Ahead of the Hot Chips conference this week, photonics chip startup Lightmatter revealed the first technical details about its upcoming test chip. Unlike conventional processors and graphics cards, the test chip uses light to send signals, promising orders of magnitude higher performance and efficiency. The technology underpinning the test chip -- photonic integrated circuits -- stems from a 2017 paper coauthored by Lightmatter CEO and MIT alumnus Nicholas Harris that described a novel way to perform machine learning workloads using optical interference. Chips like the test chip, which is on track for a fall 2021 release, require only a limited amount of energy because light produces less heat than electricity. They also benefit from reduced latency and are less susceptible to changes in temperature, electromagnetic fields, and noise.
Light forms the global backbone of information transmission yet is rarely used for information transformation. Digital optical logic faces fundamental physical challenges1. Many analog approaches have been researched2,3,4, but analog optical co-processors have faced major economic challenges. Optical systems have never achieved competitive manufacturability, nor have they satisfied a sufficiently general processing demand better than digital electronic contemporaries. Incipient changes in the supply and demand for photonics have the potential to spark a resurgence in optical information processing.
"Deep Learning" computer systems, based on artificial neural networks that mimic the way the brain learns from an accumulation of examples, have become a hot topic in computer science. In addition to enabling technologies such as face- and voice-recognition software, these systems could scour vast amounts of medical data to find patterns that could be useful diagnostically, or scan chemical formulas for possible new pharmaceuticals.
Chip startup Lightmatter has received an infusion of $11 million from investors to help bring the world's first silicon photonics processor for AI to market. Using technology originally developed at MIT, the company is promising "orders of magnitude performance improvements over what's feasible using existing technologies."
Silicon photonics is exhibiting greater innovation as requirements grow to enable faster, lower-power chip interconnects for traditionally power-hungry applications like AI inferencing. With that in mind, scientists at Massachusetts Institute of Technology launched a startup in 2017 called Lightmatter Inc. to develop silicon photonic processors. Another goal was leveraging optical computing to "decouple" AI processing from Moore's law scaling that according to the company founders literally produces more heat than light. Lightmatter announced an AI photonic "test chip" during this week's Hot Chips conference positioned as an AI inference accelerator using light to process and transport data. The 3D module incorporates a 12- and 90-nm ASIC, the latter supporting photonics processing steps such as laser monitoring and light distribution.