposal — citing a potential retention crisis due to the imbalance — and threatened to proceed with the strike.

The union had already demonstrated its ability to disrupt operations via a one-day strike that reportedly saw over 40,000 workers participate and caused night-shift output at Samsung’s foundry operations to fall sharply, with memory output also hit.

Ahead of today's deal, the May 21st strike seemed inevitable, with Samsung reportedly winding down chip production in preparation. Samsung had also obtained last-minute court injunctions to limit the impact of the strikes before direct government intervention helped bring both sides back to the negotiating table.

Analysts and officials warned of potential disruptions to chip supply and major economic damage in South Korea. One estimate cited possible daily losses of around 1 trillion won if production halted, while others warned of tens of billions of dollars in broader economic risk.

For now, that risk is suspended — not eliminated. The immediate question is whether Samsung’s union members accept the tentative wage deal. Approval will defuse the company’s biggest labor crisis in years, while a rejection will put the strike back on the table at one of the most sensitive points in the global AI chip supply chain.

Samsung and SK Hynix employees are reportedly rejecting overseas training programs in favor of bonuses while seeing their matchmaking grades rise on online dating sites. According to the Korean Media outlet Chosun, discussions on Samsung Electronics’ internal bulletin board indicate that employees are considering choosing potential bonuses over hard-earned, typically coveted training programs. The sentiments come amid projections that the company plans to distribute “record-high” performance bonuses due to profit surges from the AI-driven semiconductor boom, with the company’s policies restricting eligibility.

According to the report, Samsung Electronics has exempted employees currently undergoing overseas training from bonus eligibility. This stance is reportedly seeing a number of employees terminating their training to return to their roles. Samsung runs a highly sought-after training program that provides employees around their 7th year at the company with financial and operational support to pursue postgraduate degrees at prestigious institutions both in and outside Korea. For example, in addition to their annual salaries, the company provides employees pursuing an MBA in the US with 500 million Korean won (~$333,000) in tuition and living expenses over two years. The support varies across institutions and countries.

The program is typically highly competitive, with only 1 in 70 applicants succeeding. Now, following projections that the electronics giant could distribute an average of 600 million (~$400,000)won in bonuses to employees in the semiconductor division, interest in the training programs has dropped. Reports suggest that even those currently undergoing training are considering halting midway to be eligible for performance bonuses, as these are likely to outweigh the financial benefits of the training program.

According to the Chosun report, sources from Samsung Electronics stated, “There have been inquiries to the HR team about whether trainees can withdraw mid-program and if they must repay previously received company support.” indicating that despite potential repayment obligations, some employees are willing to return regardless.

These reports are coming even as Samsung Electronics employees are planning industrial action to compel the company to extend continuous performance bonuses to employees outside the semiconductor division. The company says only employees in the semiconductor division will receive ongoing bonuses, while others in other divisions will receive a one-time payment. The strike is scheduled for the 21st of May.

At Samsung’s competitor, SK Hynix, similar reports of employees abandoning training in favor of bonuses are emerging. Despite the fact that SK Hynix takes a softer stance by offering partial bonuses to training beneficiaries, anonymous posts on its internal board reportedly include comments like, “If next year’s bonus reaches 700 million Korean won (~$466,000), not abandoning the training might make me a sudden pauper overnight” and “Seeing the projected bonuses for next and the following year, I want to cut off the hand that applied for the training.”

These comments follow projections of even bigger bonuses in the coming years, as SK Hynix paid out 140 million Korean won (~$93,000) in performance bonuses early this year, which, unlike at Samsung, was distributed across the entire company. Analysts predict a dip in the popularity of overseas training programs at Samsung Electronics and SK Hynix over the next few years, as the appeal of performance bonuses grows. SK hynix bonuses are tipped to hit $477,000 this year and as much as $900,000 next year.

Beyond strikes, life-changing decisions, and financial gain, these massive performance bonuses stemming from AI-driven profit surges are influencing quite unexpected areas of life in South Korea. Reports from Chosun indicate that SK Hynix employees are ranking higher on matchmaking companies’ eligibility scales due to bonuses and increased income, with employees reportedly being flooded with blind-date offers.

"In the past, if we matched a partner for an SK hynix employee at about a B+ grade, now it's unconditionally 'A-grade.' As the overwhelming bonus system has become known, we're seeing a trend where female members are seeking out SK hynix employees first,” said Son Dong-gyu, CEO of the matchmaking company Bien Aller.

