llms2 articles
The Tokenpocalypse Is Here, and a Neanderthal Saw It Coming
The article argues that AI's enormous and growing costs are creating serious economic strain, as demonstrated by quirky cost-cutting measures like "Caveman" — a tool that strips Claude's output down to primitive language to reduce token usage. The author draws parallels to historical technology investment bubbles (canals, railways, electrification), warning that AI's voracious consumption of capital, energy, and resources is distorting broader tech and memory markets without yet delivering sustainable profits. Using Douglas Adams' "Shoe Event Horizon" as a metaphor, the piece concludes that AI companies are in a race to prove profitability before investor confidence collapses, with no clear end in sight.
Sam Altman: A Generation of AI Researchers Were Wrong About Scaling, and They Knew It
OpenAI CEO Sam Altman argues that a generation of AI researchers held the field back by being overly confident that scaling large language models (LLMs) would not work, and he dismisses critics like Yann LeCun who call LLMs a dead end. Altman points to evidence such as an OpenAI model disproving a long-standing mathematical conjecture as proof that LLMs can generate new knowledge and have surpassed human intelligence in some areas. However, he acknowledges that LLMs still underperform humans on very long-horizon tasks requiring high-level judgment.