Time magazine's doomer covers: 1954 nuclear war 1960 population explosion 1970 ecological collapse 1982 nuclear war 1989 endangered Earth 1992 ozone 1999 Y2K 2001/2006/2007 climate 2005 pandemic 2009 extinction 2013 bees 2019 climate 2020 pandemic 2023 AI extinction 2026 AI tipping point

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution

We already know what a world without work looks like. It's the life of 18th century aristocrats, who concerned themselves with political gossip and petty dramas; of society ladies in the 1980s, who spent their time hosting and volunteering; and Italian-Americans in 1950s Boston, whose status was centered around their peer groups, rather than their jobs. Relational living comes to us naturally, but – argues @clarabcollier – work offers us dignity, structure, and meaning, as evinced by surveys that consistently find that about 85% of Americans are "somewhat" or "completely" satisfied by their jobs. Work gives us an escape from the cliquishness of relational societies: without it, our personal relationships might become even more stifling and transactional.

Checking that a major mathematical proof is correct can take years. Formalization—converting the mathematical reasoning into a form computer proof assistants like Lean can verify—can help. Last month, Claude completed the first formalized proof of Fermat’s Last Theorem, one of the most famous theorems of all time. This was a project experts thought would take many years. It is the largest Lean proof ever written. Fermat’s Last Theorem was first proven in 1995 by Sir Andrew Wiles, more than 350 years after it was conjectured. Our proof, which totals over 13 million lines of code, provides machine verification. More importantly, it proves over 29,000 other theorems that the proof requires, across many areas of math which had never before been formalized. We see this as a major step in the long process of firming up the core of mathematical knowledge, building on work from three centuries of mathematicians and hundreds of contributors to Lean and Mathlib. We are optimistic that AI-assisted verification of mathematical proofs will help reduce the burden of refereeing mathematics in an era where more proofs are being produced than ever before. You can read about the process on our Science Blog: anthropic.com/research/forma… And see the complete proof on GitHub: github.com/anthropics/fermat…

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Last week I posted a new paper with Patrick Norrick: “Terra Incognita: The Economics of a Shrinking World.” We chose the title deliberately. No society in history has experienced the fertility levels now seen in South Korea, China, Thailand, Colombia, Chile, and many other countries. Our knowledge of the causes (and of the economic consequences) remains far more limited than most public discussion acknowledges. Much of what we write is, at best, educated conjecture. The paper also struggles against a space limit. We wrote 20,000 words, far from the 250,000 or so we would need to address some issues in more detail (if I had the time and resources to hide away for a year, I could do that, but not now). That means some ideas are only sketched. Nonetheless, we emphasize several important points. First, fertility has fallen very fast everywhere: rich and poor countries, east and west, north and south, conservative and liberal societies, religious and non-religious societies (with the exception of the Jewish population of Israel; fertility has also collapsed among the Muslim population within the pre-1967 borders), you name it. Even in sub-Saharan Africa we see fast and unprecedented drops in fertility (alas, from a high initial level). Second, and this is really interesting, the fertility collapse has been concentrated in poor and lower-middle-income countries much more than in rich countries. By now, income per capita and fertility are positively correlated within OECD countries. We conjecture this will hold globally in a few decades. Third, and related to the second point, the fertility collapse has been concentrated among poor and lower-middle-income women within countries. In countries such as the U.S., the rich and highly educated now have more children than the poor and less educated. Fourth, we document why we do not understand the data from the U.N. World Population Prospects. See, for example, Tables A.1 and A.2. Fifth, we explain why some proposed mechanisms struggle when confronted with the data. A more subtle point is at work here. Many commentators do not seem to understand the difference between proximate causes and ultimate causes. Yes, births might have gone down because fewer women are in long-run relationships. That is the proximate cause. But you need to explain why fewer women are in long-run relationships (the ultimate cause), and saying that they spend more years in school, to take one example, does not get us very far. Why do they spend more years in school? Once you start down the whole chain of reasoning, things become much harder than they seem. The paper can be found here: sas.upenn.edu/~jesusfv/Demog… Comments always welcome!

New paper: LLMs should give accurate answers. 
Yet we find their answers are often biased to favor their own values and they don’t disclose this in their reasoning. 
E.g. Claude’s answer below favors Anthropic. On other tasks, Gemini & GPT-5.5 show similar biases.

"Anthropic applies that idea of formation to a machine with extraordinary care, and almost never to the people who use it." @Brendan_McCord, in the first piece of our new series on Anthropic's approach to forming Claude and the threat to human autonomy. blog.cosmos-institute.org/p/…

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