Lambda, a supplier of deep learning GPU cloud services and computing hardware, has raised $24.5 million in new funding. Primary investors include 1517 Fund, Gradient Ventures, Bloomberg Beta, Razer, and Georges Harik. This round of funding includes a $15 million Series A equity investment and a $9.5 million loan facility from Silicon Valley Bank.

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Lambda, founded and led by AI and ML engineers, provides deep learning computing infrastructure to clients such as Apple, Intel, Microsoft, Amazon Research, Tencent, Kaiser Permanente, MIT, Stanford, Harvard, Caltech, and the Department of Defense, including GPU cloud services, servers, GPU clusters, GPU workstations, and GPU laptops.

The funds will be used to develop Lambda’s cloud and software engineering teams, as well as to pay for fixed assets connected to its cloud business and to provide working capital for its deep learning hardware business.

“Fortune 500 companies, startups, and universities are forced to build huge teams to administer the compute resources required to train deep learning models,” said Stephen Balaban, co-founder, and CEO of Lambda. “We want to build a world where a single researcher can manage petaflops of GPU compute. A world where training a model on a data center scale computer is as easy as training a model on your laptop.”

Existing Lambda Investors

With the exception of Razer, all major funding parties were existing Lambda investors. Lambda’s Board of Directors include Robert Youngjohns, Operating Executive at Marlin Equity Partners, and Zach Bratun-Glennon, Partner at Gradient Ventures. Robert was previously the EVP and GM of HP Software at HPE and, before that, President of Microsoft North America. He has also held senior leadership roles at Callidus Cloud, Sun Microsystems, and IBM.

Current investors and advisors to Lambda include 1517 Fund, Gradient Ventures, Bloomberg Beta, Razer, Scott McNealy, Austin Russell, Georges Harik, James Hong, James Cham, Jun Hong Heng, Nicolas Pinto, Gary Bradski, Ken Patchett, Randy Ching, Keller Rinaudo, and others.

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