Neuromorphic Computing vs AI Chips: Compete or Complement?

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Both AI and neuromorphic computing run neural networks, but it doesn't necessarily follow that they will go head-to-head.

eetasia.com, Apr. 15, 2020 – 

At first glance, the new breed of neuromorphic chips have several things in common with the similarly cutting-edge field of AI accelerators. Both are designed to process artificial neural networks, both offer improvements in performance compared to CPUs, and both claim to be more power efficient.

That's where the similarity ends, though: Neuromorphic chips are designed only for special neural networks called spiking networks, and their structure is fundamentally different from anything seen in traditional computing (nothing so conventional as multiply-accumulate units). It is perhaps a too soon to say what the market for these devices will look like, as new applications and technologies continue to emerge.

EE Times asked CEOs at leading AI accelerator companies whether the technologies are truly complementary or whether there is some overlap.

The big question is: Will these computing paradigms end up competing with each other further down the line?

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