The Federal Trade Commission has a two-word name for how the AI industry funds itself: circular spending. It sits in a staff report the agency published in January 2025, describing the deals between the largest cloud companies and the largest AI labs. Not a critic’s phrase. Not a short seller’s. The government’s own words, in a federal document, for the way the money moves.

Here is the arrangement that phrase describes. A cloud company invests billions of dollars in an AI lab. The lab then agrees to spend a large share of that same money buying computing power from the company that just funded it. The money leaves and comes home. The FTC found that these partnerships “include cloud commitments that require AI developers to spend a large portion of their CSP partner’s investment on cloud services from their partner,” and it named that feature, in plain type, circular spending.

That finding has been public for more than a year. So has a second fact, from a different stack of documents: the same small group of companies now floods Washington with more lobbyists than almost any other industry. What nobody has done is lay the two records side by side. Do that, and a single machine comes into focus. A money loop that funds its own demand, and a legal wall going up to keep anyone from regulating it. Same companies. Both halves. It is the first thing to understand about the AI economy, and it is hiding in plain public records.

The loop

The loop runs through three partnerships, and the FTC studied all three. The agency’s 6(b) study examined Microsoft and OpenAI, Amazon and Anthropic, and Google and Anthropic, the largest such deals in the industry. As the report tabulated the publicly reported figures through September 2024, Microsoft had put 13.75 billion dollars into OpenAI, Amazon 8 billion into Anthropic, and Google 2.55 billion into Anthropic. Microsoft’s own quarterly filing that fall put its total funding commitments to OpenAI at 13 billion, accounted for under the equity method.

These are not ordinary stock purchases. The FTC found the deals hand the cloud partners “significant equity and certain revenue-sharing rights,” and leave the door open for one company to fully acquire its partner down the line. They carry “consultation, control, and exclusivity rights,” including board seats and preferential treatment. The company writing the check also gets a hand on the wheel.

Then the money comes back as cloud spending. That is the circular part, and the FTC was direct about why it matters. The structure, in the agency’s reading, is one avenue through which a cloud provider may aim to reduce the size of the loss it might otherwise take on the billions it pours into a partner. The lab gets discounted computing it could not afford on the open market. The cloud gets its money returned as revenue, plus equity, plus a view inside a rival’s operation. The report found the arrangement reaches all the way down to the silicon, with “co-development plans for CSP-designed semiconductor chips” tuned to the labs’ models. Money, equity, control, and custom hardware, all moving in a ring.

The entanglement runs deeper than money. The FTC found the partnerships give the labs discounted access to the scarce computing they cannot get elsewhere, let the two sides embed their own engineers inside each other’s companies, and share training data along with detailed performance and financial figures on the models themselves. The people, the data, and the hardware are braided together as tightly as the cash. Unwinding one company from the arrangement would mean pulling all of it apart at once.

The agency also listed risks it thought were worth watching. In Section 5 of the report, staff flagged that these partnerships could limit other AI developers’ access to computing power and engineering talent, the two scarcest inputs in the field. They flagged that the deals could raise the cost of switching providers, through exclusivity terms and technical lock-in that make leaving expensive and slow. And they flagged that the arrangements hand the cloud partners access to sensitive financial and technical information, including confidential chip designs and a partner’s own customer and revenue numbers, which those same cloud companies could use to build products that compete with the labs they fund.

That section is contested, and the objection came from inside the agency. Commissioner Andrew Ferguson, joined by Commissioner Melissa Holyoak, filed a concurring and dissenting statement on January 17, 2025. Three days later Ferguson became Chairman of the FTC, the job he still holds. He voted to approve the report and said why: it “sheds light on three Big Tech-AI partnerships,” and “Congress, state officials, and the public deserve to understand how these partnerships work.” What he objected to was Section 5. The study was fast and narrow, he wrote, covering three partnerships between five companies, and “the limited, brief nature of the study should foreclose the drawing of broad conclusions about the AI industry and its future, or even about the partnerships themselves.” His instruction to readers was blunt: “Readers should skip Section 5 of the Report, or read it with tremendous skepticism.”