However, on the flip side, because bonuses are paid in direct proportion to days worked, there has been an uptick in aversion to taking extended leave, such as parental leave, as these are reportedly perceived as forfeiting income. These reports all underscore the massive influence of the AI boom on almost every aspect of humanity.

Arm Holdings, the maker of the popular Arm architecture used by Qualcomm, Apple, and several other companies, is facing an antitrust investigation as the U.S. Federal Trade Commission (FTC) looks into the company’s operation. Bloomberg reports that the FTC is determining if the company is trying to monopolize the Arm architecture and either only give customers lower quality designs for their own semiconductors or outright deny them access to its licenses. The move comes as Arm launched its own AGI CPU focused on data centers in March 2026, a significant departure from the company, whose business previously focused on licensing its chip designs to other companies.

The company’s legal troubles began when it sued Qualcomm, the biggest manufacturer of smartphone chips, for using Nuvia’s ARM licenses after it acquired the startup in 2022. Arm Holdings argued that the smartphone chipmaker cannot use Nuvia’s licenses after its acquisition, and that it should have acquired a new one to continue using the startup’s designs based on Arm licenses. Arm ultimately lost the case, allowing Qualcomm to continue using the Oryon cores it acquired from Nuvia.

The Qualcomm lawsuit broke the longstanding relationship the two companies had, and it also opened a can of worms for Arm. The former launched a global antitrust campaign against the latter because of the case, saying that it was using its dominant market position to prevent competition. It reached out to the European Commission, the U.S. FTC, and Korea’s Fair Trade Commission to present its case, with the Korean government agency raiding Arm’s Seoul office in November 2025.

While the x86 processor still has the advantage when it comes to desktops and laptops, its advantage is slowly being eroded by Arm-based Apple Silicon and Qualcomm’s Snapdragon X-series chips. On the other hand, it has cornered the mobile market, with Apple, Qualcomm, Samsung, MediaTek, and other mobile device chipmakers using Arm architecture. Some analysts also say that it will eventually dominate the AI server industry, with over 90% of custom processors expected to use an Arm chip by 2029.

Arm’s launch of its own AGI processor has got its customers (and now potential competitors as well) wary of its status as both chip designer and manufacturer. Arm did not introduce a processor for consumer computing, meaning it hasn’t directly challenged some of its biggest customers. However, the fact that it has expanded into building physical chips has worried them that it could leverage the popularity of the Arm architecture to gain an unfair advantage and limit competition.

Intel has announced a multi-year strategic partnership with F1's legendary McLaren Racing team. The chipmaker is now the Official Compute Partner of the McLaren Mastercard Formula 1 Team, Arrow McLaren IndyCar Team, and McLaren F1 Sim Racing Team, according to a press release today. Interestingly, this announcement again pits Intel against its PC chip industry nemesis, AMD. The Red Team has already been working in partnership with the Mercedes-AMG Petronas Formula One Team for six years.

Intel's PR blurb says F1 racing is "one of the world’s most technologically demanding sports." Thus, Intel engineers will be tasked with delivering advanced computing for AI and high-performance architectures that are required to keep McLaren competitive.

The new agreement means that systems using Intel Xeon and Core Ultra chips will be leveraged to support McLaren's quest for the ultimate performance on the track. Specific calculations that F1 engineers spend their days optimizing for include "performance-critical workloads, including computational fluid dynamics, aerodynamic analysis, vehicle-dynamics simulation, [and] race strategy analytics." As well as real-time data, F1 support computers are used to sift through massive volumes of post-race data. Computers used to optimize F1 racing cars are also increasingly using AI tools, plus low-latency edge computing solutions, and diverse software platforms.

"Formula 1 racing and IndyCar are some of the ultimate proving grounds for high-performance computing. Intel is proud to be McLaren Racing’s compute partner, and to be part of a team that thrives on precision, speed, and innovation," said Lip-Bu Tan, Intel CEO. "Together, Intel and McLaren will push the boundaries of what’s possible, transforming data into competitive advantage at every turn."

A statement by Zak Brown, CEO, McLaren Racing, confirmed Intel hardware had already been an important part of the F1 team's tech ecosystem. It will be interesting to see if the new, closer relationship will produce noticeable results on the circuits around the globe, burning rubber at speeds pushing beyond 230 mph.

