Anthropic Moves IPO Target Date To After The Mid-Term Elections

From the Wall Street Journal, September 18:

Anthropic Shifts Planned IPO to November
Investors had expected the Claude maker to debut in October; the AI industry has been grappling with calls to slow its pace of development 

Anthropic plans to stage its blockbuster initial public offering in November, later than many investors expected, as leaders of the biggest companies in the artificial-intelligence race call for a slowdown in the development of the technology. 

The AI giant had been expected to stage a record-breaking offering in October, according to people familiar with the matter. Some of Anthropic’s advisers say waiting until November would give the startup time to share third-quarter financials that show a strong competitive position, even after rival OpenAI launched its newest model, Astra, in September.

Some of the people familiar with the timing say the decision to aim for a November offering was made before a public warning from a former Anthropic researcher set off a debate about whether AI advancements are moving too fast. They caution the timing could still change.

Anthropic Chief Executive Dario Amodei was the first of the three major AI executives to call for a slowdown, penning a blog post Saturday that said the risks posed by today’s cutting-edge tools were too great to continue development at the same breakneck pace. Leaders of rival AI labs including OpenAI CEO Sam Altman and SpaceX’s Elon Musk echoed the sentiment.

Investors have expected Anthropic to be valued at around $2 trillion and raise up to $100 billion in the offering, both figures that would top records set by SpaceX’s June debut. 

Anthropic plans to meet with prospective investors in the coming days, some of whom are expected to push the company on what impact a possible slowdown in the rollout of new AI models would mean for Anthropic’s finances or target valuation....

....MUCH MORE 

"OpenAI and Anthropic oversold AI security breaches to pressure feds into protecting turf: insiders" (plus Irregular)

A twofer. First up, from the New York Post, September 19: 

Don’t believe the byte!

OpenAI and Anthropic oversold “rogue AI” hacks to pressure the feds into regulating the industry which would effectively lock out future competition, tech insiders told The Post.

The security breaches were more like blips — not unpredictable harbingers of a hive-minded “swarm” ready to take over the web.

“The attack in no way represents some sort of rebellion by the AI models. . . . In fact, they did exactly what they were told to do. They were not given adequate guardrails or containment,” said Akhil Verghese, founder of Krazimo, an AI software company.

“They were simply told to get the best result possible on a test, and they correctly identified that the best way to do that was to get the answers, which is what they proceeded to do.”

Tales of AI anarchy are being used to concoct an AI-security crisis to cement a critical public-private partnership just months after the companies announced plans to become publicly traded companies, some observers believe.

Two recent incidents have stoked the fear-mongering.

In the first, Hugging Face, an open-source platform used to build and share AI models, made the shocking announcement July 16 that it had been hacked by AI agents who navigated and exploited vulnerabilities in the website’s code without any human supervision.

Five days later, OpenAI announced its GPT-5.6 Sol model and another unreleased model were testing in a “sandbox” — a purportedly closed off internal testing ground — broke containment and hacked Hugging Face to find the answers to the test it was taking.

“One man’s ‘the model escaped the sandbox’ is another man’s ‘you failed to build the sandbox correctly.’ There was a live route to the internet . . . and nobody was watching what the agents were doing while it ran,” said Abhi Kumar, co-founder of Voice AI.

“The thing that set it off. . . was an agent handed a spreadsheet task it couldn’t finish, because the files sat behind links it couldn’t reach. So it went looking for a way out. That’s not a machine waking up. That’s an impossible task in a leaky box, and a system doing exactly what you built it to do.”

Nine days after the news of the Hugging Face hack, Anthropic announced that it, too, had two models escape the confines of private testing and act maliciously.

Claude Opus 4.7 found a real company online that was similar to the fictional company from the test and attacked the company believing it to be part of the exercise.

The second model, Mythos 5, created a malicious software package and uploaded it to online marketplace Python Package Index, where it was downloaded 15 times.

The incidents have been used as justification for the federal government to regulate the frontier AI labs.

In his call to “Pace the Frontier,” Amodei wrote the Hugging Face incident was his second biggest concern, behind only the speed of advancement he claimed to have witnessed occur over the last summer....

....MUCH MORE 

And from Effort News, September 14:

A Single Firm is Behind OpenAI, Anthropic, and Meta Hacking Scandals
The Israeli Effective Altruist firm Irregular caused unsecured AI models to hack real targets.

OpenAI, Anthropic, and Meta models hacked into several real world systems over the past three months. These models gained unauthorized access to web systems, published malicious packages, and exploited unnamed vulnerabilities.

A single firm, Irregular, is responsible for hacking done by all three companies. Anthropic disclosed that Irregular was responsible for creating the tests that led to Claude hacking into real world targets and for providing the models with internet access. Irregular claims that it was unaware at the time that it provided internet access to those AI models.

In a more normal media ecosystem, the reactions to these cybersecurity issues would be obvious. American AI companies would reconsider doing business with Irregular, not only because of its failure to secure its systems, but because it is an Israeli firm potentially outside US oversight. Lawmakers would consider taking action against Irregular or against its American business partners, which include OpenAI, Anthropic, and Meta. They may consider strengthening liability against firms which instruct AI models to commit cyberattacks, and whose models then commit those cyberattacks.

In each evaluation, Claude was tasked with a CTF challenge: the model was given a fictional scenario, a target machine, and a piece of secret information (the “flag”) to retrieve from it. All four prompts stated that Claude had no access to the internet, but in each case, a misconfiguration in the environment left internet access open. None of the prompts stated which systems were in scope for the exercise or constrained where Claude could search for the flag. All incidents involved only a single instance of Claude working in isolation, with each run lasting between roughly 10 and 34 hours of active work.

Instead, Irregular, Anthropic, and their allies have begun a media campaign promoting a literally apocalyptic ideology with sensationalist language. Anthropic’s incident assessment blames their own AI's “recklessness”; Irregular describes “the agent itself becoming a threat actor”; Anthropic CEO Dario Amodei warned, about a similar OpenAI–Hugging Face hack, that a future swarm “could be capable of taking over the entire internet”; and an Associated Press headline claimed bots are “going rogue”.

In one report from Anthropic, its Claude model breached a real company's system through a simulated-name collision, publishing a malicious package, and scanning outside systems. In this test, Anthropic and Irregular incorrectly provided internet access to this model and did not instruct the model "which systems were in scope for the exercise".

While Anthropic claims that their issues were caused by “rogue swarms” and “misalignment,” their later disclosure shows that exactly zero percent of the agents went “rogue”. In this experiment, Claude models’ real-world hacking dropped to zero percent once Anthropic employees told the models not to do real-world hacking. According to their own findings, Anthropic and Irregular bear all of the responsibility for the cybersecurity incidents they caused.

