Can anybody with experience in fabrication reveal more about this? Very exciting ideas, but hoping to learn more in real-world context
Can anybody with experience in fabrication reveal more about this? Very exciting ideas, but hoping to learn more in real-world context
Still, i don’t think it’ll need to get much more complex to be very useful for AI workloads.
People have been discovering that more, and simpler, calculations seem to work better? the trend in AI workloads seems to have gone from FP32 -> FP16 -> INT16 -> INT8 and possibly even INT4?
Seems like just having lots of simple calculations is more efficient/effective than more complex stuff.
Well these chips perform analog math, which means high precision high speed. It’s not as accurate as fp32 as in repeatedly and deterministic outputs, but that’s def not a problem for a deep and wide neural network such as used by llm