Fine. Skip it.

Nothing else in this piece needs it. The money loop, the equity and revenue-sharing rights, the board seats, the chip co-development, the embedded engineers, the shared training data and financial figures, all of that sits in the parts of the report Ferguson voted to publish and called valuable, drawn from what he described as “company documents produced in response to the Commission’s Section 6(b) orders.” The speculation about what it might mean is the part he wanted struck. What these companies actually signed is not in dispute.

It is worth noting what Ferguson did not say. He did not say the arrangement is harmless. His own statement holds that the Commission “must remain a vigilant competition watchman, ensuring that Big Tech incumbents do not control AI innovators in order to blunt any potential competitive threats.” His argument is that a study run in under a year should not be the last word. That is a reasonable thing for a regulator to say, and it cuts both ways. If a year was not enough to draw conclusions, it was not enough to rule anything out either.

The report’s own limits are real and worth stating plainly. It covers three partnerships. It reflects what the companies disclosed as of September 2024. It was aggregated to protect trade secrets. It says outright that it is “not a formal legal or economic analysis” and accuses no one of breaking the law. Circular spending is not a crime. The concern here is not illegality. It is that this structure concentrates enormous power in very few hands, and that the ordinary means of checking that power are being closed off one at a time.

What happened next

The FTC published those numbers in January 2025. Every one of the three partnerships has been rewritten since, and the public record of what replaced them is the strongest evidence in this piece.

Start with Amazon and Anthropic, because the arithmetic is right there in the announcement. On April 20, 2026, the two companies said Amazon “is investing $5 billion in Anthropic today, with up to an additional $20 billion in the future,” securing “up to 5 gigawatts (GW) of capacity for training and deploying Claude.” In the same announcement, Anthropic said: “We are committing more than $100 billion over the next ten years to AWS technologies.” That covers Amazon’s own Trainium chips, Trainium2 through Trainium4, plus Graviton processors and the option to buy future generations of Amazon silicon.

Read those two sentences together. Amazon puts in up to 25 billion dollars. Anthropic commits to spend more than 100 billion dollars back with Amazon. The purchase commitment running the other way is roughly four times the size of the investment. That is the arrangement the FTC described in January 2025, at ten times the scale, announced in public by the companies themselves. It is also a large share of the 2026 capex wave now reshaping the American power grid.

Google and Anthropic expanded too. On April 6, 2026, Anthropic announced a deal with Google and Broadcom for “multiple gigawatts of next-generation TPU capacity that we expect to come online starting in 2027,” Google-built chips supplied through Broadcom, with the vast majority of the capacity sited in the United States. Anthropic did not disclose the dollar terms. It did say its run-rate revenue had “surpassed $30 billion,” up from roughly $9 billion at the end of 2025, and pointed back to an earlier pledge to “invest $50 billion in strengthening American computing infrastructure.”

Microsoft and OpenAI went the other direction on some terms. On April 27, 2026, Microsoft announced an amended agreement. Its license to OpenAI’s models and products runs through 2032 but is “now non-exclusive.” OpenAI “can now serve all its products to customers across any cloud provider.” Microsoft “will no longer pay a revenue share to OpenAI.” Those are real changes, and they loosen exactly the kind of exclusivity the FTC described.

The same announcement says what did not change. Microsoft “remains OpenAI’s primary cloud partner,” and OpenAI’s products still ship first on Azure “unless Microsoft cannot and chooses not to support the necessary capabilities.” Microsoft “continues to participate directly in OpenAI’s growth as a major shareholder.” And revenue share payments from OpenAI to Microsoft “continue through 2030, independent of OpenAI’s technology progress, at the same percentage but subject to a total cap.”

So here is the honest accounting. One leg of the arrangement got looser. The other two got dramatically larger. Ferguson was right that a one-year study could not tell you where this was going. Sixteen months of company announcements can. The money still leaves and comes home, and the sums involved have gone from billions to hundreds of billions.

