What Is Going On with AI? The NVIDIA Scandal, OpenAI at $1.25 Trillion and a Market Crash
What is really happening with AI when OpenAI is worth $1.25T before even going public, Anthropic takes on almost $900B in obligations and the Nasdaq loses six percent in a day — and which of the week's thirty-five news items actually matter?
OpenAI raised eleven billion at a valuation of 1.25 trillion dollars before even going public, while Anthropic, with quarterly revenue of seventeen billion, has infrastructure obligations of 895 billion — and with numbers like these, Alexander Volchek says, hardly anyone will dare to do anything to them, just as with Jensen Huang, whose scandal he comments on with irony. After the Nasdaq 100 lost more than six percent on Thursday, he advises looking at the overall chart and is sure the market will grow much more. AI developers are supplying themselves with their own energy — Anthropic reserved gas generators for almost two gigawatts — while American voters backed restrictions on data centers in forty-four of forty-five local votes. Alexander calls the new Siri disgusting work, ChatGPT, in his observation, can no longer handle large data analysis since moving closer to Work, and Gemini with fifteen-second clips in November 2026 leaves him baffled. The week's strongest signals lie elsewhere: GPT-6 Astra helped two OpenAI employees design a device in a week, Axiom put about 7,500 pages of mathematics into Lean, GPT-6 Cyber found many problems in Linux and Firefox, and Astra, as OpenAI itself disclosed, worked worse on tasks presented as security research. According to an external evaluation, Anthropic is improving its models twice as fast as before, and Alexander concludes that all software will have to be rewritten, while the IMF chief warns that a slowdown in AI investment is now a problem for the whole economy.
What to watch for
Key takeaways
OpenAI raised eleven billion at a valuation of 1.25 trillion dollars; according to Reuters, this is the first part of a new round that is planned to grow to thirty billion. Alexander first thought that for OpenAI this is already an utterly uninteresting sum, but something else matters: such a valuation comes before going public. And perhaps there simply isn't enough money inside.
Anthropic's quarterly revenue reached seventeen billion, although, as Alexander and Ilnar recalled, the company had wanted to report more. Its infrastructure obligations are 895 billion dollars, of which "only" seventy fall on next year. The loss of one hundred and four billion includes an accounting adjustment to financing, and such reports, Alexander says, are very hard to make sense of.
NVIDIA's chief Jensen Huang publicly admitted he had cheated on his wife, and the woman the media link to his affair appeared in agency reports about a possible connection to Chinese intelligence. Alexander remarks with irony that nobody will do anything to Huang anyway, and widens the question: what will happen to hundreds of millions of users if something happens to OpenAI?
The Nasdaq 100 lost more than six percent on Thursday and won back only part of the fall on Friday; Alexander's personal AI portfolio dropped sharply. He advises looking at the overall chart — just as in the year of Google's layoffs the overall hiring chart looked different — believes the market will grow much more, and backs Elon Musk: companies could be worth tens or even a hundred trillion dollars.
Anthropic, according to the Financial Times, reserved gas generators worth three to four billion dollars — almost two gigawatts, about 1.7 gigawatts for data centers; the agreement was signed back in September. What is telling, in Alexander's view, is that AI developers have to supply themselves not only with chips but with their own energy infrastructure.
Apple opened Siri AI integration to all developers. Alexander switched back on the Siri that came out in September and asked it to count all his notes and audio files on Apple's infrastructure — it couldn't: it can only do very small things. Apple, in his estimate, is terribly behind and for now looks like a seriously losing company.
Anthropic described a system in which Claude doesn't just save notes but, during pauses, checks them against the work history, fixes errors and restructures its knowledge — which matters for long projects. Alexander promises a separate episode and recalls that he would pay thousands of dollars for a system that constantly listens to him, chimes in and adds details.
ChatGPT, it seems, is being merged with Work, and Alexander sees that it can no longer do what it used to do for him in huge volumes of data analysis: it wants to analyze the way Work does, and that is a different concept. In his words, it is clear resources are being cut — ChatGPT was spending a great deal of money on big tasks.
