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Verifiable AI: Proving What Happened Behind the Black Box
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Verifiable AI: Proving What Happened Behind the Black Box

#hackernoon#technology#model#proof#provider
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The receipt you never get

when a server tells you which model answered, how would you know?

Today you would not. An API response has a model field, and that field is a string the provider typed. You cannot see the weights, the quantization, the system prompt, or whether your request was cached, rerouted, or trimmed.

This is more than paranoia. Researchers at UC Berkeley tested it in Are You Getting What You Pay For? , and the results are uncomfortable:

A classifier trained to tell quantized outputs from full-precision ones scored about 50 percent, the same as guessing.

Statistical tests on larger models caught substitution reliably only when around 60 percent of queries were swapped.

With sampling switched off, outputs for the same open model matched across different providers less than 5 percent of the time. Ordinary backend noise was bigger than the signal an auditor would look for.

So a provider that wanted to serve a cheaper model some of the time would probably get away with it.…

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