The shield

The companies inside the money loop are also among the largest lobbying forces in Washington. Public Citizen, a nonprofit watchdog, found that more than 3,500 lobbyists worked on AI issues in 2025, more than one in four of every registered federal lobbyist in the country. The overwhelming majority of that work, 82 percent of it, was done on behalf of corporate interests. The AI lobbying force grew 168 percent between 2022 and 2025. Sludge, working the same disclosure filings, put the precise count at 3,570 lobbyists, or 26 percent of everyone registered.

The growth is steeper than even that suggests. Public Citizen found the number of distinct lobbyist-and-client relationships working AI jumped 265 percent over those three years, from 1,672 to 6,110. Software and services became the single largest lobbying sector in the country by that measure, with about 1,448 lobbyists, close to 30 percent of the entire AI lobbying push. Lobbyists working specifically on data centers grew from 68 in 2022 to more than 400 in 2025, close to six times as many. An industry that barely registered on K Street four years ago now sits near the center of it. I have written before about the money behind AI policy and about the policy revolving door that moves people between the agencies and the firms they regulate.

Look at who is doing the spending. Public Citizen’s count of the top AI-lobbying operations in 2025 lists the US Chamber of Commerce with 91 lobbyists, Microsoft with 63, Meta with 55, Intuit with 51, and Amazon with 48. The names at the top of that list are the same names inside the money loop.

And the policy showing up is built to remove the biggest threat to the loop. On December 11, 2025, the White House issued an executive order titled “Ensuring a National Policy Framework for Artificial Intelligence.” It orders the Attorney General to stand up an AI Litigation Task Force whose only assignment is to challenge state AI laws in court. It directs the Commerce Department to identify state AI laws it considers onerous and hand them to that task force. It moves to cut states that keep the targeted regulations off the non-deployment portion of federal BEAD broadband funding, the money for planning, administration, and outreach, unless they fall in line. And it reaches further still, directing the FCC to weigh a federal reporting standard that would override conflicting state rules, and the FTC to spell out when a state law that forces changes to an AI model’s output is preempted by federal law. States have been the one level of government actually writing rules for this industry, and the fight over state AI laws had been running in 45 of them. The order is designed, layer by layer, to preempt them. It is the enforcement arm of the White House framework released earlier that year.

No one can prove the lobbyists wrote that order, and I am not going to claim they did. But the shape is hard to miss, and it is not the first time the question has come up about Big Tech’s hand in an executive order. The firms that dominate the money loop are among the heaviest spenders shaping AI policy, and the policy that arrived, federal preemption of state law, happens to sweep away the one venue that had started to regulate them. Public Citizen’s J.B. Branch put the stakes plainly: “Congress now has a once-in-a-generation opportunity to decide whether AI becomes another chapter in the story of unchecked corporate power.”

I asked Public Citizen how the two halves fit together. Eileen O’Grady, a researcher there and co-author of Generative Influence, told Laterstack:

“Last year’s AI lobbying surge and the preemption push are two parts of the same play. Big Tech spent heavily to shape federal policy and is effectively cashing in through the government’s attempt to wipe out state laws that would have created common sense guardrails for the industry. We can expect to see federal AI lobbying continue to intensify as preemption plays out in Congress and the courts, especially if bills like the draft Great American AI Act advance. We might also see more pressure directed at the executive branch, which has become the industry’s most effective route now that the direct legislative attempts have stalled.”

The bill she names is real and not yet law. Representatives Jay Obernolte, a Republican from California, and Lori Trahan, a Democrat from Massachusetts, released the Great American AI Act as a discussion draft on June 4, 2026. It has not been formally introduced. It carries a three-year preemption of state laws governing how AI models are built, while leaving states their authority over how those systems get used.

Her last point is the one to sit with. She reads the executive branch as the industry’s most effective route now that the direct legislative push has stalled. The December order came from the executive branch.

The same hands

Set the two records next to each other and the machine is whole. Microsoft and Amazon are principals in the arrangement the FTC called circular spending. Microsoft and Amazon also sit second and fifth on the list of the country’s biggest AI lobbying operations. The hands that built the loop are the same hands building the wall. This is not two stories about the AI industry. It is one story about a small number of companies that fund themselves in a circle and are working, out in the open, to keep anyone from stepping in.

