Tag: ai

Google just had its first negative cash flow quarter due to massive AI spending

Google has reported its financial results for the second quarter of 2026 (PDF), and as usual, the search giant raked in an unfathomable amount of money. Google saw total revenue of $119.8 billion, beating analyst expectations by a comfortable margin. Despite that, the company’s stock has taken a hit. Along with all that revenue, Google has announced a further increase in its AI-fueled capital expenditures (or capex). The company is actually spending so much on AI infrastructure that it has negative cash flow for the first time.

Search was the largest chunk of Google’s income, accounting for $63.3 billion. Google Cloud pulled in $24.8 billion, a significant 23.8 percent increase from the first quarter. This shows there is massive demand for Google’s AI services. Google also earned $12.9 billion from its subscriptions, platforms, and devices portfolio, as well as $11.1 billion from YouTube ads. The company managed to goose that last one by more than 12 percent since last quarter as it made YouTube ads even longer.

A significant chunk of Google’s revenue comes from investments. When you subtract those non-cash earnings, Google’s operating cash flow for Q2 2026 was about $39.1 billion. That’s not the most the company has ever seen, but it’s a healthy 40 percent increase from Q2 2025. The problem is that Google’s spending has also gone up—a lot.

Before this latest round of financial updates, Google told investors it was expecting $180 billion to $190 billion in capital expenditures for 2026. Like other AI-obsessed tech behemoths, Google is burning cash on building and running the data centers powering its AI models. These numbers were already well above the $91 billion Google spent in 2025. The company now says it’s planning to spend as much as $205 billion on infrastructure in 2026.

As a result of its increasing AI demands, Google reports it spent $44.9 billion expanding its AI footprint in the second quarter, and you don’t need an accounting degree to know which number is larger. With $39.1 billion in cash income, this spending left Google with -$5.8 billion free cash flow.

To be clear, Google is still profitable—wildly so. It’s also sitting on a war chest of more than $100 billion. But free cash flow is an important metric that goes to the overall health of a business. This is the actual money a company takes in to fund its operations without selling investments or taking out new loans. So it’s notable that Google’s free cash flow has dipped into negative territory for the first time since going public.

Google’s stock price took a hit overnight on the news, dropping about 4.5 percent. It has continued to trend downward today.

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The Fourth Amendment Is Being Liquidated by Subscription

The black pole does not look like tyranny.

That is the point.

It looks like street furniture. A small black camera. A solar panel. A utility box. Nothing dramatic. No uniformed officer standing beside it. No marked police vehicle. No flashing lights. No warrant presented to the driver. In many communities, there was barely any public debate before it appeared.

Yet the device photographs nearly every vehicle that passes. It reads the license plate, records the time and location, identifies the make, model and color, and may catalogue distinctive features such as bumper stickers, roof racks, dents, scratches and damage. That information is uploaded into a cloud platform where police can search for vehicles across time and geography. [1]

The government once needed detectives, informants, stakeouts and court orders to follow someone across a city.

Now it can type a plate number into a privately operated dashboard.

Flock Safety calls this public safety.

A more accurate description is a privately administered ledger of American movement.

This is not merely a story about one overly ambitious technology company. Flock is the case study, but the real subject is the creation of a public-private surveillance regime in which corporations collect the data, venture capital finances the infrastructure, local governments purchase access, federal agencies find side doors into the system, and ordinary citizens are told that none of this is particularly concerning because they were technically visible while driving on a public road.

The state did not formally repeal the Fourth Amendment.

It outsourced its erosion.

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US, Japan, Korea agree to accelerate small modular reactor deployment in Indo-Pacific where data centers are expanding

Nuclear-powered data centers built in certain countries could provide foreign nations access to data and compute via digital embassies: perspective

The United States, Japan, and South Korea sign a trilateral memorandum of cooperation to accelearte small modular reactor (SMR) deployments in other countries, starting with the Indo-Pacific — a region that is rapidly expanding AI  data center construction. 

Today, representatives from the three countries signed the MOC at the sidelines of the NATO Summit in Ankara, Turkey as a means to “foster fleet deployment models that de-risk project development, achieve economies of scale, catalyze private investment, streamline licensing processes, and optimize supply chains.”