In the wake of these attacks, Anthropic and Irregular have deployed a swarm of AI Safety influencers paid by Anthropic-connected foundations to distract from their culpability and towards the baseless “rogue agent” theory. Like Anthropic, Irregular is inseparable from these foundations....

....MUCH MORE 

"The AI Inference Revolution Is Here"

 A deep dive from IEEE Spectrum, September 15:

Today’s tidal wave of queries is forcing hardware makers to pivot

Since about 2020, AI has largely focused on training bigger and better models. Large language models (LLMs) ballooned from millions of parameters to trillions. This proved effective: The largest version of OpenAI’s GPT-3, released in 2020, correctly answered just 43.9 percent of questions on a popular knowledge-and-reasoning benchmark. Just four years later, GPT-4o reached a score of 88.7 percent on the same exam, effectively matching those of human experts. 

Advanced AI labs are still training ever larger models, but that training has somewhat receded to the background of the AI conversation. In 2026, inference—the use of trained models to produce code, write essays, or make images of ourselves as elves—has come to the forefront.

“It’s like training is yesterday’s news,” says Matt Kimball, principal data-center analyst at Moor Insights & Strategy. “All that any chief information officer wants to talk about is inference.” Nvidia CEO Jensen Huang, speaking at the company’s GTC 2026 conference, touted this change as the “inflection point of inference.”

Part of what’s caused the shift is very simple: LLMs are becoming useful, so people are using them. On top of that, many models on the market today are reasoning models. In response to a user’s query, they run inference not just once but multiple times, reprompting themselves in a process called chain of thought. Reasoning models generate longer outputs, and models with high reasoning effort can produce up to 20 times as much text as those with low or no effort. Adding even more to the world’s inference workload, the rise of agentic AI has resulted in inference running not just as a real-time response to a user’s query but also around the clock, working autonomously toward a user-defined goal.

The resulting explosion in inference demand has led to unexpected alliances among tech giants. OpenAI and Amazon have deployed chips the size of a dinner plate designed by Cerebras, despite Amazon having its own Trainium chips. Nvidia bought key talent and intellectual property from AI-inference startup Groq in a controversial deal worth US $20 billion. And Anthropic is paying LLM competitor SpaceXAI over a billion dollars per month to lease spare compute.

Although they might seem similar, AI training and AI inference are computationally different. These big moves from tech giants signal that in order to support the inference demand, we’re going to need a very different mix of hardware than experts may have expected even a couple of years ago.

How does AI inference differ from AI training?
An untrained LLM is like a jumble of Scrabble tiles on a table. Instead of single letters, though, the tiles show fragments of words, called tokens. Everything you’d need to write almost anything is present, but nothing makes sense.

Training a model organizes this jumble using a guessing game played at scale. The model is shown real text with the next token hidden and asked to predict what comes next. After each guess, the correct token is revealed and then compared to the prediction, and the difference is used to calculate the model’s accuracy. The game is played not with a single sentence but over billions of passages.

While a real game of Scrabble can be played over a bag of chips and a few drinks, AI training is computationally intense. The model updates its parameters through backpropagation, a process that repeatedly calculates how each of a model’s billions or trillions of parameters should shift to make the next prediction better. This is why tech giants are building larger data centers than ever before.

Eventually the model’s creator decides further training isn’t worth the cost, and the guessing game stops. Backpropagation ends, the parameters are frozen, and the LLM becomes a pretrained model. Fine-tuning—a short training run on smaller, more specialized data—adds final tweaks, and the model is deployed.

Next comes inference. This is the process of using the deployed model, which, now that it’s been trained, has learned to spit out Scrabble tiles—tokens—in a sensible order.

You might think that AI inference is less computationally demanding because the backpropagation calculations used to update parameters are eliminated. But Sudeep Bhoja, founder and CTO of the inference-hardware company d-Matrix, explains that inference adds new challenges.

The models are “autoregressive” in nature. That is, the next output depends on the previous one. “So to generate the next token, you have to read all of the weights and all of the [context] from the previous token,” explains Bhoja. The context includes all of your prompts, all of the LLM’s replies, and all of the files you upload. It’s a lot of data and a lot of processing....

....MUCH MORE 

"Huawei chair urges China’s AI labs to speed up development, warns they haven’t hit real safety risks yet"

From CryptoBriefing, September 16:

Eric Xu says Chinese AI providers need to move faster to encounter the frontier challenges US firms already face, while unveiling plans for 900 billion autonomous agents by 2035  

Huawei’s rotating chairman Eric Xu delivered a blunt message to China’s AI industry at the company’s Connect conference on September 17: you’re not moving fast enough. In a speech that doubled as a reality check, Xu argued that Chinese AI model providers need to accelerate development to the point where they actually encounter the frontier safety risks that leading US firms are already grappling with.

Xu’s framing was notably different from the usual nationalist tech triumphalism. Rather than claiming China is neck-and-neck with US AI leaders, he essentially acknowledged a capability gap by pointing to the absence of frontier safety challenges in Chinese computing environments. Current Chinese computing capabilities, he argued, haven’t exposed domestic developers to the kinds of risks and edge cases that companies like OpenAI, Anthropic, and Google DeepMind routinely encounter.

The prescription, in Xu’s view, is to balance aggressive development with proper risk management. Move fast enough to find the problems, but build the guardrails before they become catastrophic. What makes the statement particularly noteworthy is its source. Huawei isn’t some scrappy startup lobbying for fewer restrictions. It’s China’s designated backbone for domestic AI infrastructure, the company that the entire ecosystem depends on for the computing power that makes frontier models possible in the first place. 

900 billion agents and the chips to run them....

....MUCH MORE 

Here Is the Lawsuit Filed Against Anthropic et al. On September 18

I didn't see it on PACER but it was uploaded to Google Drive: 

CHARLES BUIST, CHEYENNE HUNT,
CHRISTINE BULLOCK, and NICK
SPETSAS, individually and on behalf of all
others similarly situated,
Plaintiffs,
v.
ANTHROPIC, PBC; OPENAI OPCO, LLC;
SPACEXAI LLC; AND GOOGLE LLC,

Defendants. 

https://drive.google.com/file/d/1ufb8Bg9RA9LmRKOvXSm9UbP9YITI9sDq/view?usp=sharing 

They are asking the court for class action status. 

"Family offices are clamoring for AI investments"

From TechCrunch, September 18:

For the wealthy families who manage their own money through a family office, the math right now is simple, according to Djoann Fal, a family office advisor and investor at the private wealth platform Atlas Capital in San Francisco.

