AI Developers Grapple with Model Efficiency
12 posts across 11 communities in the last 90 days; 17% from community.openai.com.
“Some specialized models may end solving themselves by helping fit the problem with the appropriate regular algorithms/formulas, which are a million times more efficient. So they are probably less attractive to dump money on. As of currently they still benefit from expressing…”
“For example, I want one model to handle research, another to do deeper reasoning or technical analysis, another to critique the result, and then one main model to combine everything into the final answer. Can this be done directly inside ChatGPT or ChatGPT Work, or do you need…”
“It feels like a zig-zag: you don't want a model that's too dumb to do anything agentic. But once a model is good enough to be agentic, you don't want it to run so slow that iterating takes hours. For me the sweet spot is something like ~500 tps prefill, ~25tps decode. If a model…”
Developers are focused on optimizing AI models for performance and resource usage, particularly in local deployment scenarios. There's a drive to reduce model size and improve efficiency without sacrificing accuracy.
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“For example, I want one model to handle research, another to do deeper reasoning or technical analysis, another to critique the result, and then one main model to combine everything into the final answer. Can this be done directly inside ChatGPT or ChatGPT Work, or…”
Optimizing AI compute before inference
AI Efficiency Mode" for Sustainable AI Usage"
“It feels like a zig-zag: you don't want a model that's too dumb to do anything agentic. But once a model is good enough to be agentic, you don't want it to run so slow that iterating takes hours. For me the sweet spot is something like ~500 tps prefill, ~25tps decode. If a model isn't fast enough to pass that bar on the hardware I have, I'd rather just run something slightly dumber but faster Thoughts? submitted by /u/maddie-lovelace [link] [comments]”
“Some specialized models may end solving themselves by helping fit the problem with the appropriate regular algorithms/formulas, which are a million times more efficient. So they are probably less attractive to dump money on. As of currently they still benefit from expressing lots of patterns that nobody bothered formalizing.”