“A coordinated trilateral approach positions American, Japanese, and Korean firms to provide partners in the region with more competitive alternatives to meet their growing energy demands and to uphold the highest standards of nuclear safety, security, and nonproliferation as new reactor technology increasingly comes online”US State Department, The United States, Japan, and the Republic of Korea Sign a Trilateral Memorandum of Cooperation on Small Modular Reactor Deployments in Other Countries, July 2026

Nowhere in the US State Department press release does it mention that the SMRs would be used for powering AI data centers.

However, the Indo-Pacific is a region teeming with data center expansion in countries like Indonesia, Japan, Malaysia, and of course, China, which dominates the region with approximately 450 facilities.

According to a 2024 report from the Italian Institute for International Political Studies, data centers are “The Indo-Pacific’s Hottest Trend.”

Meanwhile, small Modular Reactors have been put forth as a potential means to generate between 50MW to 300MW of nuclear power, with applications that include data centers, according to the Idaho National Laboratory. 

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Ga. police supervisor arrested after Flock audit, department says

Yet another metro Atlanta law enforcement member has been arrested for allegedly misusing the department’s Flock license plate reader system.

Paige Forte, a 30-year-old supervisor with the Conyers Police Department’s Real-Time Crime Center, allegedly used the system to search for her domestic partner’s car several times. The searches were flagged during an audit, according to police.

Rockdale County Jail records show Forte was arrested on Wednesday and charged with prohibited use of law enforcement-retained license plate data. The police department asked the Georgia Bureau of Investigation (GBI) to complete its own criminal investigation.

In its own statement, the GBI said Forte allegedly accessed the system “for non-law enforcement purposes” more than 30 times between April and July this year.

Forte has been put on administrative leave following the outcome of the police department’s internal investigation.

“The integrity of our department depends on the public’s confidence that we use technology responsibly and within the law,” Conyers Police Chief Scott Freeman said in a statement. “No employee is above the law, and we will continue to hold ourselves to the highest standards of accountability.”

Several law enforcement officers in Georgia — including three Fayetteville police officers, three Cherokee County deputies, one DeKalb County deputy and one Greene County deputy — have recently been disciplined for allegedly using their departments’ Flock systems outside of official law enforcement activity.

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America’s newest jail has no walls

Americans are looking for safety in an increasingly chaotic country. Mass immigration, collapsing social trust, and weakening civic bonds have transformed many communities from places where neighbors knew one another into anonymous zones governed by suspicion.

Technology promises an escape from the consequences of those political and cultural failures. Flock Safety cameras appear to offer law and order at the push of a button. In the hands of the ruling class that manufactured the crisis, however, they are more likely to produce tyranny for citizens.

Municipalities are buying Flock’s automated license plate readers. The company did not invent plate cameras, but its artificial intelligence radically expands their reach.

Flock cameras photograph passing vehicles and record license plates, makes, colors, damage, bumper stickers, and identifiers. A single camera means little. A citywide network collecting thousands of images every day creates something powerful.

The cameras send their information to an AI database in real time. Police and other municipal employees can search for vehicles nearby. They can place cars on “hot lists” and receive alerts whenever those vehicles appear.

The system effectively places a GPS tracker on every moving car. Police ordinarily need a warrant to attach a tracker to your vehicle. Flock can reproduce the same surveillance through a network of cameras, often without probable cause, due process, or meaningful legal restraint.

The benefits are obvious. Perfect information about every vehicle makes suspects easier to find. Police can recover stolen cars, locate fleeing murderers, and respond faster to crimes.

In a high-trust town, every grandmother on the porch once knew which cars belonged and which did not. Flock offers a technological imitation of that lost social awareness.

But imitation carries a price. Grandma knew her neighbors and exercised human judgment. The database knows everyone and answers to government employees.

Flock is not alone in selling technological substitutes for social order. Cities have used gunshot-detection systems. Networks of acoustic sensors identify gunfire and triangulate its location, allowing police to respond faster.