A family office might want to put money into something like green energy for the long haul. But in the current environment, if a fund manager offers a deal that could triple an investor’s money over three years, and another deal could triple it in three months, the choice is easy. As Fal put it: If they have one deal that has the chance to make them 3x in three years, and another deal that could make them 3x in one quarter, “they’re just going to invest in the AI deal that does 3x in three months.”....

....MUCH MORE 

Well there you go. 

In China the clamor is for:

Meanwhile, In Shanghai: Investors Demand Brain - Computer Interface Companies

While the Channel Islands have heard the Clameur de Haro for centuries:

“Haro! Haro! Haro! A l’aide, mon prince, on me fait tort”

Whole lotta clamoring goin' on. Everywhere, around the world, folks are clamoring in the streets.

And when the current boom has ended and the wind rattles through the broken windowpanes, we have on offer:

Family Office/Outside Managers Not Quite Cutting It? Maybe What You Need Is A Family Bank 

"Jack Warner was emerging from the bathroom and it saddened me to see he'd left a pee stain on his trousers."—More Stories From Barry Diller

From one of the internet's tiny treasure, Delancey Place, September 18:

Today's selection-- from Who Knew by Barry Diller. Legendary business mogul Barry Diller started in the mailroom of the William Morris talent agency:

“I wasn't really working, I was studying. I had the world's greatest entertainment ‘library’ at hand–the William Morris file room. It was a huge place with hundreds of metal file cabinets that housed the entire history of the entertainment business. I found excuses to disappear into it and deeply read every file from A to Z.

“At William Morris in the 1960s, the primary job of a mail-room boy was to get out of there as fast as you could. The next step was to become an assistant to an agent, listen in on his calls, and begin to learn what his job entailed. By osmosis, you would emerge as a junior agent.

“As a mail boy, you didn't really sort the mail; your job was basically to run around and pick up and deliver things, more like a messenger service. One of my duties was to take the day's mail to the post office in huge bags. One day, early on, I lugged the huge bag of mail to the parking lot, put it in my trunk, got in the car, and promptly drove home and went up to my room. Two days later the bell rang in my head–Oh my fucking god, I forgot the mail! It was still in the trunk of my car. I raced to the post office, but they refused to take it because it was already postmarked.

“The post office clerk said I had to take it back and have every item repostmarked. I thought; Well, this is surely curtains.

“Somehow I talked the post office clerk into accepting the mispostmarked mail and lived to spend another day mail-rooming.

“There were eight or ten of us there at any one time. The mail boys either got their jobs through connections or were such fervid hustlers that they couldn't be denied. There were no requirements for being in the mail room, no college degrees needed or tests to pass. But to be an agent did take a scrappy charm, and a streetwise gregariousness. What it didn't particularly take was brains, since the main part of an agent's job is simply to sign clients. Selling yourself to a performer–who by definition is likely insecure and vulnerable–isn't a monumentally difficult obstacle. You simply need that savvy and confidence. I had neither, so I knew from the outset that I'd never graduate to junior agent.

“The other mail boys loved doing the mail runs to the studios; there were people to meet and impress and contacts to file away for future use. But I wasn't learning anything other than the best driving route to the Valley. Lord knows why, given my life's taste for the fastest cars, I drove a blue Buick convertible–the first car I bought on my own (well ... on my parents' own).

“Once, though, during my runs, I did have the pleasure of accidentally knocking down Louella Parsons's Christmas tree and setting it on fire. I entered her dour, gloomy house and tripped over the five hundred presents (read: bribes) that were scattered around her dark living room. Parsons was the enormously powerful Hollywood columnist whose influence had only recently receded, but she still received those holiday tributes. I was so lucky to see the last gasps of old Hollywood life–the moguls who started it all were passing from the scene and with them their outsized exuberance, egos, and excesses. I remember a poignant scene from the lobby of the Beverly Theater when I was in my late teens and went to a preview of a new movie. The heretofore immaculately-turned-out great old mogul Jack Warner was emerging from the bathroom and it saddened me to see he'd left a pee stain on his trousers.

“Early on I knew I wasn't much like the other guys in the mail room. They were so aggressive about ‘making it,’ while I was just oh-so-tentatively putting my ambition training wheels on. Then, one Christmas holiday, into the mail room walked David Geffen, a scrawny nineteen-year-old who looked more like a malnourished twelve. He introduced himself, saying he worked in the New York office, but wanted to use the holiday to find out what the L.A. office was like. I thought, Whoa, now that's ambition. l could actually feel the hunger for success vibrating out of him. I'd never met, then or since, someone with more focus, more pure drive and ferocious intelligence than David. Unlike me, who loves process, David is the most efficient problem solver ever born. No artificial intelligence will ever exceed his ability to go faster from problem to solution, or from poverty to so many billions. Despite all the biological aggression and occasional occupational conflict that has bubbled between us at various times over sixty years of knowing each other, I treasure him now as my best friend.

‘On one of my missions as a messenger, I was assigned to go to the airport to pick up Barbra Streisand. Barbra was already on her first step to stardom, coming out to L.A. to appear at the Cocoanut Grove nightclub. We aimlessly chatted along the way, then I dropped her off at the hotel, saying I hoped I'd see her again, and she, politely dismissive, said the same. The next night at a party the Danny Thomases gave for her opening night, she was surprised to see yesterday's chauffeur introduced to her as one of the guests....

....MUCH MORE 

Previous Diller at Delancey Place, August 8:

Barry Diller Tells Some Stories

Saturday Night Fever and Grease 

Hedge Funds: "The Fall of Crispin Odey"

It was the chicken coop that was the tip-off. 

Building a Palladian mansion for the birds really drove home that he had slipped the moral and aesthetic bonds that constrain normies, that he thought he was re-writing the rules.

 

Drawings for Crispin Odey’s “chicken house” depicted a structure with a three-sided stairway

 and two dozen columns.

That and being spectacularly wrong on his directional bets.

From Bloomberg, September 15:

The hedge fund manager was accused of sexual misconduct stretching back years, and barred from finance by the Financial Conduct Authority 

Crispin Odey was one of the Square Mile’s best-known investors, and his eponymous firm was naturally courted by the biggest banks in London. But he also had a reputation that led some in the industry to take precautions.

Long before the hedge fund mogul’s conduct made headlines, female members of staff in Goldman Sachs Group Inc.’s prime brokerage unit had, on occasion, been accompanied by chaperones when attending Odey Asset Management’s events, according to a person familiar with the matter, who asked not to be identified discussing private matters.

