MIPS in Hand, AI Chip Startup Wave Computing Delivers First Silicon

When it comes to deep learning chip startups, hype moves fast but crossing the finish line to real production silicon takes an incredibly long time. There are several incumbents on the custom hardware side aiming for the AI training and inference market but outside of Google's TPU, there are very few functioning inside datacenters. From the forthcoming Nervana chips (now expected in 2019) to startups like Graphcore, Cerebras (which just ducked back into stealth mode), among several others, the pressure is on to create hardware that reflects the latest framework and algorithmic developments that so far seem to run quite well on widely available GPUs with all the requisite porting and software work handled thanks to big library and tooling investments from Nvidia over the last few years. In other words, it is going to be damn tough to beat Nvidia, especially this late in the game, but for one of the better known deep learning chip startups, Wave Computing, there is more going on in the outfield than we might readily see. This is why the company has invested in tech that might seem a bit left field--that is, until we look at how the AI hardware game of the future might play out.