Photonic startup Lightmatter raises $400 million amid AI datacenter boom, eyes IPO next
Lightmatter raises $400 mln in Series D funding led by T. Rowe Price
CEO eyes future IPO, sees demand from cloud and AI companies
By Krystal Hu
Oct 16 -Lightmatter, a Mountain View, California-headquartered startup building photonic tech in datacenter networking chips, said on Wednesday it has raised $400 million in a Series D funding round at a valuation of $4.4 billion.
New investor T. Rowe Price led the funding round, with participation from existing backers including Fidelity and Alphabet's GV.
The latest funding came less than a year since the last raise, bringing total funding since inception to $850 million as the company tries to capitalize on the datacenter boom and need for more efficient infrastructure in the artificial intelligence (AI) race set off by ChatGPT.
Lightmatter said its fresh capital will be used to manufacture and deploy its photonic chips in partner data centers, as well as expanding its 200-person team across the U.S. and Canada.
The funding follows the appointment of former Nvidia executive Simona Jankowski as CFO, and could pave its way for a potential public offering.
“This is probably our last private funding round,” said co-founder and CEO Nick Harris. “We've booked very large deals. And that is the reason that this level of funding is possible. We see a future where most of the high performance computing and AI chips very soon are going to be based on Lightmatter tech."
The company, which develops methods for computer chips to communicate and perform calculations using silicon photonics, said it sees huge demand from cloud providers and AI companies, but declined to name its customers.
While the concept of using light in computing isn't new and offers potential for faster, more energy-efficient processes, creating the necessary components has historically been challenging.
Founded in 2017, Lightmatter says its proprietary technology enables photonics chips to move data, increasing AI cluster bandwidth and performance while reducing power consumption. Its first large clusters are expected to be running next year.
Editing by Elaine Hardcastle
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