Ex-Meta scientists want to bring visual AI to the factory floor

AI is transforming everything around us but, thus far, it has largely remained contained to the digital realm. Increasingly, however, startups are looking to take it into the real world.

Perceptron , a startup started by two former Meta research scientists, is one such company. Founded in November 2024, the firm develops frontier vision models that aim to help machines more competently interact with their physical environments.

This week, the company launched its latest model, Isaac 0.5, which its creators say is designed to provide machines with the ability to “perceive, reason and act” in industrial settings. Specifically, the software is capable of helping vision-guided robots navigate complex environments like warehouses or factory floors. It also helps companies extract visual intelligence from videos recorded by those bots.

Isaac 0.5 is also being released as an open-weight model, so its parameters and training materials can be inspected by anyone.

The startup, which recently raised $21 million in a funding round led by Bessemer Venture Partners, was co-founded by Armen Aghajanyan and Akshat Shrivastava, who previously worked for Meta’s Fundamental AI Research (FAIR), the tech giant’s AI research division. The duo see their software as the future of industrial automated deployment.

“Physical AI today forces a false choice: generalist foundation models that need multiple dedicated cloud GPUs for every instance, or narrow models that handle perception or control, but never both,” the company says.

Aghajanyan and Shrivastava say their tool is unlike existing models in the space because it is general-purpose, meaning that it’s not built for one specific, repetitive task. Instead, they say, the model is designed to be flexible depending on the particular environment (or situation) it is in.

In an interview, Shrivastava asked me to consider what goes into a simple physical process like organizing boxes: “Imagine there’s a robot being deployed to sort packages right now. What are the tasks it would need to do?”

Such a relatively simple task indeed consists of many steps. A robot would first have to read the label on the package, do some spatial analysis to understand where the boxes are, and decide which one to pick up. If it’s picking up a series of boxes, it would have to plan which boxes to pick up and in which order.

Perceptron’s software is designed to help robots find their way through each step of the process. To be clear, the industry already has software that can help machines do most of those tasks, but there are few programs that are designed to do it flexibly.