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"There's a belief that the world's GDP is limited at $100 tn. What's likely to happen is AI is going to cause that $100 tn to become $200 tn, $300 tn, $500 tn. There's no fundamental limit to the size of the GDP." - Nvidia CEO Jensen Huang https://t.co/YxfiYZQFMv https://t.co/ldU2tWmXuh

In its latest research, Anthropic projects 32% US GDP growth by 2030 in extreme AI Scenario Some takeaways: - The extreme scenario assumes AI performs nearly all knowledge-work tasks autonomously and creates essentially no new knowledge tasks for humans, a combination the authors say would likely require recursively self-improving AI adopted rapidly. - US GDP is 32.4% higher in 2030 than without AI, yet total labor income barely changes while capital’s share of GDP rises from about 40% to 54.8%. - The extreme scenario puts knowledge-worker unemployment at 17.9% by 2030, compared with 3.9% for other workers and 11.9% across the economy. - knowledge-worker pay is 11.5% below the no-AI baseline in 2030, while other workers earn 33.6% more and average pay across workers is 9.7% higher. - In its substantial and extreme scenarios, Anthropic explicitly says coders and call service center agents may have to switch into professions such as electrician and nurse because those occupations are less exposed to AI. - Anthropic excludes hyper-capable robots from its model and reports that some external reviewers questioned whether AI-exposed occupations would shrink at all, with others suggesting the extreme scenario is better understood as a thought experiment.

Fable is probably ~2-2.5T parameters, not 10T. Kimi K3 is 2.8T params, trained on maybe 20–30k Blackwell-equivalents. It lands within spitting distance of Fable 5 in terms of capabilities (5, not 5.1). Anthropic has far more compute than Moonshot, better rl environments, better architecture and better optimizers and all of that adds to capability per parameter. So if Fable is only slightly ahead of K3 with this in mind, it's almost certainly a smaller model. GPT-5.5 and 5.6 are smaller still (I'll say more on that later)

Anthropic’s Economics team is sharing a new model of how AI might affect economic growth, jobs, wages, and more by 2030. Explore the scenarios, tell us what you think will happen, and see how your answers compare to more than 10,000 Americans. https://t.co/AvQlEZNxR0

Anthropic’s Economics team is sharing a new model of how AI might affect economic growth, jobs, wages, and more by 2030. Explore the scenarios, tell us what you think will happen, and see how your answers compare to more than 10,000 Americans. https://t.co/AvQlEZNxR0

Sam Altman on how AI token usage is growing at an exponential rate. "6 and a half years ago, the world token leader was an OpenAI employee using about 100,000 tokens a month. And this seemed ludicrous at the time. The worldwide average per capita was, like, zero. Now, the worldwide average of tokens per month, is like 100,000, and the token leader at OpenAI uses something in the hundreds of billions. If that happens again, which I think it probably will, then in another six and a half years, the average person uses, let’s say, 500 billion tokens a month, and the token leader uses a quadrillion or quadrillions of tokens a month. And I think that will just become the expectation." --- He was at YC Startup School 2026, in conversation @garrytan From "Y Combinator" YouTube channel, (full video link in comment)

OpenAI's usage pattern from CFO Sarah Friar's new interview. "Our free users do about seven turns, or seven questions, a day. Our first paid tier does double that, about 15. Our real paid tier, Plus, which is $20, is about 3x, and Pro is about 11x over a free user." Our mission at OpenAI is AGI for the benefit of humanity, not for the benefit of humanity who can pay, or for the benefit of humanity who live in an enterprise" ---- From @theallinpod YouTube channel, (link in comment)

https://t.co/brIhFmbO3q