[scrps]

If my reading of it is correct this is similar to something like a trusted bootchain where every step is cryptographically verified against the chain and the components.

In plain english the final model you load and all the components used to generate that model can be cryptographically verified back to whomever trained it and if any part of that chain can't be verified alarm bells go off, things fail, etc.

Someone please correct me if my understanding is off.

Edit: typo

[losteric]

How does this differ from challenges around distributing executable binaries? Wouldn't a signed checksums of the weights suffice?

[manmal]

I think this is more a „how did the sausage get made“ situation, rather than an „is it the same sausage that left the factory“ one.

[scrps]

Sausage is a good analogy. It is both (at least with chains of trust) the manufacturer and the buyer that benefits but at different layers of abstraction.

Think of sausage(ML model), made up of constituent parts(weights, datasets, etc) put through various processes(training, tuning), end of the day, all you the consumer cares about is the product won't kill you at a bare minimum(it isn't giving you dodgy outputs). In the US there is the USDA(TPM) which quite literally stations someone(this software, assuming I am grokking it right) from the ranch to the sausage factory(parts and processes) at every step of the way to watch(hash) for any hijinks(someone poisons the well), or just genuine human error(gets trained due to a bug on old weights) in the stages and stops to correct the error and find the cause and allows you traceability.

The consumer enjoys the benefit of the process because they simply have to trust the USDA, the USDA can verify by having someone trusted checking at each stage of the process.

Ironically that system exists in the US because meatpacking plants did all manner of dodgy things like add adulterants so the US congress forced them to be inspected.