Bifrost helps industrials speed up model training with its 3D data generation platform
Bifrost has raised an $8M Series A led by Carbide Ventures to further build out its 3D real-world data simulation platform.
For many companies working on AI models with applications in the physical world, data presents the biggest opportunity. It’s also the biggest hurdle they face, as nicely labeled and clean real-world data is as readily available as hen’s teeth, and the costs and effort required to gather and clean up data can be immense.
Bifrost, a 3D data generation platform, believes its tech can help robotics and industrial companies solve at least one part of that problem: the time required to train AI models. The startup, based out of San Francisco, says its platform lets companies generate simulated 3D worlds to instruct their AI models and help their robots adjust to new objects, tasks and surroundings within hours instead of months.
The company said on Wednesday that it has raised $8 million in a Series A funding round led by Carbide Ventures.
“Most of our customers need vast amounts of real-world data to train AI models,” co-founder and CEO Charles Wong said in an exclusive interview with TechCrunch. “This often means they would have to deploy fleets of robots across hundreds of locations, collect millions of hours of footage, manually label the data, and implement rigorous quality checks to reduce human errors and bias. This approach is brutal. It costs millions, takes years, and proves nearly impossible to scale.”
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