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Eugene Yan shares insights on LLM system building and AI engineering trends

By PulseAugur Editorial · [2 sources] ·

Eugene Yan presented key learnings from building with Large Language Models (LLMs) at the AI Engineer World's Fair 2024. The keynote, co-authored with others, focused on practical aspects of LLM system development, including evaluations, Retrieval-Augmented Generation, and guardrails. Yan also discussed challenges in consistently evaluating LLMs, citing concerns raised by researchers at OpenAI, Anthropic, and others regarding benchmark reliability and task relevance. AI

RANK_REASON The content is a presentation and reflection on practical LLM engineering, drawing from prior writings and community feedback, rather than a new model release or significant industry event.

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Eugene Yan shares insights on LLM system building and AI engineering trends

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The content is a presentation and reflection on practical LLM engineering, drawing from prior writings and community feedback, rather than a new model release or significant industry event.
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COVERAGE [2]

  1. Eugene Yan TIER_1 English(EN) ·

    AI Engineer 2024 Keynote - What We Learned from a Year of LLMs

    Special double-feature closing keynote from the 6 authors of the hit O'Reilly article on Applied LLMs.

  2. Eugene Yan TIER_1 English(EN) ·

    AI Engineer 2023 Keynote - Building Blocks for LLM Systems

    Evals, retrieval-augmented generation, guardrails, and collecting feedback; all that good stuff.

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