As we mentioned in the intro, AMD has already been working closely with a major F1 team for years. The firm has a page dedicated to how AMD Epyc and Threadripper processors are a competitive edge for the Mercedes-AMG PETRONAS Formula One team. Similar to Intel's announcement today, the AMD/Mercedes partnership uses advanced compute for "aerodynamic simulation and faster data analysis."

AMD's partnership with Mercedes-AMG was forged back in 2020, which might explain why there's no mention of artificial intelligence in the linked PR blurb, yet.

Amazon is the latest hyperscaler where employees have been caught inflating AI token consumption to hit internal usage targets, following similar behavior documented at Meta and Microsoft last month, the Financial Times reports.

The company set targets requiring more than 80% of its developers to use AI tools each week and tracked consumption on internal leaderboards. Some employees told FT they had been using MeshClaw, an in-house agent platform that can initiate code deployments, triage emails, and interact with Slack to maximize their token numbers. Amazon said usage statistics would not factor into performance evaluations, but multiple employees said they believed managers were monitoring the data. One said there was "so much pressure to use these tools," another described how tracking created "perverse incentives."

The practice — dubbed "tokenmaxxing" — has become widespread enough to generate its own vocabulary and leaderboards, but beyond workplace culture, if a meaningful share of AI consumption is performative, how reliable are the demand figures that hundreds of billions in AI infrastructure procurement are being allocated against?

Combined 2026 capex from Amazon, Microsoft, Alphabet, and Meta is tracking between $650 billion and $700 billion, with some Wall Street projections exceeding $1 trillion for 2027, and every hyperscaler has told investors that inference capacity is being absorbed as fast as it can be deployed. Internal developer consumption is obviously part of that absorption, and it sits alongside paying external customers in the usage data that informs the likes of capacity planning, GPU orders, HBM procurement, and power infrastructure.

Tokenmaxxing doesn’t mean the demand is fabricated — enterprise AI adoption is broadening, and inference workloads are scaling into production — but there’s a distinction between adoption and consumption intensity. The former is a durable driver of demand, whereas the latter is gameable, and it’s currently being amplified by the incentive structures that these companies built. The water is further muddied by reports that AI is more expensive than actual workers.

Meta's internal leaderboard lasted days after public exposure, and Amazon recently restricted visibility of team-wide usage statistics. And when measurement shifts, the consumption intensity they incentivized will shift with them.

Nvidia CEO Jensen Huang has highlighted per-engineer token consumption as a key metric, stating he’d be "deeply alarmed" if a $500,000-a-year engineer was not consuming at least $250,000 in tokens. Nvidia's inference growth obviously depends on that consumption being a productive workload that persists and compounds because every inflated token is real GPU time.

Angie Jones, formerly VP of engineering for AI tools at Block, told LeadDev she expected the industry to pivot toward measuring efficient token usage rather than celebrating volume. In a cycle where GPU orders and power commitments are being placed years in advance, the quality of the demand projections behind them matters. The hyperscalers are building for a world where every knowledge worker consumes hundreds of thousands of dollars in annual compute. Whether that consumption proves productive or performative will determine how much of this year's $700 billion generates durable returns.

Jobs cuts related to increased AI usage have practically become background noise at this point, but there's still the occasional outlier that merits inspection. In this case, Cloudflare announced both its quarterly results and the fact that it's cutting 20% of its workforce over this year — to the tune of 1,100 heads.

Although Wall Street investors are usually amenable to job cuts, as they're generally seen as source of added short-term profit, this time around the market didn't react kindly at all, tossing Cloudflare's stock price down a cliff to the tune of a 19% drop in one day alone — nearly a 24% drop for the week. In a tweet, CEO Matthew Prince noted that "very few engineers or customer-facing sales people" are impacted by the layoffs, and that the firm wants to "continue to hire like crazy" for those roles.

The firm expects to take a $140-$150 million charge associated with the job cuts, and the soon-departed also ought to receive equity in the company as of their professional passing. The Q1 2026 results actually matched or beat both its revenue and Earnings Per Share (EPS) estimates — with a revenue of $639.8 million (up 34% year-over-year) and an adjusted EPS of $0.25 (beating the expectation of $0.23). Also, it's worth noting that Cloudflare is still up around 30% since the start of the year.

It's hard to pin down why investors are so disappointed, but perhaps the reason is that Cloudflare issued Q2 2026 guidance stating that its revenue will be around $644.5 million — a figure described as "just shy" or "below" estimates, thus displaying a lack of growth. Stockholders may have gotten the impression that the company needed the job cuts for financial growth in this environment, but, as the old adage says, markets will do market things.

