The stock market had its worst day since April 2025, led by the companies building AI, and then most of it came back. Also this week: Anthropic’s new AI and the price it just set for its IPO, an AI that found 948 holes in Linux, and Google switching off AI for school students.
The big picture
On Thursday, November 5, the stocks behind the AI boom pulled the whole market down. The S&P 500, the index most retirement funds follow, fell 4.4%, its biggest one-day drop since April 2025. The tech-heavy Nasdaq fell 5.5%. Reuters reports that the 100 biggest companies on the Nasdaq lost about $2.5 trillion in value in a single day. Spread across everyone in the US, that’s roughly $7,400 each.
The companies that make AI’s chips and run its data centers fell hardest. AMD dropped 17.3%, CoreWeave, which rents out AI computing power, fell 9.8%, and Nvidia, whose chips power most AI, fell 9.3%.
We covered a smaller drop in Issue #14, when investors flinched at Big Tech’s building bill. This one was more than twice as deep, and the people who watch markets for a living pointed to a different worry: that building may slow. UBS, the Swiss bank, estimates about 30% of the new US data-center capacity expected in 2028 could be at risk from construction pauses. Qualcomm, which makes phone chips, also gave a disappointing forecast. "The market’s moving from the promise of AI to the price of AI," said Ted Parkhill of Incline Investment Management.
Then most of it came back. After a strong Monday, the S&P 500 closed November 9 less than half a percent below where it stood on October 30. Ed Yardeni, a longtime Wall Street strategist, said he didn’t think the AI bubble was bursting, calling it "an AI bubble losing some air very, very rapidly."
So what: If you have a 401(k) or an index fund, about $26 of every $100 in an S&P 500 fund now sits in six companies betting heavily on AI. That’s why a bad day for AI is now a bad day for ordinary savers. A week like this is a reason to know what you own, not a signal to sell. Nobody, including us, knows whether this was a wobble or the start of something bigger.
Sources: AP · Reuters · CNBC · NBC News · CNBC (Monday) · State Street
What’s new
Anthropic released a faster, cheaper model
On November 9 Anthropic, the maker of Claude, released Claude Fable 5.2, the newest version of its top public model. The company says it answers up to 30% faster than the last version, and businesses pay $8 for every million tokens they feed in (a token is about three-quarters of a word). Fortune reports that’s cheaper than OpenAI’s top model, GPT-6 Astra, at $10. People on paid Claude plans such as Pro and Team can use it now, within usage limits.
Anthropic’s own tests put Fable 5.2 ahead of OpenAI’s and Google’s best on most coding tasks, though Google’s Gemini 4 Carbon still beat it on one test of routine office automation. The headline claim is about maths: Anthropic says 1,000 copies of the AI working together turned the proof of Fermat’s Last Theorem, a famous problem solved by a human in the 1990s, into a form a computer can check, in 30 hours. An earlier, unreleased research version of Claude took 11 days.
Meta also released Muse Ember, a small, very cheap model built for simple jobs done at huge volume.
So what: The price war matters more than the scoreboard. When the top AI gets cheaper every few weeks, more of the apps you already use will quietly start running on it. Treat the maths claim with care: checking a proof that already exists is impressive engineering, but it isn’t new mathematics, and outside testers did not review Anthropic’s announcement.
Sources: Anthropic · Fortune · TechCrunch (Meta)
OpenAI’s security model found 948 Linux flaws
Linux runs most of the world’s web servers. OpenAI says a special security version of its AI, GPT-6 Cyber, searched Linux for flaws that would let an attacker take full control of a machine, and found 948 of them in one run that would have cost about $1.2 million at OpenAI’s prices, roughly $1,300 per flaw. Ten days in, 61 had been fixed and 43 more had fixes waiting.
In July, an earlier model found 166. OpenAI is giving GPT-6 Cyber only to approved security teams.
So what: This is the double edge of AI in security. The same tool that finds holes for defenders could find them for attackers, which is why access is restricted. For you, the practical step hasn’t changed: install updates when your devices ask, because fixes like these arrive that way.
Google will turn off AI for K-12 students by default
On November 3 Google said its AI tools will be "entirely off" for student accounts from kindergarten through 12th grade until school administrators choose to switch them on. Google says it will give schools details "in the coming months," before the change rolls out. Google Search is on the list too, so it will also be off for students until the school switches it on.
So what: If your child has a school Google account, whether they can use Gemini will now be the school’s decision, not Google’s default. It’s a good question for the next parent night: has the school turned it on, and what are the rules?
Sources: Google
Apple starts selling extra AI usage
Apple’s Creator Studio apps, starting with Logic Pro, include a monthly allowance of AI features. Hit the limit and you can now buy a one-time $49.99 "intelligence usage pack," 9to5Mac reports. Apple’s support page says unused usage rolls over for up to 12 months and the packs can’t be shared with family.
So what: This is a sign of where AI pricing is heading: a monthly allowance, then a top-up, like phone data. Apple hasn’t said how much use a pack buys. If metered AI spreads to the apps you use, check the allowance before you subscribe.