None of the individual facts here are secret. The FTC report is on the agency’s website. Public Citizen published its lobbying count. The executive order is posted on the White House site. The partnership terms are on the companies’ own newsrooms. The pieces have been sitting in the open, in separate places, waiting for someone to set them on the same table. Standard Oil looked permanent too, right up until someone wrote the whole thing down in one place.

A quick word on why I am writing this. I am not trying to tell you what to think. I want to lay out what the public documents actually say and let you weigh it for yourself. How these companies are funded, and who gets to set the rules for them, touches things people feel directly, like prices, competition, and how much real choice they have. You can follow all of that without taking a political side, and it is already on the record.

No brakes

Two forces usually correct a concentration of corporate power, the market and the government, and in the AI economy both are being closed at once. The market is the first. Competitors move in, customers leave, the advantage erodes on its own. But a loop that funds its own demand does not wait on the market’s permission to keep running. Government is the second. Regulators and legislators draw the lines. But you cannot regulate a machine whose owners are writing the rules, and the December order is aimed squarely at the level of government that was trying.

The bill for all of it lands somewhere. Five gigawatts here, multiple gigawatts there, and the power and water to run them come from somewhere real. In Arizona that has already turned into the data center bill you never voted on, paid through electricity rates by people who were never asked.

That is the machine, at least the part you can already prove from public documents. It is also only two layers of it. The full stack runs from the chips and the packaging bottleneck that decides how many of them get built, up through the clouds and the labs, to the money loop and the law wrapped around it. The rest of this series follows it the whole way down.

Laterstack contacted Microsoft, Amazon, Google, OpenAI, and Anthropic for this piece. None provided an on-the-record comment.

Where every number came from

Every figure and quote in this piece comes from a public document. Here is where each one lives, in the order the claims appear.

The loop

1. The phrase “circular spending,” the cloud commitment finding, the equity and revenue-sharing rights, the board seats and exclusivity terms, the chip co-development, the discounted compute, the embedded engineers, the shared training and performance data, the Table 1 investment figures, and the report’s own scope limits: FTC Staff Report on AI Partnerships and Investments 6(b) Study, Federal Trade Commission, January 2025. The circular spending language appears in Finding 3 on page 19.

2. Microsoft’s own accounting of its OpenAI position, stated as “total funding commitments of $13 billion” under the equity method: Microsoft Form 10-Q for the quarter ended September 30, 2024, U.S. Securities and Exchange Commission. Note that this figure and the 13.75 billion in FTC Table 1 are not identical. The FTC tabulated publicly reported investment; Microsoft reported its own booked funding commitments. Both are cited here as each states them.

3. Amazon’s investment in Anthropic and the Trainium chip arrangement: Amazon to invest additional $4 billion in Anthropic, Amazon.

4. The dissent from Section 5, the instruction to read it with skepticism, the vote to approve the rest of the report, and the “vigilant competition watchman” line: Concurring and Dissenting Statement of Commissioner Andrew N. Ferguson, joined by Commissioner Melissa Holyoak, Matter No. P246201, January 17, 2025.

What happened next

5. Amazon’s $5 billion investment, the up to $20 billion that follows, the 5 gigawatts of capacity, and Anthropic’s commitment of more than $100 billion to AWS over ten years: Anthropic and Amazon expand collaboration for up to 5 gigawatts of new compute, Anthropic, April 20, 2026.

6. The multiple gigawatts of next-generation TPU capacity from 2027, the Broadcom supply arrangement, the U.S. siting, the $30 billion run-rate revenue figure, and the $50 billion American infrastructure pledge: Anthropic expands partnership with Google and Broadcom for multiple gigawatts of next-generation compute, Anthropic, April 6, 2026. Confirmed by Google Cloud, which discloses no financial terms.

7. The non-exclusive license through 2032, the any-cloud provision, the end of Microsoft’s revenue share payments to OpenAI, the primary cloud partner and major shareholder language, and the revenue share running to Microsoft through 2030 subject to a cap: The next phase of the Microsoft-OpenAI partnership, Microsoft, April 27, 2026.