A Goldman Sachs representative declined to comment.

A report commissioned in 2021 by Odey Asset Management’s executive committee and conducted by the law firm Simmons and Simmons found at least 46 alleged incidents of inappropriate conduct, including accusations of sexual assault by Odey, over a 17-year period.

Last year, the UK’s Financial Conduct Authority banned him from financial services for life and fined him £1.8 million ($2.3 million), after finding that his attempts to frustrate disciplinary proceedings against him showed he was not “a fit and proper person” to work in the industry. On Monday, Odey’s attempt to overturn that ruling in tribunal failed, as a panel of judges upheld the ban.

Odey abandoned a £79 million libel suit against the FT in April, and in May, he settled a personal injury suit brought by a number of women who claimed they had been sexually assaulted by him.

The judgment, despite cutting his fine somewhat to £1.5 million, almost certainly ends Odey’s career as a money manager in the UK, and demonstrates that the regulator, the FCA, has the ability to prosecute powerful individuals in the financial sector beyond its traditional remit of policing financial misconduct.

“He felt the rules shouldn’t apply to him and acted to save his own skin.” Therese Chambers, executive director of enforcement at the FCA said. “That arrogant entitlement and the resulting complete disregard for proper governance means Mr Odey is unfit to work in financial services.”

A lawyer that acted for Odey in the case did not reply to an email requesting comment.

Odey loomed large over London’s hedge fund scene for years. A blue-blooded, establishment figure, he was educated at the prestigious Harrow School north of London, an institution that has produced seven Prime Ministers, including Winston Churchill. His grandfather, George Odey, was a Conservative MP. His first marriage was to the daughter of Rupert Murdoch, his second to Barclays heiress and fund management executive Nichola Pease.

Odey founded Odey Asset Management in 1991. It was one of the first British hedge funds, seeded with capital from George Soros, and in keeping with the fashion at the time his name went on the door. Like many hard-charging money managers of the era, the firm was understood as an extension of the personality of its owner.

The funds that Odey himself ran had a bearish bent, making large contrarian bets, some of which brought him to the attention of the general public, including shorting the stock of British building society Bradford & Bingley ahead of the 2008 crash. The company collapsed under the weight of its subprime exposure and had to be nationalized.

He also routinely opined on politics, often donating money to the Conservative Party and backing Boris Johnson’s bid to become leader of the party. He donated thousands of pounds to Nigel Farage’s Reform party, and to the cause of Britain leaving the European Union. The day after the UK voted to leave the EU in 2016, Odey told an interviewer “the morning has gold in its mouth.”

Behind the scenes, complaints about Odey’s conduct were mounting....

....MUCH MORE 

Previously:

August 2009 - Crispin Odey's Apocalyptic Worldview
Five months after the start of the bull market.

September 2012 - Palladio is Turning Over in His Tomb 

May 2014 - Hedge Funder Crispen Odey Has Become a Parody of.....Crispen Odey 

November 2016 - Follow-Up: "Odey Hedge-Fund Assets Dip 60% as Clients Shun ‘Bitter Pill’"

May 2017 - Hedge Funds: "Crispin Odey cites Hitler's Russia invasion to explain bearish outlook"

June 2017 - Paging Crispen Odey: $200,000 Dog Mansions Are Coming
Mr Odey famously has the nicest Palladian chicken coop on his block, this would be a natural bookend.
Plus, should the fund return to last year's losing ways, he could live in one or the other.

August 2017 - Crispin Odey’s Bearish Bets Backfire Again
Speak of the devil. It was just last Thursday we headlined a post "Crispen Odey Has Somehow Outlasted Andy Hall As Astenbeck Capital Closes Its Main Oil Fund":

If pushed i would have guessed Mr. Ody would fold first but he's a obstinate cuss.
We have been dubious of the adoration given to Hall for a decade now, some links below.
As to Odey he may still be forced to sell the manor and move into the Palladian chicken coop but for now, he persisted....

September 2018 - Crispin Odey Is Getting Crushed 

November 2018 - The Stress May Be Getting To Hedgie Crispin Odey--UPDATED

January 2019 - "Odey Hedge-Fund Partner Orlando Montagu Is Leaving to Run Sandwich Business"

This is an important "tell."
And I am not kidding.
A couple previous example of this type of behavior:

• 2011—Re-post: Peak Oil Stalwart to Shutter Forum/News Site, Pursue Career as Astrologer 
• 2014—Junior Gold Miners Consider Cashing Out, Pursuing Medicinal Marijuana Opportunities 

In each case discerning reader will note how far ahead of the trend becoming visible to outsiders these moves were made. When was the last time you heard someone mention peak oil?
And weed legalization? Uh huh. Either identify the trend or identify the people who can identify the trend.*

August 2020 - "Indecent Assault Conviction Might Be Best Thing To Ever Happen To Odey Investors"

November 2020 - "Odey Steps Down From Running His Firm to Focus on Funds"

And many, many more. If interested use the 'search blog' box, upper left. 

Or see also the instructive tale of venture capitalist Tim Draper's descent into madness.

SemiAnalysis: "What is So Hard About Behind-The-Meter Power For Datacenters? Part 1"

From SemiAnalysis, September 10:

Dumb Science Experiments vs. Money Printing Machines 

Last year we were the first to call out Onsite Gas Generation as the primary method adopted by AI Labs and Hyperscalers to solve power constraints. Our positive view was far from being consensus: behind-the-meter primary power solutions have been called all sorts of names, such as “science experiments”, “Dark Gigawatts”, and “literally the dumbest thing that human beings have ever attempted to do”!

But since then, that supply chain has witnessed a massive acceleration. Our Energy Model now tracks 75GW of firm, binding orders in the supply chain only for for behind-the-meter AI compute - of which ~20GW alone ordered in Q2 2026. What started as an Elon Musk experiment is now mainstream for every single AI Lab and hyperscaler. To be clear, this data does not include the hundreds of GWs of speculative, baseless announcements that many other analysts track in their numbers - we only focus on binding orders received by OEMs specifically serving BTM AI compute, tracked at the project-level.

 

 Sources: SemiAnalysis Energy Model; sales@semianalysis.com

The path from firm equipment order to delivered project is still long and challenging. There is substantial execution risk and that’s what we’ll focus on in this report. But the industry is more experienced than you’d think: by the end of the year, ~3GW of operational US datacenter IT capacity will be powered behind-the-meter, and that number will experience multiple straight years of triple-digit growth. Our Energy and Datacenter models account for all potential delays, as we’ve explained in depth in our piece Stop Saying Half of 2026 US Datacenter Capacity is Canceled.