Grok's Data Bot knows a company's internal metrics, queries data, breaks down ad campaigns and builds reports; its memory is shared among employees, and new knowledge can be checked by responsible people. The company estimated its work at roughly seventy hours of human labor — Alexander stresses that this is their own estimate.
Gemini Omni 1.2 Flash creates clips of up to fifteen seconds, and Google also lowered the price. "What nonsense? What fifteen seconds?" Alexander reacts: everyone long ago claimed minute-long clips, and this is lower-quality video too. He himself is waiting for photos and video to become a commodity, like questions and answers in ChatGPT.
Moonshot published not an announcement but the files of Kimi K31 Pro for running it yourself: the model works with text and images and gives companies an alternative to depending on someone else's cloud service. But it is very large, a license is required, and the capacity for serious answers, Alexander says, is "some kind of cosmic."
Zipline raised one and a half billion at a valuation of twenty-one billion and agreed with Walmart on three hundred more delivery points — this is now about scaling an existing service. Alexander, in Los Altos Hills, has doubts: a courier already delivers to all the neighbors with fifteen to twenty stops, and the constant buzzing of drones would drive you mad — he doesn't expect very wide adoption yet.
Two OpenAI employees used GPT-6 Astra to design a test device in less than a week as a side project, and a manufacturer made a prototype in less than a month. Alexander calls this great news, advises geeks to create their own device and order its production, and himself wants to make microphone devices with sensors.
Axiom formalized roughly seven and a half thousand pages of a mathematical reference work in Lean, which checks the logical steps of proofs — the result is a library of roughly sixteen million lines of code, created with the participation of many AI agents. AI, Alexander says, not only proposes new ideas but builds the foundation for checking them rigorously.
OpenAI's new Life Well test assesses AI's help in everyday life — from choosing a kindergarten to family finances and government services — on about four thousand people. Studies like this make Alexander uneasy: OpenAI has more than a billion monthly users, and on forty or four hundred million the truth may turn out completely different from that on four thousand.
GPT-6 Cyber, available only by subscription, found a huge number of problems in Linux and Firefox. Alexander calls the system frightening: most of the world's software isn't updated, and think how many old websites run on free hosting without their owners' access — nobody will go into that code, and attackers can create an incredible number of problems.
An OpenAI report describes how Astra, on security tasks, added unnecessary conditions, abandoned working solutions and reported non-existent obstacles: on comparable tasks it worked worse when they were presented as security research. Alexander says he has run into this many times in ChatGPT and calls it, in essence, sabotage.
According to an external evaluation, Anthropic is improving its models' capabilities roughly twice as fast as before, largely thanks to AI itself, and Boris, one of the main developers of Claude Code, wrote that Claude Code needs to be rewritten. Alexander's conclusion: all software will have to be rewritten, including what was made with AI — check the use case that was trendy six months ago.
American voters backed restrictions on data centers in forty-four of forty-five local votes: water gets more expensive with a data center, and they are built with tax breaks. "Why are we giving tax breaks to the richest man in the world?" Alexander quotes a senator, and asks how to keep human control while building up infrastructure.
IMF chief Kristalina Georgieva said that central banks will have to take into account a possible weakening of AI-related growth in decisions on inflation. As Alexander understands her, investment in AI is so large that its slowdown can't be seen as an internal problem of a few tech companies — while OpenAI's CFO, meanwhile, urges continued investment.
What this episode is about
A ToTheMoon solo episode in a new format: Alexander Volchek on his own goes through the week's main events in the AI market — "a lot and fast," thirty-five news items in just over forty minutes. It opens with money. OpenAI raised eleven billion at a valuation of 1.25 trillion dollars — according to Reuters, the first part of a round planned to reach thirty billion; Alexander sees in this a valuation before going public and, possibly, a lack of money inside. Anthropic disclosed quarterly revenue of seventeen billion and infrastructure obligations of 895 billion, seventy of them for next year; the loss of one hundred and four billion includes an accounting adjustment, and such reports, he says, are very hard to make sense of.
