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Lightmatter lands $33M to marry photonics with AI

27 Feb 2019

Boston startup developing programmable Mach-Zehnder interferometers attracts financial support from GV, formerly Google Ventures.

Lightmatter, a Boston-based startup developing photonics technology for faster and more efficient computing than is possible with electronic devices, has increased its series A funding to $33 million.

The company, incorporated in 2017, has just closed an add-on round of $22 million led by GV, previously Google Ventures. Spark Capital and Matrix Partners also took part in the round.

Interferometer focus
The cash is intended to support development of future computing hardware based around Mach-Zehnder interferometers. In a blog post at medium.com, co-founder and CEO Nicholas Harris wrote:

“This January marks one year since we started - a lot has happened. We carefully assembled a team of 23 world-class scientists and engineers to develop a scalable platform for high-throughput, high-efficiency artificial intelligence computing.

“We taped out our first (successful) test chip with transistors and photonic elements from start to finish in four months. Eight months after that, we taped out a chip with over a billion transistors.”

The Lightmatter engineering team is aiming to deliver the first photonics-based artificial intelligence accelerator product, and is currently hiring a full-time photonics design engineer at its Boston site.

By using light instead of electrical signals, the company says that its combination of photonics, electronics, and algorithms will deliver a new computing architecture offering “orders of magnitude” performance improvements over what would be feasible with the traditional approach of shrinking transistor dimensions with lithography.

“It’s worth noting that the end of Moore’s Law isn’t (yet) due to the inability of chip makers to shrink transistors,” explained Harris in his post. “If you’re going to pack more transistors onto the same sized chip, which has been happening for decades, those transistors need to be commensurately more energy efficient; herein lies the problem.”

Photonics suits AI
Instead of using conventional computing architecture based around so-called “multiply-accumulate” units, Harris and colleagues plan to employ programmable Mach-Zehnder interferometers.

“This photonic device is not bound by the physics that limit transistor-based electronic circuits - opening an avenue towards continuing the currently broken trend of exponential growth in compute per unit area within a practical power envelope,” states the CEO.

The idea is that the novel approach will be better suited to the way that artificial intelligence platforms operate.

“Current transistor-based technologies are approaching the limits of their fundamental capabilities, and faster and more energy efficient computers will be essential to the continued progress of AI,” claims the company. “The alternative computing platform being developed by Lightmatter will be critical to powering the next generation of AI algorithms.”

In a release announcing the latest funding, GV general partner Tyson Clark, who now sits on the startup’s board of directors, added:

“Lightmatter is building a next-generation computing platform at the cutting edge of photonics and artificial intelligence, at a time when there is a growing need for new hardware-based approaches to AI acceleration.

“We believe the team’s theoretical expertise and engineering talent are clear differentiators in the market for artificial intelligence accelerators.”

Alongside MIT-trained Harris, Lightmatter’s co-founders include chief scientist Darius Bunandar, and COO and former Google employee Thomas Graham. MIT professor Dirk Englund, winner of the 2017 ACS Photonics Young Investigator Award, is the company’s technical advisor.

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