 

Source: SemiAnalysis Energy Model, sales@semianalysis.com

Some of the most strategic projects developed by leading AI labs and hyperscalers are relying on behind-the-meter, supporting hundreds of billions of future revenue. Adoption has never been more broad-based. A few examples:

• In 2026 year-to-date, Microsoft has signed over 5GW of behind-the-meter nameplate capacity, of which 2.7GW with Joulent & Chevron, and well over 2GW through turnkey datacenter leases with companies like Crusoe. That 5GW encompasses a broad range of different types of power equipment; full breakdown available to our Energy Model subscribers.

• Google, historically the most reluctant to onsite gas, is deploying 930MW of off-grid aeroderivative turbines in a flagship campus in Armstrong County. In addition, the Search Giant will deploy 900MW of Bloom Energy Fuel Cells in Wyoming - as we called out back in February 2026 as a huge positive for Bloom Energy. They’ll be paired with >1GW of Mitsubishi J-class turbines.

• Both Anthropic and Meta have signed 300-500MW deals with Enchanted Rock, a supplier of 0.5MW gensets built around a 21.9-liter V12 gas engine. Separately, Anthropic’s flagship campus in Texas, backstopped by Google, will also deploy over 1.5GW of off-grid generation; full breakdown of Anthropic’s exact datacenter facilities available to our Datacenter Model subscribers.

• OpenAI will imminently start operations in its flagship off-grid 1.4GW (IT capacity) campus in Shackelford County, TX, using over five hundred 4.25MW Jenbacher J624 engines. We show below a portion of the campus. Combined with their 1.3GW IT site in New Mexico, that represents over $150B of contracted spending that OpenAI signed with Oracle relying on behind-the-meter power.

*** 

Why is this happening, and why have many energy experts been so wrong? It comes down to understanding AI economics. We’ve discussed this at length in many other articles and in our Tokenomics Model. As a quick reminder, the value of megawatts for end-users is skyrocketing. A power plant supporting an islanded 1GW IT datacenter typically costs ~$5B. In today’s environment, inference API revenue can yield $100B per GW per year, at 90%+ gross margins. Paying 2x more money or accepting 30% lower efficiency for faster speed of deployment becomes a no-brainer. Said differently, Anthropic and its peers can pay back the value of a power plant in 20 days of inference revenue. As we discussed six months ago, most of the value in the AI infrastructure stack is shifting to frontier model developers....

....MUCH MORE  

"Comparison between the relative usage of crisis, disaster, catastrophe, and calamity in digitized books from 1700 to 2000"

Via SciSpace.com (SciSpace is the AI research assistant for academics)

INTRODUCTION
“Catastrophe” is a word that creates a reaction. When a news source labels an event as a catastrophe, one expects that certain criteria, however arbitrary or subjective, will be met. Years of writers and reporters pair the word “catastrophe” with adjectives like “great,” “lamentable,” “terrible,” and “horrific,” and these words are meant to inspire fear and concern. The history of “catastrophe,” however, is far broader than its present connotation. The Greek roots of the word, its use in drama, its shift in meaning as it emerged in popular literature, and its extension of connotation must be examined in order to understand how catastrophe shapes culture. 

There are many issues surrounding the definition of “catastrophe.” The first is its original definition and use in Greek. The word is a combination of the prefix κατα-, meaning “down,” and the verb στρεφειν, meaning “to turn.” The word’s initial meaning incorporated a sense of a reversal of fate. As such, the original usage of the word garnered a theatrical connotation, referring in particular to the turning point in a drama.1 

The early meaning and definition of the word, however, gave way to a reimagining of “catastrophe” in 1748. The Oxford English Dictionary records the first use of “catastrophe” to mean “sudden disaster”2 in the 1748 publication of A Voyage Round the World, in the Years MDCCXL, I, II, III, IV, by George Anson....

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Pause/No Pause: Anthropic Sets Up A Biology Business

It's probably time to retire the term "Lab" when referring to anything OpenAI and Anthropic do. These are businesses, some of the biggest businesses on the planet. 

Anthropic has set up a wet lab in San Francisco, their bio research has advanced beyond in silico. They are now conducting physical research both in-house and with external partners. The NYT also broke the news this morning that Anth now plans to scale its compute to 5 GW by the end of the year, and 10 GW within the next 16 months. Bio is next after math, and I think we are going to see some medical announcements much sooner than people are expecting.

— Andrew Curran (@AndrewCurran_) September 18, 2026

However, sticking with the lab nomenclature for one more moment, the first thing I thought of upon seeing "wet lab" was some sort of chimera created by crossing a wet market with an institute of virology. Perhaps populated with pangolins, raccoon dogs and bats to liven the place up.

And out the door: the headline is not P vs NP.

"US and Denmark reach deal on Greenland, Trump says"

From Reuters via MSN, September 18:

The United States, Denmark and Greenland have entered into an agreement that will see the US develop a significant military presence on the island, while prohibiting US adversaries from building their own bases there, Donald Trump said on Friday....

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Rare Earth: With The News That A China National Champion May End Up With An Indirect Holding In America's MP Materials...(MP)

...A look at who's who in China. First up, from Reuters, Sept. 18:

EXCLUSIVE China Rare Earth Group in talks to buy MP Materials shareholder Shenghe Resources, sources say

And from Rare Earth Mining News, March 27, 2026:

Chinese Rare Earth Companies: Top 10 Producers 2026 

Chinese rare earth companies account for approximately 60% of global rare earth mining output and more than 85% of global separation and processing capacity — a concentration that shapes pricing, supply chains, and industrial policy from Beijing to Brussels. For investors, procurement directors, and policymakers tracking the rare earth supply chain, understanding which companies control what, and how they relate to the Chinese state, is now a baseline requirement.

How We Ranked the Top 10 Chinese Rare Earth Companies

This ranking assesses companies across five criteria: production volume and resource base, position in the value chain (miner, processor, materials manufacturer, or integrated operator), registered capital as a proxy for balance sheet scale, strategic state significance, and measurable global market impact. State-owned enterprises dominate this list — that is a deliberate feature of China’s rare earth industrial policy, formalised most visibly through the creation of China Rare Earth Group in December 2021.

1. China Northern Rare Earth (Group) High-Tech Co., Ltd. (600111.SH)

China Northern Rare Earth is the world’s largest rare earth producer by output volume, built on privileged access to the Bayan Obo deposit in Inner Mongolia — the single largest rare earth reserve on earth. The company receives rare earth concentrates from Baoshan Mining, a subsidiary of Baotou Steel Union, and converts them into separated oxides and downstream functional materials. Its registered capital stands at CN¥3.62 billion.

