3 ms·
Ask HN: When do you think LLM capacity will reach its ceiling?
- murzynalbinos 3mo agoIMO we might not hit a hard ceiling on capacity, but we will likely hit a wall with data quality
- vincenthsin 3mo agoAs human-generated nutritional data runs dry, LLMs will end up eating their own garbage ?
- murzynalbinos 3mo agoYeah, pretty much. Once the good human data runs out and models start training on each other’s output, quality drops fast.
- vincenthsin 3mo agoEven worse, it makes it difficult to distinguish between real and fake data.
- ozereray1 3mo ago[flagged]
- vincenthsin 3mo agoSorry,I mean capability limits.
- vuggamie 3mo agoWhen do you think { compiler | http | von Neumann architecture } capability will reach its ceiling? Unless replaced by something far more capable, refinements and incremental improvements will continue to be applied to LLMs. They will become less expensive and more specialized. Machine learning and neural networks are part of the software stack. LLMs will continue to grow and improve for the foreseeable future.
- vincenthsin 3mo ago[dead]
- samuelknight 3mo agoAI is the latest downstream consequence of the 15 order of magnitude increase in global digital compute since 1946. If compute increases into the foreseeable future; so too will the capability of AI.