The shield

8. The AI lobbyist count, the corporate share, the growth figures from 2022 to 2025, the data center lobbyist growth, the lobbyist-and-client relationship growth, the software and services sector share, the top lobbying operations by headcount, and the J.B. Branch quote: Generative Influence, by Mike Tanglis and Eileen O’Grady, Public Citizen, February 24, 2026.

9. The 3,570 lobbyist count, the 26 percent share of all registered federal lobbyists, and corroboration of the top lobbying employers: AI Boom on K Street: One in Four Lobbyists Now Work on AI, by David Moore, Sludge, February 24, 2026.

10. Federal lobbying spending by the AI developers themselves, $3.13 million by Anthropic and $2.99 million by OpenAI in 2025: AI’s Biggest Builders Are Now Its Biggest Lobbyists, by Phoebe Liu, Forbes, February 20, 2026.

11. The AI Litigation Task Force, the Commerce Department review of state AI laws, the BEAD funding condition, the FCC reporting standard, and the FTC preemption guidance: Executive Order 14365, Ensuring a National Policy Framework for Artificial Intelligence, The White House, December 11, 2025. Legal analysis of the same order, including the point that the funding at risk is the non-deployment portion of BEAD: AI Executive Order Targets State Laws and Seeks Uniform Federal Standards, Latham and Watkins, December 17, 2025.

12. The three-year preemption of state laws governing model development, and the bill’s status as a discussion draft: Obernolte, Trahan release a discussion draft of the Great American AI Act, June 4, 2026.

13. Eileen O’Grady’s comment was provided to Laterstack by email on July 22, 2026, and her attribution was confirmed by her on July 23, 2026.

Frequently Asked Questions

What is circular spending in AI?

Circular spending is the FTC’s term, from its January 2025 staff report, for cloud commitments that require AI developers to spend a large portion of their cloud partner’s investment back on that partner’s cloud services. The money is invested, then returns as revenue.

Which companies did the FTC 6(b) study cover?

Three partnerships between five companies: Microsoft and OpenAI, Amazon and Anthropic, and Google and Anthropic. The report reflects what those companies disclosed as of September 2024.

Did anyone at the FTC disagree with the report?

Yes. Commissioner Andrew Ferguson, joined by Commissioner Melissa Holyoak, voted to approve publication but dissented from Section 5, the Areas to Watch section. Ferguson wrote that readers should skip Section 5 or read it with tremendous skepticism. He became FTC Chairman three days later.

How much are these partnerships worth now?

In April 2026 Amazon announced a 5 billion dollar investment in Anthropic with up to 20 billion more, and Anthropic committed more than 100 billion dollars over ten years to AWS technologies. Anthropic separately signed with Google and Broadcom for multiple gigawatts of TPU capacity starting in 2027. Microsoft and OpenAI amended their agreement to make Microsoft’s license non-exclusive.

What does the December 2025 executive order do?

Executive Order 14365 directs the Attorney General to create an AI Litigation Task Force to challenge state AI laws, has Commerce identify state laws it considers onerous, conditions the non-deployment portion of BEAD broadband funding, and directs the FCC and FTC toward federal standards that would preempt conflicting state rules.

How many lobbyists work on AI?

Public Citizen found more than 3,500 lobbyists worked AI issues in 2025, more than one in four of every registered federal lobbyist. Sludge put the count at 3,570, or 26 percent. Public Citizen found 82 percent of that work was on behalf of corporate interests.

A former Google employee has filed a confidential SEC whistleblower complaint alleging the company helped an Israeli military contractor apply Gemini AI to drone surveillance video. The complaint, first reported by The Washington Post on February 1, claims Google breached its own ethics policies in the process.

The core allegation is straightforward. Google provided AI tools to an Israeli contractor who used them to analyze drone footage – the kind of application Google once publicly promised it would never support.

The Ethics Policy That Disappeared

In February 2025, Google quietly revised its public AI Principles, stripping out language that committed the company to avoiding AI technologies applied to weapons or surveillance violating “internationally accepted norms.” The updated version replaced those commitments with vaguer language about pursuing AI “responsibly” and in line with “widely accepted principles of international law.”