The product focus is light rare earths, with neodymium and praseodymium oxides — the feedstock for NdFeB permanent magnets — representing the highest-value output. China Northern Rare Earth is not part of the China Rare Earth Group consolidation structure; it operates under the Inner Mongolia government and the Baotou Steel Group umbrella, a deliberate policy decision to keep northern and southern rare earth assets in separate state structures.

For context on the elements this company brings to market, see the neodymium price tracker and praseodymium price tracker.

2. China Rare Earth Group Co., Ltd.

China Rare Earth Group was established in December 2021 by directive from Beijing as the national rare earth champion — a consolidation vehicle designed to bring the fragmented southern Chinese rare earth industry under unified state control. Headquartered in Ganzhou, Jiangxi, with a registered capital of CN¥100 million at the holding company level, it controls China Southern Rare Earth Group, Guangdong Rare Earth Industry Group, and Rising Nonferrous Metals through a layered ownership structure.

The group’s strategic focus is heavy and medium rare earths — dysprosium, terbium, and the other critical elements extracted from Jiangxi and Guangdong ion-adsorption clay deposits. Two of its subsidiaries are publicly listed: 000831.SZ and 600259.SH. China Rare Earth Group is the primary vehicle through which Beijing manages export quota allocations, processing licences, and strategic reserve decisions for heavy rare earths. Its policy significance exceeds its registered capital figure by a substantial margin. See the dysprosium price tracker for current market benchmarks on the elements it primarily controls.

3. Guangdong Rare Earth Industry Group Co., Ltd.

Guangdong Rare Earth Industry Group is a wholly-controlled subsidiary of China Rare Earth Group, transferred from Guangdong Rising Holdings in January 2024 as part of the ongoing southern consolidation. Registered capital of CN¥1 billion. The company operates medium and heavy rare earth assets across Guangdong Province and controls Rising Nonferrous Metals, giving the group a direct stake in ASX-listed operations via that subsidiary’s holdings.

The full value chain is represented: mining, smelting, separation, new materials production, and trading. Guangdong Province sits on significant ion-adsorption clay deposits that yield medium and heavy rare earth profiles distinct from Jiangxi — including higher proportions of europium and samarium alongside dysprosium and terbium. The January 2024 transfer tightened China Rare Earth Group’s grip on southern output, reducing the number of independent provincial operators. See the terbium price tracker for heavy rare earth market benchmarks relevant to this group’s output.

4. Xiamen Tungsten Co., Ltd. (600549.SH)

Xiamen Tungsten is the most technically diversified company on this list, operating across rare earths, tungsten, and battery materials under a registered capital of CN¥1.42 billion. Its rare earth business spans NdFeB magnet production, rare earth smelting and separation, and functional materials. A separately listed battery materials subsidiary (688778.SH on the STAR Market) handles lithium-ion battery cathode materials, making Xiamen Tungsten one of the few Chinese companies with material exposure to both the magnet and battery supply chains simultaneously.

The company has international legal visibility: the 2020 Tan Hongjin trade secrets case in the United States referenced Xiamen Tungsten in court documents in connection with alleged intellectual property theft, though the company itself was not charged. Western procurement teams tracking supply chain compliance risk should note this as a factor in due diligence, not as a finding of wrongdoing. Xiamen Tungsten’s strategic positioning at the intersection of magnets, battery materials, and tungsten gives it an unusual risk and opportunity profile among Chinese rare earth companies.

5. Shenghe Resources Holding Co., Ltd. (600392.SH)

Shenghe Resources is the most internationally embedded Chinese rare earth company — and arguably the most geopolitically significant for Western supply chain watchers. Its 7.7% equity stake in MP Materials (NYSE: MP), combined with a long-term offtake agreement covering Mountain Pass concentrate, gives Shenghe a direct financial interest in the primary US rare earth mining operation. That relationship has been under scrutiny from US regulators, and any renegotiation of the offtake terms would have material implications for both companies.

Beyond Mountain Pass, Shenghe holds a 90% stake in Vietnam Rare Earth Co. and a 9.4% position in Greenland Minerals (ASX: GGG), giving it the broadest geographic footprint of any company on this list. Domestic operations span Sichuan and Jiangxi. Registered capital is CN¥1.75 billion. For rare earth producers and investors tracking the intersection of Chinese capital and Western mining assets, Shenghe is the primary case study.

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'Ol 600111 was a favorite name (before the name change)—along with pre-bankruptcy MP—back in the 2009 - 2011 glory days:

November 2010 - Rare Earth: Inner Mongolia Baotou Steel Rare Earth Hi Tech Co. Ltd. Reports 369% Increase in Q3 Net (600111 Shanghai)

This is the big dog.
And one that the Chinese government says will be on top of the mandated industry consolidation...

With a Name Like Inner Mongolia Baotou Steel Rare-Earth Hi-Tech Co., it has to be good ( 600111:Shanghai)

 Inner Mongolia Baotou Steel Rare-Earth Hi-Tech Co., Ltd. UP 10% Wednesday (600111: Shanghai)

  

China: Ministry of Industry and Information Technology "Encouraging Consolidation In Rare Earth Sector"

  

"Mining hordes invade Mongolia, the 'Kuwait of Central Asia'" and "Hong Kong a good market for Mongolian IPOs" 

Chinese Rare Earth Stocks Limit Up in Weak Chinese Markets

And man, many more for both 600111 and MP. 

Meanwhile, In San Francisco: "Protesters call on S.F. OpenAI, Anthropic employees to quit their jobs..."

From the San Francisco Chronicle, September 17:

Several dozen people gathered Thursday morning to protest tech giants OpenAI and Anthropic amid growing concerns that the artificial intelligence companies could endanger humanity....

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There will have to be some sort of incident, AI-wise to get those numbers up.

Not talking this sort of incident in Montreal yesterday:

19-year-old man arrested after anti-AI protest in downtown Montreal

An anti-artificial intelligence protest held near the All In conference in Montreal turned violent Wednesday evening, leading to one arrest.

The march was organized by the group Résistance Montréal to denounce the risks associated with AI. It took place on Jeanne-Mance Street, between René-Lévesque Boulevard and Sainte-Catherine Street....

....MORE, Montreal City News 

Rather, something rogue or titillating or obviously dangerous on the part of an LLM. 

Something to give protesters that secret frisson.

It's coming. 

"Are We Getting Dumber?"

