From Wafer-Out to First Token: Codifying Supply Chain Expertise with Nemotron and Palantir Foundry
Source
Elizabeth Goodman
Author
Elizabeth Goodman
Date
Why it matters
Shows a concrete recipe for post-training a smaller open model on domain decision logs to beat a much larger general model on a specific operational task, with a governed retrain loop that compounds over time.
Key quotes
“On the development benchmark, the post-trained Lightning model reached 86.7% allocation-decision accuracy”
“On a bounded allocation task, a specialized 30B model can outperform a general-purpose model that is more than an order of magnitude larger.”
“The model never retrains itself in production.”
“This is sovereign AI in practice: proprietary supply-chain data, model weights, and inference all remain inside a single governed environment.”
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