An artificial intelligence startup based in San Francisco has raised fresh funding to build software that helps other businesses develop machine learning platforms and products more responsibly.
Weights & Biases announced on Wednesday that it had raised $50 million in new funding in a "strategic" round that was led by former Github CEO Nat Friedman and Daniel Gross, who was briefly a partner at Y Combinator before launching his own accelerator called Pioneer in 2018.
Other investors that participated in the new round included Sapphire Ventures, Coatue Management, Insight Partners, Felicis Ventures, BOND Capital and Bloomberg Beta.
The round brings the company's total funding to $250 million and also pushed Weights & Biases' valuation to $1.25 billion, up slightly from its previous valuation of just over $1 billion after its Series C round closed in 2021, according to PitchBook.
“Our goal at Weights & Biases has never changed: to build the best tools for machine learning practitioners,” CEO Lukas Biewald said in a statement. “We’re really excited about where the field is moving, specifically the success and adoption of foundational generative AI models."
Biewald co-founded Weights & Biases in 2017 with CTO Shawn Lewis and chief information security officer Christopher Van Pelt, and started partnering with another local AI startup at that time: OpenAI.
“We’re big Weights & Biases fans here at OpenAI and have been using their product for a long time. In fact, we were their first customer," OpenAI's VP of product said in a statement.
Weights & Biases helps other AI and machine learning developers automate a lot of processes so that their repositories of code aren't so-called black boxes.
Instead, the tools from Weights & Biases help developers track and monitor their code so that it can be more easily observed, debugged, audited and explained, which is important for keeping code organized as well as ensuring compliance with regulations.
Weights & Biases was also selected as one of the honorees for this year's Bay Area Inno Awards.
“It’s important to me that we make machine learning available to everyone that’s interested in doing it,” Biewald told me in an interview for the Inno Awards. “I had the opportunity to go to Stanford, which turned out to be ground zero for this stuff, but that was luck … We have a role to play to help people become productive machine learning engineers.”
The company says it has over 700,000 users including generative AI developers at OpenAI, Meta, MosiacML, Aleph Alpha and HuggingFace.
It charges commercial and enterprise users, and also makes its tools available for free to students and personal use.