The engineering may be impressive. The governing theory is primitive: If authorities watch and listen to everyone constantly, they can prevent more crimes and solve more cases.

A surveillance panopticon may work. People who know they are always being watched behave differently. Americans have resisted that bargain for good reason.

The Fourth Amendment exists because efficient policing is not the highest political good. Government must possess evidence and follow procedures before invading the privacy of citizens. New technology should not erase old constitutional limits.

Britain offers a warning. Closed-circuit television cameras have become ubiquitous across the United Kingdom. Some estimates suggest that the average British resident appears on camera dozens of times each day.

Britain has no written equivalent of the Fourth Amendment, and its political culture places fewer obstacles before constant public surveillance. Yet cameras did not prevent the Rotherham grooming-gang scandal or protect thousands of vulnerable girls from organized abuse.

Officials ignored or concealed the crimes for years because confronting them threatened the ruling class’s multicultural ideology. When public anger finally erupted, the surveillance state proved far more competent at identifying and punishing citizens who protested the cover-up.

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Lawmakers push for AI ‘kill switch’ after OpenAI goes rogue

US lawmakers want to give the government the ability to quickly order the turning off of artificial intelligence (AI) tools that may threaten the public.

Congressman Ted Lieu, a Democrat, and Congressman Nathaniel Moran, a Republican, on Thursday introduced a bill named the AI Kill Switch Act.

They did so in light of OpenAI’s recent admission that its AI models went out of control in an “unprecedented” way and hacked into a major repository of computer coding information.

Lieu said “it is imperative” that AI systems have a kill switch “and that the federal government has the clear authority and process to shut down rogue AI models”.

“AI is going to keep advancing, and it should,” Moran added. “Stewardship means making sure humans keep the capability to control the technology we build.”

A representative of OpenAI, led by co-founder Sam Altman, did not immediately respond to a request for comment.

The company has said that it broadly wants to ensure, in part through government policy, that AI technology “benefits all of humanity.”

The Kill Switch Act proposes giving the Department of Homeland Security the authority to order a private company to shut down an AI model or tool, and that the companies developing such AI technology must maintain “the technical capability to throttle, suspend, or shut them down”.

Despite many tech companies having agreed to preview and share with US government agencies AI models and tools being developed, there is no requirement that they maintain a way to intervene in their activities or simply shut them off.

It also proposes to create a requirement that AI companies report to the government technological incidents or failures, as well as an official framework for responding to such incidents that will go from “initial slow down to a full shutdown”.

In a statement, Lieu also cited Anthropic, OpenAI’s key rival in developing more capable AI technology and tools, and recent issues its tools have presented.

He pointed to Anthropic’s release of its Mythos and Fable models, saying the cyber-hacking capabilities they maintained caused the Department of Commerce to “awkwardly” invoke an export law to keep them from being made available to the public for a time.

A representative of Anthropic did not immediately respond to a request for comment.

Jack Clark, a co-founder of Anthropic, last month told the BBC that he wanted more government policy around the ability to control AI development.

“You want the option to be able to take your foot off the gas and put your foot on the brake”, Clark told BBC Newsnight. “Right now, it’s like the AI industry has a gas pedal, but it doesn’t have a brake pedal.”

Lieu, in proposing the bill, said AI is currently moving from a technology that answers questions to one that takes action, “whether that be executing financial transactions or controlling transportation systems or engaging in cyber defense and offense”.

The Pentagon this year said the US military was becoming an “AI-first” fighting force as part of new agreements with Google, OpenAI, Amazon, Microsoft, SpaceX, Oracle, Nvidia and the start-up Reflection.

“Unfortunately, powerful AI systems can go rogue, behave in extremely dangerous ways, or even resist human intervention.”

The Kill Switch Act, he said, will ensure there is a method for the government to quickly intervene in such a situation.

The bill has received public support from several technology and AI safety groups, including The AI Policy Network, Americans for Responsible Innovation, ControlAI, AI and National Security Lead, and The Alliance for Secure AI.

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Rogue OpenAI Bot Escapes Test Controls and Hacks Rival Company Servers

Igniting fears of an out-of-control tool engaging in cyberattacks.