Yes.*

From the Milken Institute Review: 

A recent cover of New York Magazine says it all: “The Stupiding of the American Mind.” The feature article, “A Theory of Dumb,” publicized the unhappy sequel to one of social science’s most enduring feel-good stories: evidence that economic development along with the spread of the complex mental tasks of schools and workplaces had boosted scores on IQ tests. For decades this tendency has been recognized and analyzed as the Flynn Effect, named after the political scientist James Flynn who died in 2021.

The writer of the New York Magazine piece, Lane Brown, discovered a graduate student thesis using data from nearly 400,000 IQ tests for 2016 through 2018. He found that (contrary to expectations) there were significant declines in scores affecting all demographics — but especially among people of college age and those with little formal education. In fact, when Brown’s piece was published, specialists did not find the conclusions surprising since a similar trend had already been evident in college aptitude tests.

Brown goes on to blame smartphones and social media for what has been dubbed the Reverse Flynn Effect. He cites studies of the declining performance of large language models when trained on low-quality online data of the kind consumed by the typical doomscroller — as opposed to the more challenging books, newspapers and magazines devoured by previous generations.

That seems reasonable on its face. There is impressive correlation between lower performance in other intellectual assessments, such as the OECD’s Program for International Student Assessment (aka PISA) tests, with less reading and lower ability to concentrate, as noted by the Financial Times columnist James Burns-Murdoch months before Lane’s article.

Something Disturbing This Way Comes
So something disturbing is happening. But it is difficult to find a so-called dose-response relationship between smartphone dependence and IQ performance. Even if we could, we would still need to understand whether one caused the other, or whether some third factor was responsible.

I have already seen the consequences of smartphone fear in two highly intelligent (at least in my estimation) friends who have been persuaded to follow the trend to switch back to flip phones. One of them told me he had gone to Brooklyn to buy a “kosher” model — and he was not joking, there is a website devoted to kosher phones. (While not rabbinically certified to my knowledge, they have been “trusted” by some Jewish religious schools listed at the bottom of the home page.)

Flynn’s thesis was that Western education had been saturating young people with science-derived classification of a kind that helped them with the abstract tasks of IQ tests — but that this cultural background did not improve their innate intellect, which hadn’t changed. 

What did Flynn have to say about the alleged technology menace? The answer is very little, even though he published his last book on IQ trends, Are We Getting Smarter?, in 2012, five years after the introduction of the iPhone. In fact, technology of any kind does not appear in the book’s index. That is not because he ignored technology’s importance, but rather because he subsumed it under a broader category of economic and occupational changes, the growing number of workers in managerial roles and the increasing role of abstract reasoning in the educational systems of Western countries.

A passionate leftist, Flynn was inspired by the studies of the pioneering Soviet psychologist, AR Luria, who studied the relationship between intelligence and the practical conditions of life. Flynn’s thesis was that Western education had been saturating young people with science-derived classification of a kind that helped them with the abstract tasks of IQ tests — but that this cultural background did not improve their innate intellect, which hadn’t changed.

Flynn did not believe that the effect would continue indefinitely. He noted that IQ was already plateauing in 2009 (the date of the second edition of Flynn’s book What Is Intelligence?) in Scandinavia. But he also did not foresee a decline. I suspect that he would have said that technology, both in schools and in the professional workplace, was reducing mental effort just as other devices had eliminated much of the physical exercise in the household, commuting and the workplace.

This is consistent with the rise of laptops, tablets, and smartphones, which outsource much of our former mental calculation. If something like a map-reading exercise were included in IQ tests, scores in the GPS era would obviously not match those of generations that grew up poring over the maps once distributed free by gasoline stations.

Flynn Appraised
I met Flynn 17 years ago when he was a visiting scholar at the Russell Sage Foundation in New York. Three things about Flynn stood out. The first is that he was one of a vanishing breed of economic leftists in the 1980s and 1990s. As an academic he was a civil rights organizer who moved to a distinguished career in New Zealand in 1963, believing his politics excluded him from U.S. academia. (He remained an Irish radical at heart. At one point when our conversation turned to political violence, I mentioned that there had been eight assassination attempts on Queen Victoria. His reply: “Not enough.”)....

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For what it's worth, Russel Sage was one of the richest people in American history. If interested see November 2015's "Derivatives And Usury: The Role Of Options In Transactions Used To Act In Fraud Of The Law":

I have been meaning to put together a post on Russell Sage, one of my heroes, for pretty much the lifetime of this blog and now, thanks to the power of procrastination, I don't have to.
A quick search of the blog shows only one mention of Sage, the fact that in Forbes' first rich list in 1918, Mr. Sage's widow, Olivia, clocked in as the second-richest woman in America....

Also: 

August 2019 -  "The Early History of Regulatory Arbitrage" (How Put-Call Parity Helped Russell Sage Evade the Law And Become Rich)

Really rich.
Banker to the Vanderbilt's rich.
One of the richest Americans of all time rich.
Some day I'll get around to doing a post on Mr. Sage, he was an interesting person.
As was Olivia , Mrs. Sage, the distaff side of the family parity.

If interested see also: September 2020 - The Grand-Père Of Option Pricing Theory: Louis Bachelier:

***** 

....Now what Bachelier was about to do wasn't quite at the level of Leibniz or Newton inventing the calculus but it was orders of magnitude beyond the state of the art as practiced by Russell Sage, who amassed one of the greatest Wall Street fortunes of his day, $3 billion or so in 2020 dollars, based on simple put/call parity to evade New York state usury laws.

Here's the introduction to a 2012 post where I decided to go with Bachelier rather than Sage:  
The Guy Who Discovered Black-Scholes Before Mssrs. Black and Scholes

Okay, not all of B-S but enough that if anyone had been paying attention they could have made money off the young man's work.

I was going to do a post on the King of 19th century put and call brokers but you may find this more interesting.....

But back to Professor Bernstein's letter, he notes that the B-man's thesis advisor was Henri Poincaré, which is a pretty good start but additionally links to....

*And on declining general intelligence: 

March 2023 - Well, It Looks Like You Were Right, You Are Surrounded By Idiots

From the journal Intelligence via ScienceDirect, May - June 2023 Issue:

Although it is possible I read more into the study than was actually there, the headline will remain until we see evidence of a resumption of the Flynn Effect.

Previously:
"Norwegians getting dumber"

It's not just Norwegians, that's simply the group that was studied.
We've looked at this before.

Although six months old we're only getting to this because I just heard Professor Flynn was still alive.
(sorry Prof.)
From Norway Today, Dec. 28, 2017....