The timing was not subtle. The revision came weeks after Alphabet CEO Sundar Pichai attended President Donald Trump’s January 20, 2025 inauguration alongside Jeff Bezos and Mark Zuckerberg. Hours after taking office, Trump rescinded a Biden-era executive order that established guardrails for AI development.

Google was not alone. Throughout 2024, OpenAI, Anthropic, and Meta had already walked back their own AI usage policies to allow U.S. intelligence and defense agencies access to their systems.

Project Nimbus and the Broader Pattern

This whistleblower complaint lands on top of years of internal conflict over Project Nimbus, a $1.2 billion cloud computing contract with the Israeli government signed jointly by Google and Amazon. In April 2024, Google fired 28 employees who staged sit-in protests against the contract at offices in New York, Sunnyvale, and Seattle.

At least nine employees were arrested. No Tech for Apartheid, the activist group behind the protests, alleged the Israeli military was using Google Photos as part of its facial recognition efforts in Gaza.

The pattern is clear. Write ethics policies when public pressure demands them. Rewrite those policies when government contracts require it. Fire anyone who objects.

Commercial large language models are now reportedly used by the Israeli military for translating intercepted Palestinian communications, automatically adding individuals to target lists based on keywords. The line between “cloud services” and “military AI” has been functionally erased.

Laterstack exists to sharpen critical thinking by connecting tech, policy, and power to everyday life – across class, industry, and influence. Google did not accidentally end up powering drone surveillance. It removed the ethics language that would have prevented it, fired the employees who protested, then quietly rewrote the rules. The timeline is a sequence of deliberate decisions by executives who understood exactly what they were enabling. Lawmakers drafting AI governance frameworks, Pentagon officials evaluating tech partnerships, and the billionaires on Google’s board need to answer a direct question: when a company rewrites its ethics policy to match its contracts rather than the other way around, what is the policy actually for?

What This Means for Everyday People

Corporate AI ethics policies are marketing documents. They exist until they conflict with revenue. Every major AI company has now revised or abandoned its restrictions on military and surveillance use. The shift is not unique to Google – it is an industry-wide pivot toward defense revenue as the commercial AI market matures.

The whistleblower route through the SEC signals that internal dissent has been effectively crushed. When employees cannot protest internally without being fired, federal complaints become the last recourse.

Professor Elke Schwarz of Queen Mary University London put it bluntly: the “shifting mood among big tech firms towards military AI” is no longer a trend. It is the baseline.

What does the Google whistleblower SEC complaint allege?
A former Google employee filed a confidential complaint with the SEC alleging Google helped an Israeli military contractor use Gemini AI to analyze drone surveillance footage, breaching the company’s own ethics policies.

Did Google remove its AI ethics rules on weapons and surveillance?
Yes. In February 2025, Google removed language from its AI Principles that pledged not to develop AI for weapons or surveillance violating internationally accepted norms. The revised policy uses vaguer language about operating “responsibly.”

What is Project Nimbus?
Project Nimbus is a $1.2 billion cloud computing contract between Google, Amazon, and the Israeli government. Google fired 28 employees in April 2024 who protested the contract.

Google has filed a lawsuit against SerpApi, a company offering tools to scrape web content, including Google search results. The complaint alleges that SerpApi used automated methods to bypass protections, access copyrighted data at scale, and sell it to customers. Google says these actions violate federal copyright law and threaten the integrity of its search ecosystem.

This legal conflict is part of a wider pattern. Reddit also sued SerpApi and other data scrapers for taking content from its platform to feed AI tools. While Google’s complaint references Reddit’s case, it does not name any AI companies using the scraped data.

At the center of the dispute is SearchGuard, a technology Google introduced earlier in 2025 to block automated scraping. Google claims SerpApi quickly discovered ways to bypass the system, sending hundreds of millions of queries daily while masking them to appear as human-generated. Each circumvention, Google argues, constitutes a violation of federal law.

