@jacobli99: Continual learning is widely discussed right now, but mostly as improving on the job or avoiding catastrophic forgettin…
Summary
Jacob Li introduces the concept of 'Machine Studying' as a distinct and urgent form of continual learning, where AI systems must develop expertise in a new domain from a corpus of documents alone.
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Cached at: 06/17/26, 09:59 PM
Continual learning is widely discussed right now, but mostly as improving on the job or avoiding catastrophic forgetting. But it has a different, difficult, and already urgent form:
Given nothing but a corpus of documents, how should AI systems develop expertise in a new, unfamiliar domain? We call this problem Machine Studying.
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@jacobli99: To compare procedures for machine studying, we start by defining expertise. The corpus is always available at test time…
Jacob Li introduces 'Machine Studying' as a new problem in continual learning: how AI systems develop expertise in an unfamiliar domain given only a corpus of documents, distinct from avoiding catastrophic forgetting.
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Jacob X. Li discusses the need for AI systems to develop expertise autonomously from a corpus of documents, framing this as a challenging form of continual learning.
@DSPyOSS: a crisper operationalization of continual learning that matches problems that are inaccurately treated as "RAG" or "RL"…
Introduces 'Machine Studying' as a new formulation of continual learning where AI systems autonomously develop expertise from a corpus, and presents StudyBench for evaluation.
@lateinteraction: putting the link here for those that want to jump right into the long form: https://jacobxli.com/blog/2026/machine-stud…
Introduces 'Machine Studying' as a problem where AI agents must autonomously develop expertise from a corpus, beyond RAG or long-context, and presents the StudyBench benchmark for evaluation.
@lateinteraction: Been extremely excited about this work by @jacobli99! We're disappointed in the current ways our agents develop experti…
A discussion on the challenge of enabling AI systems to develop deep expertise from documents, akin to humans learning from textbooks, highlighting a form of continual learning.