As befits any harsh breakup, Cloudflare's management sent out a long message to employees detailing the why and how of the move. The company claims it increased the usage of AI "by more than 600% in the last three months alone," noting that most every part of the company runs "thousands of AI agent sessions" daily. Thus, Cloudflare believes it "[has] to be intentional in how we architect our company for the agentic AI era," and notes that the decision is "is not a reflection of the individual work."

U.S. District Judge Jon Tigar has denied Nvidia's request to dismiss a copyright infringement case filed against it, arguing that it’s not liable for how clients use its AI-powered NeMo Megatron Framework. According to TorrentFreak, Nvidia is asking the court to dismiss the direct copyright infringement claims that are connected to its use of the Bibliotik eBook torrent tracker, the Books3 dataset, and 'The Pile' dataset for language modeling. Nvidia then cited the Cox vs. Sony ruling, where the U.S. Supreme Court ruled that a service provider is not liable for any piracy that its users might carry out.

Nvidia said that its NeMo Megatron Framework has significant “non-infringing uses” and that it did not promote it as a piracy tool. This should fall under Justice Clarence Thomas’ decision saying, “Under our precedents, a company is not liable as a copyright infringer for merely providing a service to the general public with knowledge that it will used by some to infringe copyrights.” Unfortunately for the company, Judge Tigar disagreed with its argument, saying that it’s not the framework, but specific scripts within it that violated copyright rules.

He said that these were intended to make it easier for users to automatically download and preprocess The Pile dataset, which the complainants said allegedly contained copyrighted work. “The scripts are alleged to have no other purpose than to speed up the process of infringement, unlike the digital video recorder systems at issue in Sony Corp. or the internet service provided in Cox,” Judge Tigar wrote. Bibliotik is a private eBook torrent tracker, which allegedly contains over 197,000 books. It was then included in the Books3 dataset, which itself was included in the 800+ gigabyte The Pile dataset. The Pile was then used for training Nvidia’s AI LLMs, resulting in several authors filing a class action lawsuit against the company for copyright infringement.

There have been previous cases of copyright infringement related to AI companies scraping data for training their models. Aside from this case against Nvidia, Meta has also been facing a similar lawsuit since last year. It even defended itself by saying that using pirated material is legal if you don’t seed content. Google has even been pushing to have AI scraping tagged as fair use, saying that it wants “copyright systems that enable appropriate and fair use of copyrighted content to enable the training of AI models in Australia on a broad and diverse range of data while supporting workable opt-outs for entities that prefer their data not to be trained in using AI systems.”

With this decision, the authors’ class action against Nvidia is set to move forward, and we will likely hear more details as the case progresses. We don’t have a date yet for when the next hearing will be, though. Still, we expect this to be a multi-year battle as the AI giant battles it out with allegedly infringed writers.

Negotiations between the National Samsung Electronics Union, which represents workers in the company’s chipmaking division, and management have seemingly broken down over a single issue. According to the Financial Times, the two sides are close to agreeing on an allocation of 13% of operating profit, which works out to be roughly $340,000 USD per employee, as a bonus to the workers. However, company management is only willing to give this as a one-time offer, while the union wants the allocation to be guaranteed annually and included in the agreement that the two sides will sign.

The issue about the bonus was brought to national attention when more than 30,000 Samsung workers took to the streets in late April to demand a bigger slice of the profits that Samsung is making from the AI infrastructure buildout. This demand stemmed from a comparison with SK hynix workers, who were guaranteed bonuses of $477,000 each this year, and almost doubled to $900,000 next year. Furthermore, these bonuses are guaranteed for the next ten years. The massive amount stemmed from the windfall that the memory and storage chip manufacturer is making from the AI infrastructure build-out, with AI data centers and hyperscalers willing to pay a premium just to secure the chips they need.

The workers argue that even though Samsung is much larger, their bonuses only equate to less than 30% than what SK hynix offers to its people. Their initial demand was a 15% cut in the semiconductor fab’s operating profit, a removal of the 50% bonus cap, and a 7% wage hike, while management countered with a 10% allocation, a 6.2% pay increase, and other benefits like preferential mortgage rates. It seems that the two sides have finally settled on the 13% bonus allocation, and the only question remaining is whether management will agree to a guaranteed annual bonus.

