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Shanu Mathew
@ShanuMathew93
Energy Abundance, AI Power & Data Centers, NBA, & Rap posts. Background in equity & credit markets, startups, & IB. Personal views NOT employers. NOT advice.
Joined June 2019
1.9K Following    35.2K Followers
This got me thinking as lines will eventually blur btwn what gets pushed into deterministic code as rules vs. probabilistic agents on well defined/repeatable tasks extremely fine tuned for situations with varying degrees of uncertainty, etc. the decision tree will look interesting as organiations mature across this boundary -->Explicit rules can move into code vs. -->Recurring judgments on messy inputs may stay with small, specialized models vs. --> Broader agents make sense when the steps themselves vary.
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totally agree for "general purpose" models. The valid exception would be the cost comparison of a general purpose frontier model to a smaller model fine tuned for a narrow use case. The latter can still yield material cost savings, for example in the Crowdstrike data below, but only if you have a stable and sufficiently scaled use case to justify the R&D investment (not one time but ongoing to keep up w/ the frontier).
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