Machine learning experiment tracking startup Weights and Biases raises $45M
Machine learning startup Weights and Biases Inc. said today it has raised $45 million in a new round of funding that brings its total amount raised to $65 million.
The Series B round was led by Insight Partners with participation from Coatue, Trinity Ventures and Bloomberg Beta.
Weights and Biases has created a platform for teams to build and collaborate on machine learning models and operations, or MLOps. The platform enables teams to keep track of their machine learning experiments. It also provides tools for evaluating the performance of different machine learning models, dataset versioning and pipeline management.
Chief Executive Officer Lukas Biewald said that although software developers have access to lots of high-quality tools for every part of their workflow, machine learning practitioners have been left behind.
“You can’t have AI safety if ML teams can’t systematically track the models they build and the datasets they use,” Biewald said. “This funding allows us to expand the category leading products for ML practitioners that we are known for.”
In an interview with TechCrunch, Biewald said machine learning model development involves lots of experimentation. He gave the example of a model that’s used to control a self-driving car. He said that if the car were to end up crashing, it can be extremely difficult to work out what went wrong if no one is keeping track of things. Weights and Biases’ experiment tracking platform makes it easier to find out what happened, he said.
Weights and Biases already has quite a few high-profile customers. They include the agricultural giant Deere & Co., which is using the platform to continually improve the way it uses robots to spray fertilizer to kill weeds and pests. Also, several pharmaceutical companies use Weights and Biases’ platform in drug research to model how different molecules will behave.
The company said it will use the new funds to continue hiring in its engineering, growth, sales and customer success teams.
Image: Weights and Biases
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