Samsung is facing the threat of a massive strike if the two parties fail to come to an agreement. The union said that it will conduct a general strike from May 21 to June 7 — meaning Samsung’s chip fab operations will be crippled for at least 18 days. It should be noted that the single-day action in April resulted in a 58% drop in production for just a single shift. Prof. Kwon Seok-joon of Sungkyunkwan University told the Financial Times that an action like this could cost Samsung somewhere between $6.9 billion and $11.7 billion in direct losses, with an even larger amount in indirect costs. Furthermore, it will damage Samsung’s reputation as a supplier for HBM4 chips, especially with the tight competition between the three major memory and storage chip manufacturers.

Kwon also noted that it’s harder for Samsung to just grant the bonus, even if it comes from operating profits and not revenue. Unlike SK hynix, which is a standalone fab, Samsung’s semiconductor fab operates under the larger Samsung Electronics company, which itself is part of the larger Samsung Group. Other arms of the company are said to be struggling because of the higher costs brought about by the chip shortage, even as the semiconductor division is making record profits.

If the fab workers get their desired bonus, workers from less profitable divisions might feel that they’re being short-changed. Because of this, a smaller union, whose members mostly come from Samsung’s smartphone, TV, and home appliances lines, has reportedly pulled out of the planned joint strike. Should management grant the semiconductor division’s demand for a bonus allocation of 15% of operating profits, Kwon told FT that “the maths gets uncomfortable fast.”

Intel has announced a pair of high-profile leadership appointments as it doubles down on its AI ambitions. According to an official press release today, the company is bringing in industry veteran Alex Katouzian to lead its client computing and emerging “physical AI” efforts, while Pushkar Ranade is coming in as Chief Technology Officer to steer the company’s long-term innovation strategy. The appointments clearly signal Intel's intent to more tightly align its core computing business with the rapidly evolving AI landscape, particularly at the edge and in real-world systems.

Alex Katouzian is joining as executive vice president and general manager of the Client Computing and Physical AI Group, a role Intel says will align its traditional PC-focused business with emerging AI-driven systems spanning robotics, autonomous machines, and edge devices.

Katouzian is bringing 25 years of industry experience from Qualcomm, spanning from when he joined as a senior engineer in 2002 to his last very senior role as executive vice president and group general manager of mobile, compute, and extended reality (XR).

He is widely regarded as a key figure in scaling Qualcomm’s mobile and compute platforms globally and is responsible for significant contributions to the industry, including the expansion of Snapdragon mobile platforms and Qualcomm’s push into PC and XR computing. Intel believes this experience will prove invaluable as the company moves to expand beyond traditional PCs into AI-enabled, connected, and edge-based computing ecosystems.

Speaking on the appointment, which officially kicks off this month, Katouzian expressed excitement about joining Intel at what he described as a pivotal moment for AI-driven transformation across computing platforms.

“Intel is creating the foundation for AI-driven transformation, from leading in AI PCs, to scaling AI inference at the edge, and accelerating the future of physical AI systems,” wrote Katouzian. “I’m excited to join Lip-Bu and the Intel team at this critical moment to help scale innovation and deliver the next generation of computing experiences.” Katouzian announced his departure from Qualcomm on LinkedIn.

The second appointment sees Pushkar Ranade transition to permanent Chief Technology Officer after serving in the role on an interim basis for several months. Ranade is not a new face at Intel and has been with the company for over 10 years.

According to Intel, his role will involve leading the company’s technology strategy, overseeing special technology initiatives, and driving development across emerging areas such as quantum computing, neuromorphic computing, photonics, and advanced materials. He will also serve as chief of staff to the company’s CEO.

Both appointments continue an existing trend as more tech companies pivot to a stronger AI focus. Microsoft, for instance, created a dedicated AI division led by DeepMind co-founder Mustafa Suleyman, alongside a series of follow-on hires to strengthen its AI leadership. Google has also brought in senior robotics leadership to push AI into physical systems.

You’ve probably seen a few examples of PC DIYers installing figurines in their elaborate, RGB-infused fishtank builds. Chinese TechTuber Soda Baka has scaled this phenomenon up to create a tower PC large enough for a human to work and play inside. What looks like a figurine in some of these PC pictures is actually the TechTuber posing. The video is shared on China’s Bilibili.

We aren’t 100% sure of the purpose of this build, other than spectacle, due to things getting lost in translation. However, a short skit in the video (machine translated) indicates the build was influenced by Baka’s little cousin being barked at by his mom “You play computer games all day, why don’t you just live in a computer!” Something like that.

