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I wonder how the QC these chips. Digital chips can run vectors and show that every bit is exactly a 1 or 0 as expected. With an analog chip, each weight, each m
by tasty_freeze 3y ago
I wonder how the QC these chips. Digital chips can run vectors and show that every bit is exactly a 1 or 0 as expected. With an analog chip, each weight, each multiplication, each summation can produce a range of outputs depending on temperature, voltage, and process. I'm sure they have done everything they can to minimize these issues, but they will always be non-trivial.
Of course, the organic neural networks in our brains have all these issues and more and still do fine. On the other hand, our brains have billions of years of evolution that results in them being fault tolerant in ways that this chip can replicate at all.
- dreamcompiler 3y agoThe nice thing about this particular application (deep neural networks) is they're usually fairly insensitive to weight noise because they have a lot of redundancy, just like our brains. Your question still stands, however. And for an analog chip it's basically the question of how to qualify, validate, and characterize neural networks in general. I'm not convinced we have the faintest idea how to do that in any formal sense.
- aidenn0 3y agoWe've been QCing analog products for far longer than we have been QCing digital products.