It takes an immense amount of processing power to create and operate the “AI” features we all use so often, from playlist generation to voice recognition. Lightmatter is a startup that is looking to change the way all that computation is done — and not in a small way. The company makes photonic chips that essentially perform calculations at the speed of light, leaving transistors in the dust. It just closed an $11 million Series A.
The claim may sound grandiose, but the team and the tech definitely check out. Nick Harris, Lightmatter’s CEO, wrote his thesis on this stuff at MIT, and has published in major journals like Nature Photonics several papers showing the feasibility of the photonic computing architecture.
So what exactly does Lightmatter’s hardware do?
At the base of all that AI and machine learning is, like most computing operations, a lot of math (hence the name computing). A general-purpose computer can do any of that math, but for complex problems it has to break it down into a series of smaller ones and perform them sequentially.
One such complex type of math problem common in AI applications is a matrix vector product. Doing these quickly is important for comparing large sets of data with one another, for instance if a voice recognition system wants to see if a certain sound wave is sufficiently similar to “OK Google” to initiate a response.
The problem is that as demand increases for AI-based products, these calculations need to be done more and faster, but we’re reaching the limits of just how quickly and efficiently they can be accomplished and relayed back to the user. So while the computing technology that has existed for decades isn’t going anywhere, for certain niches...