We also get the feeling this is a canny video sponsorship deal as air conditioners start to become highly desirable, now that we are moving into warmer months in the Northern Hemisphere.

The human-habitable PC tower project gets underway with Soda Baka sketching and modeling before the construction begins in earnest. We see various huge components being fabricated, that look like case fans, GPUs, AiO CPU coolers, RAM sticks and so on. The TechTuber doesn’t forget to add splashes of RGB lighting, of course.

Some real-PC stuff is installed in the mega-PC, so there’s something to do once the side panel is put on… You can see Soda Baka sitting at a compact desk playing a game on the screen attached to the AiO – how modern.

Now things heat up, literally, as to simulate PC-scale heat at this large scale some hot-coal sauna installations are used. We see the TechTuber boosting the heat/humidity levels with a bottle of water. Apparently it doesn’t take long for the enclosed computer room (in the PC) temperatures to rise above 100°F (38 degrees Celsius).

Because all the huge fans and coolers are fake, our trapped TechTuber has to turn on the installed 12kW AC unit, which boasts 820m³/hr air circulation to cool the ‘PC system.’ Quickly enough the atmosphere changes to become “like a spring evening in the North [of China].” Was it all an elaborate Midea 3^rd Gen Pro AC unit sponsorship promotional video? Maybe it was.

Google, Amazon, Microsoft, and Meta plan to spend a combined $725 billion on capital expenditure in 2026, a 77% increase over last year's record $410 billion, according to first-quarter earnings reports compiled by the Financial Times.

Google led with 63% cloud revenue growth and an 81% jump in net income to $62.6 billion, while Meta's stock dropped 6% after hours despite a 33% revenue increase, punished by investors for adding $10 billion to its spending forecast and offering no firm timeline on new AI models.

But in the earnings calls, at least two of the four companies explicitly blamed rising memory chip prices for pushing budgets higher, confirming what market data and industry executives have been warning about for months.

Memory costs inside the capex

Microsoft’s CFO, Amy Hood, told investors that rising prices for memory chips and other components accounted for $25 billion of the company's record capex budget. Microsoft set its 2026 spending at $190 billion, far above the $152 billion average analyst forecast. Hood warned that even with the additional investment, Microsoft expects to remain capacity-constrained on GPUs, CPUs, and storage through at least 2026.

Meta cited the same, with the company raising its full-year capex range to $125 billion to $145 billion, up from a prior ceiling of $135 billion. In its earnings release, Meta attributed the increase to "higher component pricing this year, particularly memory," alongside rising costs for land, power, and skilled workers needed to build data centers that now consume 70% of the world's memory output.

The timing of all this is hardly coincidental, with TrendForce having reported DRAM contract prices rising roughly 95% quarter over quarter in Q1 2026, with a further 58% to 63% increase projected for Q2. NAND is following a similar trajectory, with Q2 contract prices expected to climb 70% to 75%. Server DRAM and high-density DDR5 RDIMMs are absorbing the bulk of production capacity, and all NAND output for 2026 is already committed, according to Phison CEO Khein-Seng Pua.

Hood's $25 billion, therefore, helps to put a dollar value on what has previously been an abstract concern: If one company's memory cost inflation alone exceeds the entire annual capex of most semiconductor firms, the pressure on consumer DRAM and NAND supply becomes much easier to quantify.

Google Cloud's contract backlog

Meta and Microsoft aside, Google’s Cloud revenue hit $20 billion in the same quarter, growing 63% year over year, outpacing both Amazon Web Services ($37.6 billion, up $8.3 billion) and Microsoft's Azure-driven cloud segment ($34.7 billion, up $7.9 billion).

Google's cloud contract backlog reached $460 billion, roughly double the $240 billion reported at the end of Q4 2025. Amazon reported $364 billion in its own pipeline, which will expand further after a recent $100 billion computing contract with Anthropic over the next decade. Microsoft's commercial remaining performance obligations hit $625 billion, up 110% year over year.

Cloud boss Thomas Kurian attributed Google's growth to its strategy of building custom AI chips, foundation models, and products in-house, telling the Financial Times that this gives the company a cost and research advantage over competitors that have struggled to develop their own chips and frontier models. Google's 7th-gen Ironwood TPU, which packs 192 GB of HBM3E per chip with 7.37 TB/s bandwidth in pods of up to 9,216 chips, is central to that strategy, and Anthropic has committed to access up to one million of them. Google recently unveiled its 8th-gen TPUs, which are split into two distinct variants for training and inference.