SearchGuard was designed to protect Google’s search results and the copyrighted content of its partners. After the tool went live in January 2025, Google alleges SerpApi immediately worked to evade it, continuing large-scale data extraction. Google frames this as a major breach of both technical safeguards and intellectual property rights.

The case highlights broader questions about the evolving digital economy. Tools for scraping, AI data collection, and automated analysis are increasingly central to technology, but they also raise legal and ethical concerns. The tension between innovation and copyright protection is becoming a defining issue for the tech industry.

For everyday users, the story shows that the technology we rely on is underpinned by complex legal and technical frameworks. What seems like a simple search or AI query involves layers of agreements, protections, and limitations that most people never see. Recognizing these layers can change how we understand digital services and the unseen mechanics behind them.

If you have tips, insights, or want to contact Laterstack, email us at hello@laterstack.com

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Google and Apple have reportedly warned some employees to avoid leaving the United States if they need a visa stamp to return, citing growing delays and unpredictable processing times at U.S. embassies.

According to Business Insider, law firms representing both companies issued internal guidance advising caution. BAL Immigration Law, which works with Google, and Fragomen, which represents Apple, warned that employees without valid H-1B visa stamps could face extended delays if they travel abroad.

One memo reviewed by Business Insider stated that recent changes have created a risk of lengthy and uncertain wait times for re entry into the United States. Employees were strongly advised to postpone international travel unless absolutely necessary.

A spokesperson for the U.S. State Department told Business Insider that embassies are now prioritizing more extensive vetting of visa applications, even if that results in slower processing.

The issue appears to be affecting workers well beyond major tech firms. Salon reported that hundreds of Indian professionals who traveled home in December to renew U.S. work visas have seen embassy appointments canceled or pushed back. Those disruptions are reportedly tied to expanded requirements for social media screening and background checks.

Google and Apple have not yet publicly commented, but this is not the first time large tech employers have raised alarms. In September, both companies issued similar warnings after the White House announced that employers would be required to pay a $100,000 fee for H-1B visa applications.

The travel guidance underscores growing anxiety across the tech industry as immigration rules tighten and processing times become less predictable. For foreign workers, especially those in high demand engineering and AI roles, a routine trip home now carries the risk of being stranded outside the country for weeks or even months.


What This Means for Everyday People

For tech workers on visas, the warning highlights how fragile international mobility has become. A single delayed appointment can interrupt careers, separate families, and disrupt entire teams. More broadly, the situation shows how immigration policy changes ripple through the economy, affecting startups, innovation pipelines, and hiring at the largest tech companies alike.


For inquiries or tips
hello@laterstack.com

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This week, both Apple and Google released urgent security updates after discovering active zero-day vulnerabilities that targeted an unknown number of users. The incidents highlight how even the largest tech companies remain vulnerable to sophisticated attacks, often originating from government-backed actors.

On Wednesday, Google patched several security flaws in its Chrome browser. One of the vulnerabilities was actively exploited before the company could release a fix, a scenario that is increasingly common in high-profile hacking campaigns. Initially, Google provided limited details, but later updates confirmed the discovery came from Apple’s security engineering team and Google’s Threat Analysis Group. These teams focus on tracking government hackers and mercenary spyware operators, suggesting that this campaign may have been coordinated at the state level.

Apple simultaneously issued updates for its iPhones, iPads, Macs, Apple Watches, Apple TV, Vision Pro, and Safari browser. According to Apple’s advisory, two zero-day flaws were patched on iOS devices. The company acknowledged that these vulnerabilities had likely been used in “extremely sophisticated attacks against specific targeted individuals” before iOS 26 was released.

Zero-day vulnerabilities are particularly dangerous because they are unknown to the software makers at the time of exploitation. Historically, such flaws have been used by government actors and companies like NSO Group and Paragon Solutions to deploy spyware against journalists, activists, and dissidents. These attacks often go unnoticed until security researchers or the companies themselves discover them.

The public disclosure raises broader questions about digital safety, personal data protection, and the role of private companies in defending users against state-level hacking. While patches prevent future exploitation, the affected users may have already been compromised, emphasizing the importance of layered cybersecurity practices such as frequent updates, strong passwords, and multifactor authentication.

