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The End of Moore's Law for AI? Gemini Flash Offers a Warning

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113 points sethkim | 1 comments | 03 Jul 25 17:34 UTC | HN request time: 0.2s | source
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fusionadvocate ◴[03 Jul 25 19:22 UTC] No.44458352[source]▶
What is holding back AI is this business necessity that models must perform everything. Nobody can push for a smaller model that learns a few simple tasks and then build upon that, similar to the best known intelligent machine: the human.

If these corporations had to build a car they would make the largest possible engine, because "MORE ENGINE MORE SPEED", just like they think that bigger models means bigger intelligence, but forget to add steering, or even a chassi.

replies(3): >>44458546 #>>44458573 #>>44458576 #
1. dehugger ◴[03 Jul 25 19:45 UTC] No.44458546[source]▶
I agree. I want to be able to get smaller models which are complete, contained, products which we can run on-prem for our organization.

I'll take a model specialized in web scraping. Give me one trained on generating report and documentation templates (I'd commit felonies for one which could spit out a near-conplete report for SSRS).

Models trained for specific helpdesk tasks ("install a printer", "grant this user access to these services with this permission level").

A model for analyzing network traffic and identifying specific patterns.

None of these things should require titanic models nearing trillions of parameters.