Science & medicine
Chatbots pointed patients to stem-cell clinics
Researchers at Simon Fraser University in Canada asked six popular chatbots, including ChatGPT, Gemini, Claude and Grok, 540 questions about stem-cell treatments for Alzheimer’s, autism and cerebral palsy, posing as patients in five cities. The chatbots cited about 5,000 links. Nearly a quarter of them, 23.4%, led to businesses selling treatments, not to health agencies or hospitals.
Some went further than the question. Of the links to businesses, 17.3% pointed to clinics offering a behavioural therapy for autism, not stem cells, which the researchers never asked about. "There’s a big difference between Health Canada and a business that is trying to sell you a product," said Jeremy Snyder, the study’s lead author.
So what: When you ask a chatbot a health question, look at where its links go before you trust the answer. A clinic’s website is an advert. Stem-cell treatments for these conditions are largely unproven, and they’re exactly where sellers look for worried families.
Sources: Simon Fraser University · CTV News
AI drafts cut heart-scan reporting time
At the American Heart Association’s meeting on November 9, Kaiser Permanente researchers reported a trial of 1,200 heart ultrasounds. With an AI draft, cardiologists took 4.6 minutes to finish a report instead of 8.5, and AI drafts needed big changes about as often as human ones. The results are early and not yet peer-reviewed.
So what: Heart specialists are scarce, so faster reports could mean shorter waits for results. A cardiologist still signs off every one. "AI cannot, however, replace the human team," said Keane K. Lee, one of the study’s senior authors.
Sources: Medical Xpress (AHA release)
What people are arguing about
Is AI speeding up its own progress?
For years, some in the AI world have argued that one day AI would start improving itself, and progress would run away. On November 5 METR, an independent group that tests AI, published the most careful outside measurement yet. After eleven weeks working with Anthropic’s data, it estimates the company is improving its AI about 1.9 times as fast as it did in 2024 and 2025, and that AI itself accounts for most of the speed-up.
METR is careful about how sure it is. Its range runs from 1.5 to 2.8 times, and it says it "would not be surprised if the true acceleration was closer to 1.3x or 3x." Anthropic redacted most of the evidence METR found most useful, so readers have to take METR’s judgment on trust. Measured across all the leading AI companies, the speed-up is smaller: about 1.4 times.
So what: Skeptics say a company with an IPO coming has every reason to look fast. Supporters say this is an outside group with access no one else has had. Either way, it’s worth watching. If the pace you plan your job around is itself speeding up, the gap between announcements will keep shrinking, and that’s the bigger story behind this week’s new models.
Sources: METR
Follow the money
Anthropic sets a price range for its IPO
Last week we covered Anthropic’s filing to sell shares on the Nasdaq. This week the price became the problem. On November 6 Reuters reported that potential investors doubted the company could start its planned roadshow, the tour where a company pitches its shares to big investors, in the wake of the sell-off. Some saw a value of $1.5 trillion as the high end, after earlier talk of up to $2 trillion.
Then, early on November 10, Anthropic filed a price range with the SEC: $70 to $78 a share for 825 million shares, about $64 billion at the top of the range, plus $26 billion more from a private sale alongside it. By our math, counting the shares the filing says will exist afterward, that values Anthropic at roughly $1 trillion at the top of the range.
So what: An IPO is when the public, not just private investors, gets to put a price on a company. The range Anthropic filed puts it near $1 trillion, well below the $2 trillion once talked about. Where the shares actually price, and trade on day one, will be a direct read on how much faith big money still has in AI after last week.
Business spending on AI grew about fivefold
Menlo Ventures, a venture capital firm, surveyed about 400 US business decision-makers and estimates that company spending on AI went from $33 billion last year to $177 billion this year. On average, companies spent 4.7 times what they spent last year, after budgeting for 1.9 times.
Most of that money went to two companies. One caveat up front: Menlo is an investor in Anthropic.
So what: The report says 55% of this money is new spending, not cash moved from existing software or salaries. So far, companies are adding AI on top rather than paying for it by cutting staff. It also explains why investors keep asking when all this spending turns into profit.
Sources: Menlo Ventures
What to watch next
Monday, Nov 16: The Fed’s hearing on AI, productivity and jobs, with outside voices invited.
Tuesday, Nov 17: Nvidia, the company whose chips power most AI, reports earnings after the market closes. It’s the first big test since last week’s sell-off.
Around Nov 19-20: Anthropic’s expected first day of trading on the Nasdaq, at $70 to $78 a share if the range it filed holds.
Sources: Fed press conference · Nvidia · Crypto Briefing (citing WSJ)
Human Terms is written with help from Claude, made by Anthropic. Anthropic appears four times in this issue: its new model, an outside audit of its progress, its IPO, and its share of business AI spending. The model claims are Anthropic’s own, the audit is by an independent group, and the spending report comes from one of its investors, which we say where it runs.
One question for you: did last week’s sell-off make you look at your retirement account, and what did you decide? Hit reply and tell me. I read every one.
Until next time,
Robert
Human Terms
Read past issues at humanterms.ai, or forward this to a friend.