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Open challenges in LLM research

Named practitioner synthesis

#198

T3digested
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Practitioner Notes
First seen
2026-07-16 19:08:00
Last seen
2026-07-16 19:08:00

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  • Blog / Newsletter2026-07-16 19:07:19
    Open challenges in LLM research

    <p>[<em><a href="https://www.linkedin.com/posts/chiphuyen_llm-airesearch-generativeai-activity-7097619722363408385-s5Cp">LinkedIn discussion</a>, <a href="https://twitter.com/chipro/status/1691858084824838427">Twitter thread</a></em>]</p> <p>Never before in my life had I seen so many smart people working on the same goal: making LLMs better. After talking to many people working in both industry and academia, I noticed the 10 major research directions that emerged. The first two directions, hallucinations and context learning, are probably the most talked about today. I’m the most excited about numbers 3 (multimodality), 5 (new architecture), and 6 (GPU alternatives).</p> <h2 id="1_reduce_and_measure_hallucinations">1. Reduce and measure hallucinations</h2> <p><a href="https://huyenchip.com/2023/05/02/rlhf.html#rlhf_and_hallucination">Hallucination</a> is a heavily discussed topic already so I’ll be quick. Hallucination happens when an AI model makes stuff up. For many creative use c