AI scaling myths - by Arvind Narayanan and Sayash Kapoor
Scaling will run out. The question is when.| www.aisnakeoil.com
Scaling will run out. The question is when.| www.aisnakeoil.com
AGI by 2027 is strikingly plausible. GPT-2 to GPT-4 took us from ~preschooler to ~smart high-schooler abilities in 4 years. Tracing trendlines in compute (~0.5 orders of magnitude or OOMs/year), algorithmic efficiencies (~0.5 OOMs/year), and “unhobbling” gains (from chatbot to agent), we should expect another preschooler-to-high-schooler-sized qualitative jump by 2027. Look. The models, they just| SITUATIONAL AWARENESS
The conventional wisdom, well captured recently by Ethan Mollick, is that LLMs are advancing exponentially. A few days ago, in very popular blog post, Mollick claimed that “the current best estimates of the rate of improvement in Large Language models show capabilities doubling every 5 to 14 months”:| garymarcus.substack.com