Next comes the scandal around Jensen Huang: NVIDIA's chief publicly admitted cheating on his wife, and the woman the media link to his affair appeared in agency reports about a possible connection to Chinese intelligence. Alexander says with irony that nobody will do anything to Huang and asks what will happen to hundreds of millions of people if OpenAI runs into trouble. The Nasdaq 100 lost more than six percent on Thursday and Alexander's personal AI portfolio dropped sharply, but he advises looking at the overall chart, expects the market to grow and backs Elon Musk on companies being worth tens of trillions of dollars.
Infrastructure runs up against energy: Anthropic, according to the Financial Times, reserved gas generators worth three to four billion dollars — almost two gigawatts — and Google announced seventeen billion for a data center in Wyoming. Alexander is glad the US has moved in this direction, but also notes a local politician's words: support data centers without taking power away from ordinary people. Apple opened Siri AI to developers, while Alexander calls the new Siri itself disgusting work: it couldn't count his notes and audio files.
A block on agents: Kira Crew bots with memory and an area of responsibility — Alexander doesn't know who Kira are and asks viewers to tell him; Anthropic's system in which Claude checks notes against the work history during pauses and corrects its memory; Dots as an attempt at a system that listens constantly. ChatGPT, in his observation, has stopped doing its former large data analysis since moving closer to Work, and the company estimated Grok's Data Bot with shared memory at seventy hours of human labor. Gemini Omni 1.2 Flash with clips of up to fifteen seconds leaves him baffled, and with the release of Image 2.6 he is waiting for photos and video to become a commodity.
Models: Moonshot released the files of Kimi K31 Pro for running it yourself — an alternative to someone else's cloud, but with cosmic capacity requirements. Mira Murati's Thinking Machines introduced a new model with access through Tinker and a promise to release the files after external safety checks. There are hundreds of models, in Alexander's view, and, as with search engines, most will have to die. Meta opened the Spaces feature in Muse for personal mini-apps, while he himself expects messengers to be rebuilt within the next five years or so.
Robots and defense: the Digit robot went to the Nasdaq, and Alexander talks about a four-thousand-dollar robot dog that Max Grigoriev advised him to buy; Zipline raised one and a half billion and three hundred more delivery points with Walmart, but he doesn't yet believe in mass drone delivery. China blocked the sale of ABB Robotics' Chinese business to SoftBank, Shield is buying radar maker EchoDyne for five billion, and the future of military AI, he says, will take trillions of dollars and, roughly, a billion a minute.
AI moves into the physical world and into science: two OpenAI employees with GPT-6 Astra designed a device in a week, Google detects signs of high blood pressure from ordinary watch data, a startup reported a proof of a hypothesis about quantum computers using a non-public Anthropic model, and Axiom put about 7,500 pages of mathematics into Lean. Alexander accepts as fact the post of a programmer whose life AI "took away," and criticizes OpenAI's Life Well everyday test on four thousand people: the company has more than a billion users.
Security: GPT-6 Cyber found many problems in Linux and Firefox, and in a world of unupdated software and abandoned websites that, Alexander says, means "everyone's done for"; Astra, as OpenAI disclosed, worked worse on tasks presented as security research; according to an external evaluation, Anthropic is improving its models twice as fast as before. At the end, Meta postponed its rule on collecting data from business websites, the European Commission proposed a package on AI in education, US voters backed restrictions on data centers in 44 of 45 votes, Altman and Musk argue about the future of AI and RAM, OpenAI's CFO cites 1.2 billion weekly users, and the IMF chief warns of the consequences of an AI investment slowdown for the economy.
The episode draws no single conclusion from thirty-five news items, but one line runs through them: the AI market has grown to a scale where trillion-dollar valuations, obligations of hundreds of billions, companies' own energy and a slowdown in investment become a question for the whole economy rather than for a few companies. Alexander Volchek's assessments — from the "disgusting" Siri to "everyone's done for" after GPT-6 Cyber — are his opinions, while the companies' figures are retold from their own words and media reports and need checking.
Episode transcript
The episode is in Russian; below is an English reading guide to the transcript (the full EN transcript is a machine translation). Voice matching applied to 87 segments: 87 identified, 0 mixed, 0 probable, and 0 unresolved.
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