The model can say anything. The schema decides what becomes a fact.
Same question, same answer, every time. That is not a bigger model. That is structure.
mmvfirm.com
A large open model now runs on two desktop computers. Close, sure. But the answer was never a bigger box. It's organized data and deterministic retrieval, so a small model has nothing to make up. We've been saying it since 2022. Small models were never the problem. Messy data was.
mmvfirm.com
Scality says its tests restored a 14K-token context from shared storage 14x faster than recomputing it. That's a vendor claim. If it holds, on-prem inference is mostly a memory and storage problem. Plan the cache before you buy the GPUs.
Open-weight models went from about 31% of token traffic in July to roughly 78% by September, as per Intel info. A model you can download is a model you can run, and that is truly yours. As a society, we should be moving toward democratizing AI.
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