2026-02-02 20:58 UTC
@iurii@mastodon.world @krystyna@toad.social @nixCraft@mastodon.social
Problem is, these giants also can't make a profit with it.
Hardly anyone actually wants to pay anything for AI, and even less are willing to pay the real price.
All the expensive hardware will be obsolete in two or three years and to this day I have not seen a single actually "disruptive" and functional use case for LLMs. Small improvements here and there, sure, but providing free coffee would have produced the same productivity boost.
Replies (1)
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@iurii@mastodon.world 2026-02-03 03:38
@AdmSnackbar@mastodon.social @krystyna@toad.social @nixCraft@mastodon.social you may be right. One disruptive case for LLM that I see is a shift away from LLM to less hungry models. Speech to text model can be connected to intent recognition to summarisation, etc. Small, specialised models, also domain specific, for DNA, semantic video compression, etc. LLMs become enabler of these specialised models. Also LLMs could train LLM much cheaper. Basically cost efficiency gap could be closed.