Taalas Inc. has raised $50 million to help the chip startup advance a range of deep learning models in silicon including its first large language model chip in development.
The startup, based in Toronto, Canada, is working on deep learning models that the company claims can outperform a small GPU data center which will pave the way for a 1,000 times improvement in the cost of artificial intelligence (AI).
The company is currently taping out its first large language model chip in the third quarter of this year. The chip will then be available to early customers in the first quarter of 2025, Taalas said.
The $50 million investment over two rounds of funding was led by Pierre Lamond and Quiet Capital.
"We believe the Taalas 'direct-to-silicon' foundry unlocks three fundamental breakthroughs: dramatically resetting the cost structure of AI today, viably enabling the next 10-100x growth in model size, and efficiently running powerful models locally on any consumer device,” said Matt Humphrey, partner at Quiet Capital. “This is perhaps the most important mission in computing today for the future scalability of AI. And we are proud to support this remarkable n-of-1 team as they do it.”
