Meta Debuts AI to Help Robots ‘Understand the Physical World’

Meta has introduced a model to help train robots and other artificial intelligence (AI) agents.

V-JEPA 2, announced Wednesday (June 11), is designed to help AI agents “understand the physical world and predict how it will respond to their actions,” Meta said on its blog.

The tech giant says these capabilities are key to developing AI agents that think before acting, with V-JEPA 2 marking progress toward the company’s goal of creating advanced machine intelligence (AMI).

“As humans, we have the ability to predict how the physical world will evolve in response to our actions or the actions of others. For example, you know that if you toss a tennis ball into the air, gravity will pull it back down,” the company said.

“V-JEPA 2 helps AI agents mimic this intelligence, making them smarter about the physical world. The models we use to develop this kind of intelligence in machines are called world models, and they enable three essential capabilities: understanding, predicting and planning.”

Meta said it trained V-JEPA 2 using video, which helped it discover important patterns in the physical world, such as how people interact with objects, how objects move in the physical world or interact with other objects.

The launch of V-JEPA 2 comes one day after reports that Meta CEO Mark Zuckerberg was personally recruiting experts to help assist in his goal of turning Meta into a leader in the field of artificial general intelligence (AGI), a term for machines that can carry out tasks at the same level as humans.

In other AI news, PYMNTS CEO Karen Webster spoke Wednesday with Tejas Manohar, co-founder and co-CEO of Hightouch, about the way the technology can help brands overcome “digital fatigue” when it comes to marketing.

“Marketing that actually adds value to the consumer’s life versus just sort of, ‘Hey, here’s my product, here’s my product,’ that is what resonates,” Manohar said.

Webster underscored the crux of the debate: “Our inboxes, our text inboxes, our apps are just filled with solicitations … especially now as brands are really hoping to drive more spend.”

This collective burnout, she argued, is not a technology issue but a failure of strategic design.

Manohar agreed, saying brands continue to follow analog rules: static calendars, batch-and-blast messaging, and audience segments defined by guesswork and not signal.

“Our belief is that traditional channels just don’t support the [human-feeling] capability that modern digital channels do,” Manohar explained.