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Large Language ModelsLobsters AIPublished: Oct 8, 2026, 01:00 JST

Lobste.rs user seeks AI/ML roadmap after 2018-19 hibernation

Lobste.rs user seeks AI/ML roadmap after 2018-19 hibernation

3 Key Points

  1. What happened

    A Lobste.rs user who has been on hibernation since 2018-19 asked the community to recommend books, MOOC courses, and YouTube channels for getting started with current AI/ML progress.

  2. Why it matters

    The user is seeking a structured roadmap to navigate the domain's progress since 2018-19.

  3. What to watch

    Whether the community recommends a dedicated path for LLMs versus other ML models deployed pre-2022/21.

WHO IT HITSThis request is aimed at the Lobste.rs community of developers and technologists, who may respond with curated learning paths for someone returning to AI/ML after a multi-year gap.

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Context & Analysis

The request comes from someone who describes being on hibernation since the 2018-19 time frame, meaning they missed the period in which large language models moved into wide use. They are not asking for a single answer but for a structure — something like TeachYourselfCS — that would let them navigate the field's accumulated knowledge rather than piece it together from scattered sources. They also raise a practical distinction: whether understanding LLMs requires a different approach from the ML models that were already in large-scale deployment before 2022/21. That question suggests the user suspects the recent wave may not be fully covered by older learning paths. How useful the community's replies turn out to be may hinge on whether they address that split directly, rather than offering a single generic list.

FAQ
What kind of resources is the user asking for?
The user is asking for books, MOOC courses, and YouTube channels to get started with current AI/ML progress.
What specific type of resource does the user hope to find?
The user hopes for a resource like TeachYourselfCS that can give structure and a roadmap to navigate the domain's progress and knowledge.
What question does the user ask about different ML models?
The user asks whether different approaches are needed to understand LLMs versus other types of ML models that have been in large-scale deployment since pre-2022/21.

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