Zelikman: AI field underinvests in memory due to task-centric training regimes
Eric Zelikman · No Priors Ep. 135 | With Humans& Founder Eric Zelikman · Oct 9, 2025 · at 32:13
Humans& founder Eric Zelikman explains why modern LLMs lack persistent memory capabilities across interactions.
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“I would say that memory is definitely like a feature that has been under, under-invested in by the field. But I would say that it is kind of difficult to invest in memory in this very, like, task-centric regime. Because if you have, like, A bunch of these, like, independent tasks, the amount of information that each of those needs from other things that you've discussed is not all that high. Like, because of the current paradigm, memory doesn't end up being super useful in the training, and so these models are not particularly good at doing it.”
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