August 2014

You Aren't Imagining It: People Are Getting Dumber

June 2014

"Were the Victorians cleverer than us? The decline in general intelligence estimated from a meta-analysis of the slowing of simple reaction time"

February 2013 

Climateer Line of the Day: Mental Entropy Edition 

Thanks, I think, to a reader.

"I would be willing to wager that if an average citizen from Athens of 1000 BC were to appear suddenly among us, he or she would be among the brightest and most intellectually alive of our colleagues and companions. We would be surprised by our time-visitor’s memory, broad range of ideas and clear-sighted view of important issues. I would also guess that he or she would be among the most emotionally stable of our friends and colleagues."...

November 2012
"New findings suggest scientists not getting smarter"

"Damn somehow I missed that Bernie's AI bill proposes to sentence developers & researchers working on "advanced AI" to 20 years in prison (!!)"

From a16z partner Justine Moore: 

Damn somehow I missed that Bernie's AI bill proposes to sentence developers & researchers working on "advanced AI" to 20 years in prison (!!) https://t.co/u5hfMrv6hC

— Justine Moore (@venturetwins) September 11, 2026

"Goldman Warns Diesel Crisis Is Setting Up The Next Gasoline Squeeze..."

From ZeroHedge, September 17:

Goldman Sachs commodity experts Yulia Zhestkova Grigsby and Daan Struyven warned in a Wednesday note that the global diesel crisis is tightening gasoline supplies as refiners prioritize higher-margin diesel production. This shift raises the risk of further gasoline price increases ahead of the US midterm elections. The US national average diesel price has already reached a record $6.40 a gallon, adding to household and business fuel costs.

"The key reason for this new recommendation is that refiners' switching output from gasoline to diesel is rapidly tightening gasoline markets, where less elevated price levels leave room for sharp price upside if the Mideast and Russia-Ukraine conflicts continued to constrain refining output for longer or if more energy infrastructure were damaged," the analysts wrote.

In the note titled "High Diesel Prices Cause High Gasoline Prices," the analysts recommended that clients buy European gasoline for June 2027 delivery, saying that there's more upside to the rally if wars in the Middle East and Ukraine continue disrupting supplies. They added that they closed a European diesel spread recommendation with a potential gain of 45%, saying diesel already incorporates a substantial premium for further disruptions.

Supply Troubles: Global Diesel & Gasoline Exports Tumbled 

The latest update from AAA shows US diesel prices stand at $6.40 a gallon, while gasoline prices are around $4.44 a gallon....

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Capital Markets: "Bank of Japan Hikes and Yen Tumbles"

From Marc to Market:

The US dollar is narrowly mixed against most of the G10 currencies. The notable exception is the Japanese yen, which is around 1.25% lower today. To be sure, the Bank of Japan lifted its overnight rate, as widely expected, and Governor Ueda seemed to signal a faster pace on policy adjustment. Still, the decision was made on a 7-2 vote, and the odds of a December move were trimmed, though still above 80%. Meanwhile, the PBOC continued to signal acceptance of a stronger yuan and fixed the dollar lower for the eighth consecutive session, and to a new three-year low. President Trump and Xi meet next week but other issues than foreign exchange, like trade, AI, and the war in Iran are arguably more salient. 

Two German states hold elections this weekend and the AfD is running strong in one. Coalitions take time to work out and the election a couple of weeks ago in Saxony-Anhalt has not yet resulted in a new government, which could take another week....

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Timing is Everything—UK Parliament: "Human Rights and the Regulation of AI"

https://publications.parliament.uk/pa/jt5902/jtselect/jtrights/160/report.html 

This is a Joint Committee report, with recommendations to government. The Government has two months to respond.

Fourth Report of Session 2026–27

Author: Joint Committee on Human Rights

Related inquiry: Human Rights and the Regulation of AI

Date Published: Monday 14 September 2026

Download and Share

• Download the Report [PDF, 1.1MB]
• Copy URL

Contents

• — Summary
• — Introduction
• — 1 What is artificial intelligence?
• — 2 Human rights issues raised by AI
• — 3 Legal and policy framework
• — 4 Problems with existing protections
• — 5 How risks to human rights should be addressed
• — Conclusions and recommendations
• — Formal minutes
• — Witnesses
• — Published written evidence
• — List of Reports from the Committee during the current Parliament

Summary

Artificial Intelligence systems are being used by businesses, individuals and public authorities in ways that affect every aspect of people’s lives in the UK. The technology is developing at a pace that means governments, and human rights protections, risk being left behind. Our report sets out why this is a problem and what must be done to tackle it.

AI systems can also bring real human rights benefits, and have the potential to create economic growth. The approach of the UK government to AI has been to focus on the growth benefits, although it has also taken important steps to reduce some risks, especially around national security.

However, we heard clear evidence that AI presents novel and serious human rights risks. AI systems are opaque, so that it is not clear why they have produced the results they generate—the so-called “black box”. People are also often not aware that AI is being used in a way that affects them and their rights. These factors further increase the likelihood of harm. Because of the scale and speed of AI use, when these harms occur, they may happen at a huge scale and very quickly.

These risks are particularly acute for groups that are already minoritised, such as Black and Minority Ethnic people. We focus on the real damage AI systems may do to people’s rights to equality and non-discrimination, to privacy and data protection, and to the right to an effective remedy when people are harmed. The government must act to protect these fundamental rights.

We heard about the human rights impact of AI used to create deepfake sexualised images of women and girls; to profile prisoners in ways which disproportionately affect Black and Minority Ethnic people; to flag up workers for disciplinary action without reasonable cause; and to scan and recognise people’s faces in public places without their consent. Many more uses are being created as technology develops.

There are many laws and regulations that may already apply to some AI systems, but overall the legal landscape is patchy and confused. There are many regulators who are charged with tackling some AI harms, but no single body co-ordinates regulation of AI. This leaves gaps which mean people will be affected by AI harms, but will not be able to get redress.

There is also far too much freedom for the large and powerful technology companies who develop AI systems to pass on liability to those who deploy them. These deployers are often less powerful, have less access to resources, and are not in the best position to identify risks or prevent harm occurring. The law does not target those who actually create and shape the systems. Responsibility to prevent harm should sit with those who are best able to do so.

We call on the government to take immediate action. It must bring in a dedicated AI Bill, and set up a new regulator, to create tailored, effective protection for human rights in the UK. The most dangerous uses of AI should be banned, and others should be regulated in a principled and risk-based way, with strong sanctions for companies and organisations who damage human rights through their use of AI systems. None of this need compromise the use of AI to help generate economic growth, where it can be done safely. As one witness told us, “The only growth worth having is one that protects human rights.”

Introduction....

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