parameter efficient adapters

1 statements across 1 episodes · 0 bullish · 0 bearish · 1 people on the record · first statement Jul 13, 2026 by Dan Biderman · across every show →

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Jul 13, 2026
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Biderman: Personalized AI adapters require hot-swapping millions of endpoints at inference
“And if you truly believe that we can get to the level where we have those kinds of parameter efficient adapters for every person and team, you suddenly think about deployments that involve millions of different endpoints stored in different places that need to…”
Dan Biderman Jul 13, 2026 ▶ 43:43 The AI Memory Problem: Why Long Context Isn’t Enough — Dan Biderman, Engram Co-founder & CEO
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