The answer to the question of how to make the best of AI hardware may not be solely, or even primarily, related to hardware

How do you make the best out of the proliferating array of emerging custom silicon hardware while not spreading yourself thin to keep up with each and every one of them?

If we were to put a price tag on that question, it would be in the multi-billion dollar territory. That’s what the combined estimated value of the different markets it touches upon is. As AI applications are exploding, so is the specialized hardware that supports them.

For us, interest in so-called AI chips came as an offshoot of our interest in AI, and we’ve tried to keep up with developments in the field. For Evan Sparks, Determined AI CEO and founder, it goes deeper. We caught up to discuss the interplay between hardware and models in AI.

Before founding Determined AI, Sparks was a researcher at the AmpLab at UC Berkeley. He focused on distributed systems for large scale machine learning, and this is where he had the opportunity to work with people like David Patterson, a pioneer in computer science, and currently vice-chair of the board of directors of the RISC-V Foundation.

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