Photonic computing holds the promise of revolutionizing the way artificial intelligence (AI) applications are powered. Lightmatter, a startup that specializes in creating photonic chips for AI and machine learning tasks, has recently closed an $11 million Series A funding round.

The potential of this technology is enormous - these chips can perform calculations at the speed of light, providing unprecedented performance compared to traditional computing methods. Rather than breaking down complex mathematical operations into smaller ones and performing them sequentially, Lightmatter’s photonic chips solve entire problems in one go by tracking tiny changes in the phase or path of a beam of light.

Powered by research conducted at MIT and built on patents licensed to the company, Lightmatter has created a prototype chip with 32 ‘neurons’. The aim is now to scale this up to hundreds - something that could be game-changing for industries relying heavily on AI technology.

The $11 million Series A round led by Matrix and Spark will enable the team at Lightmatter to take their technology from a prototype to a product. This isn’t seen as a science project, but rather the first application of optical computing in a very controlled manner. Compe*****s are focused on squeezing every drop of performance out of semi-specialized hardware like GPUs, while Lightmatter is offering an entirely different engine - one that has only recently become possible due to investment in basic research and infrastructure behind building photonic chips over the last decade.

AI is still in its infancy, and new enabling technologies are needed for it to progress. At Lightmatter, they aim to augment electronic computers with photonics to power a fundamentally new kind of computer that is efficient enough to propel the next generation of AI.

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