AI chips in the real world: interoperability, constraints, cost, energy efficiency, models
As it turns out, the answer to the question of how to make the best of AI hardware may not be solely, or even primarily, related to hardware
Today's episode features Determined AI CEO and Founder, Evan Sparks. Sparks is a PhD veteran of Berkeley's AmpLab with a long track record of accurate predictions in the chip market.
We talk about an interoperability layer for disparate hardware stacks, ONNX and TVM -- two ways to solve similar problems, AI constraints and energy efficiency, and Infusing knowledge in models
Article published on ZDNet
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