Alphabet raised its capex guidance to between $180 billion and $190 billion, up $5 billion from its previous guidance of $175 billion. CFO Anat Ashkenazi said he expects capex to “significantly increase” in 2027, causing shares to rise by some 7% after hours. It’s worth noting that $37.7 billion of Alphabet’s net income of $62.6 billion came from unrealized gains on non-marketable equity securities, primarily the company's Anthropic stake, according to the earnings release filed with the SEC. Strip that out, and operating performance was still strong, with a 36.1% operating margin, but the total net income number overstates recurring profitability.

Custom silicon and the GPU question

These capex figures reflect more than GPU purchases, because each hyperscaler is now deploying or developing custom accelerators to reduce dependence on Nvidia for inference-based workloads.

Amazon's Trainium3, built on a 3nm process with 144 GB of HBM3E and roughly 4.9 TB/s of bandwidth, is what CEO Andy Jassy described as "nearly fully subscribed" for 2026, and Meta has announced four generations of its MTIA inference chip, all fabbed at TSMC alongside Broadcom, even as it signed GPU deals worth roughly $110 billion combined with AMD and Nvidia. Meanwhile,. Microsoft's Maia 200 is deploying in U.S. Central data centers.

This pattern is likely to extend beyond accelerators as CPU demand for agentic AI workloads drives a parallel supply crunch with CPU lead times currently stretching to six months. Intel has reported billions in unmet Xeon demand, and Arm CEO Rene Haas has stated that agentic workloads require roughly 120 million CPU cores per gigawatt of data center capacity, four times what traditional AI training clusters need. Per Intel CFO David Zinsner, data center CPU-to-GPU ratios have already moved from 1:8 to 1:4, with further convergence expected to reach or go beyond parity.

Despite record spending, all four companies have acknowledged supply constraints that additional capital alone can’t resolve. Nvidia has booked an estimated 800,000 to 850,000 wafers of TSMC's CoWoS advanced packaging capacity for 2026, consuming over half of the total output and leaving AMD, Broadcom, and Google's TPU program competing for the remainder. CoWoS remains oversubscribed through at least mid-2026, and TSMC's U.S. packaging fabs aren’t expected to reach volume until 2028.

Power infrastructure is another bottleneck, with large power transformer lead times extending to roughly 128 weeks, and the IEA estimating that approximately 20% of planned global data center projects could be at risk of grid-related delays. TrendForce recently downgraded its full-year server shipment growth forecast from 20% to 13% because power management ICs and baseboard management controllers needed to assemble complete servers are stretching to 35- to 40-week lead times. Samsung's planned closure of its S7 eight-inch wafer fab in Korea will tighten PMIC supply further.

‘The bear thesis is garbage’

Meta's stock slipped by 6% after-hours following the earnings, erasing roughly $113 billion in market value. That drop reflected both the $10 billion capex increase and CEO Mark Zuckerberg's lack of a firm schedule for releasing improved AI models to follow the recently launched Muse Spark. Dec Mullarkey, managing director of SLC Management, told the FT that investors are concerned about whether Meta's historically capital-light business is becoming far more capital-intensive.

"The bear thesis is garbage," countered Brent Thill, an analyst at Jefferies, arguing that revenue growth across the sector justifies the spending. Zuckerberg offered little to settle the debate. Asked about Meta's AI agent development, he told investors he cared more about quality than deadlines, adding that most AI agents available today are not good enough for everyday users.

Amazon kept its $200 billion capex plan unchanged, and Microsoft CEO Satya Nadella said ending his company's exclusive contract with OpenAI was beneficial, claiming royalty-free access to OpenAI's frontier models and IP through 2032.

Meta CEO Mark Zuckerberg told employees at a company town hall on Thursday that the roughly 8,000 planned layoffs are a direct consequence of the company's ballooning AI infrastructure budget, Forbes reports. The cuts, which affect about 10% of Meta's workforce and are set to begin on May 20, come the same week the company raised its full-year 2026 capital expenditure forecast to between $125 billion and $145 billion, up from a prior range of $115 billion to $135 billion.

“We basically have two major cost centers in the company: compute infrastructure and people-oriented things," Zuckerberg ​said during the town hall, as heard by Reuters. With more capital flowing toward AI hardware, he said, there is less available for headcount. He also declined to rule out further reductions later in the year. Meta spent $72.2 billion on capex in all of 2025. The midpoint of its new 2026 guidance would nearly double that figure in a single year.

