Weaviate Podcast #148: MIT's Jacob X. Li proposes 'Machine Studying' to redefine continual learning
eshorten300 · x · 2026-11-02
Weaviate Podcast episode 148 features MIT CSAIL PhD student Jacob X. Li discussing his 'Machine Studying' framing. Continual learning is widely seen as AI's biggest opportunity, but the author argues it's poorly defined: classic CL asks how to learn tasks B and C without forgetting A (tasks assumed given), while Machine Studying asks how an agent learns from a corpus — codebases, drug-discovery papers, system logs — with no task distribution at all. Like a student prepping for unseen exam questions, an always-on agent builds deep understanding ahead of time instead of relying purely on inference-time compute, with 'expertise' defined as efficiently spending inference-time compute thanks to prior preparation.
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