What is the biggest technical limitation of LLMs?

Most answers highlight challenges with context limitations and uncertainty, while others point to compute constraints and the lack of consequence awareness as significant technical hurdles.

5 answers

Answers

  • ali dasdan

    Visiting Research Scientist · New York University

    Limited Context Window

    Ali Dasdan says the limited context window is the problem: with too much context the model doesn't know what to focus on and may ignore the middle part.

    MIT Sloan Management Review · Watch on YouTube

  • Ali Ansari

    Founder & CEO · Micro1

    Lack of Consequence Awareness

    Ali Ansari points to a lack of innate sense of consequence, saying models can't fundamentally learn what they should from the consequences humans induce.

    Antler Global · Watch on YouTube

  • Richard Socher

    CEO · Recursive

    Compute Constraints

    Richard Socher says compute is the biggest constraint, as companies will have to decide how much compute to give to solving different problems.

    The MAD Podcast with Matt Turck · Watch on YouTube

  • Itamar Friedman

    Co-Founder & CEO · Qodo

    Context Fragmentation

    Itamar Friedman says the key issue is context: given the right context, models can already reason well about code issues, but without it even the best model gives generic feedback like asking about error handling, and he notes context is currently spread across agents, cloud and skills MD files with differing standards.

    AI Engineer · Watch on YouTube

  • Ruchir Puri

    Chief Scientist · IBM Research

    Modeling Uncertainty

    Ruchir Puri identifies modeling uncertainty as one of two fundamental issues, saying these models are still learning to model uncertainty and always tell you an answer rather than say “I don’t know.”

    The Deep View: Conversations · The Deep View: Conversations · Listen at 11:22

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