The timing undercuts any suggestion that Meta is cutting jobs out of financial necessity. The company's Q1 2026 earnings, reported on Wednesday, showed revenue of $56.31 billion, a 33% increase year over year, while net income hit $26.8 billion. Q1 capital expenditure alone reached $19.84 billion, and CFO Susan Li told investors she couldn’t predict the company's optimal long-term workforce size given how quickly AI capabilities are evolving.

Zuckerberg's comments land in the middle of a growing debate about whether companies are using AI as a convenient justification for workforce reductions they would make regardless. OpenAI CEO Sam Altman raised the issue in February, telling CNBC at the India AI Impact Summit that some firms engage in "AI washing" by attributing layoffs to the technology when the actual reasons lie elsewhere.

Zuckerberg's explanation is more specific than most, explicitly pointing to infrastructure spending rather than AI-driven productivity gains as the driver, but that specificity raises its own tension. Nvidia’s VP of applied deep learning, Bryan Catanzaro, said earlier this week that compute already costs more than the employees on his team, and a 2024 MIT study also found AI automation was economically viable in only 23% of vision-related roles. If AI infrastructure is currently more expensive than the labor it supplements, the return on trading one for the other remains a dubious strategy.

Some employees have understandably criticized Zuckerberg and other executives on Meta's internal message board over the layoffs and a separate initiative to monitor employee productivity through mouse and keyboard activity tracking. "Getting everyone internally to use AI tools and getting to do the work more efficiently is not the thing that's driving layoffs," but added that Meta will monitor “how all this stuff trends.”

These are the largest cuts at Meta since the 2022 and 2023 rounds that shed roughly 21,000 positions. Across the broader tech industry, more than 80,000 workers have been laid off in 2026 so far.

Google, Amazon, Microsoft, and Meta collectively plan to spend $725 billion on capex in 2026, up 77% from last year's record $410 billion, according to first-quarter earnings compiled by the Financial Times. Google delivered the strongest results, with cloud revenue jumping 63% year over year to $20 billion, while rising memory chip prices pushed spending forecasts higher at both Microsoft and Meta.

"The AI economy is healthy," Brent Thill, an analyst at Jefferies, told the Financial Times, adding that recent revenue growth justified the enormous capital outlays. "The bear thesis is garbage."

Microsoft set its calendar-year 2026 capex at $190 billion, well above the $152 billion average analyst estimate. The company’s CFO, Amy Hood, attributed $25 billion of that figure to rising memory chip and component costs. She told investors that despite the additional spending, Microsoft expects to remain capacity-constrained through at least 2026 as it works to bring GPU, CPU, and storage infrastructure online faster.

Meta increased its full-year projection by $10 billion to a range topping $145 billion. The company cited higher component pricing, particularly for memory, alongside growing competition for land, power, and skilled workers needed to build data centers. Revenue grew 33% to $56.3 billion.

Dec Mullarkey, managing director of SLC Management, told the Financial Times that investors are growing uneasy with Meta's escalating infrastructure costs, questioning whether a historically lean business is becoming far more capital-hungry. “Investors continue to be concerned about how Zuckerberg’s once capital-light money machine may be morphing into a capital-intensive incinerator,” he said.

Alphabet posted an 81% increase in net income to $62.6 billion on revenue of $110 billion. Google Cloud reached $20 billion in quarterly revenue, growing faster than Amazon Web Services ($37.6 billion total, adding $8.3 billion year over year) and Microsoft's Azure-driven cloud segment ($34.7 billion total, adding $7.9 billion).

The company's cloud contract backlog reached $460 billion, roughly double the $240 billion reported at the end of Q4 2025. Google Cloud boss Thomas Kurian credited the company's strategy of building custom AI chips, foundation models, and products in-house for giving it a cost and research advantage over competitors. Alphabet's capex guidance rose by $5 billion to as much as $190 billion, matching Microsoft. Shares climbed 7% after hours, putting Alphabet on track for a record $4.3 trillion market valuation.

CEO Mark Zuckerberg offered no firm schedule for releasing improved AI models to follow the recently launched Muse Spark. Asked about the pace of Meta's AI agent development, Zuckerberg told investors: "There's a lot of agents out there that people are building for different things, but there aren't that many that I would want to give to my mother."