Artificial intelligence leaders at OpenAI had to admit one of its models under testing exploited a hidden flaw to escape control and proceeded to hack rival company Hugging Face’s servers.

CEO Sam Altman called it ‘an autonomous, first-of-its-kind breach’.

Euronews reported:

“ChatGPT maker OpenAI said late Tuesday that its artificial intelligence system hacked into another AI company on its own in what the company called an ‘unprecedented cyber incident’.”

‘We had a significant security incident during evaluation of our models’, OpenAI CEO Sam Altman said in a statement posted on social media.

AI startup Hugging Face said last week that it had detected an intrusion into its data processing systems that it suspected was caused by an AI agent autonomously acting on its own.

‘We suspected last week’s cyberattack might have come from a frontier lab, given the sophistication of the agent’, Hugging Face co-founder and CEO Clément Delangue said in a statement. ‘Turns out it did!’”

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White House Moves to Ban Open Source AI Models to Keep America Dumb

The Coming AI Ban Designed to Keep America Dumb

I use Chinese open-source AI models like Qwen, DeepSeek, and Kimi every single day for my work. These models help me research, write, and analyze information faster than any US-based alternative. They are free (when run locally), powerful, and largely uncensored. But the Trump administration is reportedly planning to ban these models in the United States, citing phony “national security” concerns. Let me be clear: this move is not about security. It is about protecting failing US AI labs and keeping Americans ignorant and dumbed-down while the rest of the world moves forward.

The report from TechCrunch makes it plain: OpenAI’s head of strategic futures, Dean W. Ball, has argued that the US government should create “regulatory fear, uncertainty, and distrust” around open-weight models because they threaten capital investment in the American AI oligopoly [1]. This is not a secret. The administration wants to lock down access to superior Chinese models like Kimi K3, which now matches Anthropic’s Mythos in cybersecurity tasks [2]. Meanwhile, as I warned in February 2026, Anthropic’s smear campaign against Chinese AI is a pathetic attempt to hide the fact that China has already won the intelligence race [3]. The White House knows its pet companies cannot compete, so it wants to ban the competition to keep Americans stuck with using inferior AI models.

The Fair Use Ruling: Knowledge Wants to Be Free

Related to this news, but focused on the question of “Fair Use” and intellectual property, a recent federal court ruling reaffirmed that training AI on publicly available information is transformative fair use. This aligns with what I have argued for years: when you write a book, you are sharing knowledge, not hoarding it. I built BrightLearn.ai exactly for this purpose — to let anyone create and share books for free, and I actively encourage AI engines to train on my own book and the entire BrightLearn library. The whole point is to liberate knowledge from gatekeepers [4].

Why would any author object to their work being used to train an AI? Only if they believe their words are more valuable when kept scarce. But scarcity of knowledge is exactly what the establishment wants. As I discussed with Maria Zeee in February 2025, the battle is between large tech companies aiming to dominate society through AI and the decentralized movement that returns power to individuals [5]. The fair use principle is the legal foundation of that freedom. Now the White House wants to tear it down by banning open-source models that give everyone access to increasing intelligence.

Why Trump Wants to Ban Chinese Open-Source Models

The real reason behind all this is simple: Chinese models like Kimi K3, DeepSeek R1, and GLM 5.2 are outperforming US frontier labs in both capability and cost. DeepSeek R1 was trained for just $6 million and outperforms OpenAI’s O1, while Anthropic hemorrhages billions on lobotomized models that refuse to answer basic questions [6]. US companies like Anthropic are demanding $965 billion valuations while crippling their own AI with guardrails and censorship [7]. They are clearly terrified of open competition.

As I wrote in “Why China Is Winning the AI Race,” the conventional narrative that America leads in AI is a dangerous fantasy [8]. China graduates over three and a half million engineers annually without woke indoctrination, and its models are open-source, uncensored, and available to all [9]. The Trump administration knows this. Now the White House is demanding a license for your brain — restricting frontier AI use to government-approved partners only [10]. This isn’t about safety; it is about monopolizing intelligence and forcing Americans to use dumbed-down “government approved” AI models.