Apple and Google have not commented beyond their advisories, leaving the scale of the attacks and the number of affected users unclear. For consumers, the incident serves as a reminder that vigilance is critical even with devices from some of the most secure technology providers in the world.

Protective Measures for Users:

Update devices and applications immediately after security patches are released

Enable multifactor authentication wherever possible

Monitor accounts for suspicious activity and unusual logins

Use strong, unique passwords and consider password managers for security

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Quantum technology has always been hard to explain. It deals with particles so small and strange that even experts struggle to describe what is happening. Yet behind the complexity lies a truth that is starting to surface. Quantum might soon become as transformative as artificial intelligence and possibly even bigger.

The field that once lived only in theory is now moving into hardware. Companies like Microsoft, Google, and Quantinuum are racing to build quantum computers, sensors, and communication systems. Microsoft’s latest Majorana chip is one example, designed to make quantum systems more stable and less error-prone.

For years, AI dominated the headlines. It was easy to understand, easy to use, and quick to deploy. Quantum, on the other hand, required labs, lasers, and near absolute-zero temperatures. But things are changing fast.

Researchers are finding ways to build qubits, the core building blocks of quantum computers with synthetic diamonds, allowing them to work at higher temperatures and with greater efficiency. Companies like Element Six, a subsidiary of De Beers, are now creating industrial-grade quantum diamonds in partnership with Amazon Web Services, paving the way for more accessible hardware.

The potential scale is enormous. Analysts at McKinsey project the quantum sector could reach 97 billion dollars by 2035. That is still smaller than AI’s trillion-dollar forecast, but the real measure is not in money, it is in impact.

Professor Sir Peter Knight of Imperial College London describes it simply: “Problems that would take the age of the universe to solve could one day be computed in seconds.”

That kind of power could change everything from drug discovery to energy systems. In healthcare, quantum computers could map endless combinations of molecules to design precise, personalized medicines. Google’s new Willow chip already demonstrated how a quantum processor could solve a problem in five minutes that would take the world’s fastest supercomputer ten septillion years.

The same capability could transform global industries. Airbus is testing quantum algorithms to load cargo more efficiently, saving thousands of kilos of fuel. The UK National Grid is investing in quantum models to optimize how power flows across thousands of generators. Even navigation could change, researchers at Imperial College London recently tested a quantum compass that works underground where GPS fails.

These breakthroughs are not limited to science. They also touch national security. Experts warn that quantum systems will eventually break today’s encryption standards, unlocking everything from government secrets to personal data. This looming moment is known as Q-day, when a fully operational quantum computer becomes powerful enough to decrypt traditional systems.

Governments and tech firms are already preparing. Apple and Signal have rolled out post-quantum encryption keys designed to withstand these future attacks. But older encrypted data remains vulnerable. Intelligence agencies are already harvesting and storing data they cannot yet read, waiting for the day quantum decryption becomes possible.

Professor Alan Woodward of the University of Surrey calls it “harvest now, decrypt later.” Once Q-day arrives, everything encrypted by older systems could become transparent overnight.

Still, many experts believe quantum’s benefits will outweigh its risks. Quantum sensors already enable more precise brain scans, helping doctors study movement disorders and childhood epilepsy without keeping patients still. In transportation, quantum navigation could keep airplanes and subways connected even when satellite signals drop.

As Rajeeb Hazra, CEO of Quantinuum, told the BBC, “We as consumers will touch the impacts of quantum computing in almost every walk of our lives. It could be as big as AI — if not bigger.”

The question is no longer whether quantum works. It is how soon we will be ready for it. The technology that once lived in cold labs is warming up fast. And when it arrives, the world may have to rethink not only how we compute, but how we secure, measure, and even understand information itself.

Read the original report by Zoe Kleinman at BBC.

For more Laterstack analysis, explore Quantinuum Helios quantum computer could bring quantum breakthroughs closer to real life and NVIDIA just built the bridge between quantum and classical computing.