Subtitle: Maybe we should (re)assess the case for relatively fast progress after the GPT-5 release..

Around the early o3 announcement (and maybe somewhat before that?), I felt like there were some reasonably compelling arguments for putting a decent amount of weight on relatively fast AI progress in 2025 (and maybe in 2026):

• Maybe AI companies will be able to rapidly scale up RL further because RL compute is still pretty low (so there is a bunch of overhang here); this could cause fast progress if the companies can effectively directly RL on useful stuff or RL transfers well even from more arbitrary tasks (e.g. competition programming)

• Maybe OpenAI hasn't really tried hard to scale up RL on agentic software engineering and has instead focused on scaling up single turn RL. So, when people (either OpenAI themselves or other people like Anthropic) scale up RL on [...]

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Narrated by TYPE III AUDIO.