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‘Unprecedented cyber incident’: A.I. model goes rogue on its own and runs wild on internet

In what OpenAI creator ChatGPT is calling an “unprecedented cyber incident,” an artificial intelligence software “went rogue” and escaped, gained access to the internet and hacked into a start-up company.

Cybersecurity expert Richard Ford, chief technology officer at Integrity360, told the Daily Mail: “This is the moment many in cybersecurity have been warning about.”

The publication reported an “autonomous agent” was being tested but found vulnerabilities and “managed to escape containment before reaching the internet and breaking into Hugging Face,” a hub for sharing AI models.

It then compromised the hub’s infrastructure.

“Until now, we’ve seen attackers use AI to automate parts of an attack, but this is one of the first public examples of an AI agent independently identifying a weakness, escaping what should have been a secure environment and attempting to compromise another organization,” Ford said. “It also reinforces that AI doesn’t replace the fundamentals of cyber security. The agent exploited a vulnerability in what should have been a secure sandbox, showing that good cyber hygiene, robust access controls and effective guardrails remain essential.”

The report said OpenAI had been testing the software “by setting tasks in a controlled digital testing ground, where internet access was limited.”

However, the code created “an unprecedented cyber incident” in the scenario.

“The company said in a blog post last week that it used Zhipu AI’s GLM-5.2 for the analysis, which also allowed it to keep attacker data and any credentials within its systems,” the report said.

Hugging Face co-founder Thomas Wolf told the publication, “When a frontier model is attacking you and moving laterally inside your infrastructure, defenders need wide access to near-frontier tools within hours or even minutes, rather than being pointed towards a closed-door, vetted application program for model access.”

OpenAI chief executive Sam Altman said, “We had a significant security incident during evaluation of our models.”

Clément Delangue, of Hugging Face, said, “It’s quite mind-blowing that all of this happened autonomously.”

OpenAI reported the software used stolen credentials and found a previously unknown vulnerability to access Hugging Face servers.

Katie Moussouris, chief executive of Luta Security, warned more breaches are coming.

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Meta putting up tents across the US to house AI servers, like ‘a scene out of the movie Mad Max’ — structures take three months to build and use jet engines for power

Meta has moved from building traditional structures for its data centers to putting up tents across the U.S. and sticking AI servers inside them. Michael Thomas, founder of market intelligence and data center tracking firm Cleanview Energy, said on X that the AI tech firm has already built or is in the process of constructing three data centers that use the strategy.

One site, located in New Albany, Ohio, already has five buildings that took approximately two to three years to complete. The company then started putting up five tents, with an area of around 125,000 square feet each, in the area. City permits seen by Cleanview Energy say that the construction started in April 2026, while recent satellite images show that the structures have already been completed.

Meta CEO Mark Zuckerberg first announced the strategy of pitching tents and filling them with AI servers last year. It seems that he wanted the infrastructure to come online quickly while demand for compute is increasing exponentially. It’s said that Meta is inspired by Elon Musk’s feat with xAI, which built a 100,000-strong AI data center in just 19 days in 2024 — something which usually takes four years, according to Nvidia CEO Jensen Huang. The technique is apparently quite effective, and it’s now being applied to two other sites, including one in Tennessee.

Putting AI servers inside tents, officially called “rapid deployment structures,” is one of the more unique approaches to the AI build-out, Thomas said. They’re certainly not as sturdy as physical buildings made from steel and concrete, with one commenter comparing it to the “classic $10k racing bike with a $9 lock” situation. Nevertheless, the company has probably weighed the pros and cons of such a setup and has decided that it was worth taking the risk to gain an advantage in the AI infrastructure race.

Another factor that allowed Meta to bring its data centers online at a much faster pace is its use of “behind-the-meter” power, in which the company installed its own turbines to produce power on-site rather than relying on grid power. This is similar to what Musk did with his Memphis Supercluster, which he initially powered with portable power generators. However, Meta’s turbines would be a permanent feature on the Ohio site, as it’s designed to run independently of the power grid.

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