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Meta Says Its New AI Model Can Understand the Physical World

The new model could allow robots to grasp concepts like gravity and object permanence while relying less on large amounts of video or training data.

Meta says a new generative AI model it released Wednesday could change how machines understand the physical world, opening up opportunities for smarter robots and more. 

The new open-source model, called Video Joint Embedding Predictive Architecture 2, or V-JEPA 2, is designed to help artificial intelligence understand things like gravity and object permanence, Meta said. 

Current models that allow AI to interact with the physical world rely on labeled data or video to mimic reality, but this approach emphasizes the logic of the physical world, including how objects move and interact. The model could allow AI to understand concepts like the fact that a ball rolling off of a table will fall.

Meta said the model could be useful for devices like autonomous vehicles and robots by ensuring they don’t need to be trained on every possible situation. The company called it a step toward AI that can adapt like humans can. 

One struggle in the space of physical AI has been the need for significant amounts of training data, which takes time, money and resources. At SXSW earlier this year, experts said synthetic data — training data created by AI — could help prepare a more traditional learning model for unexpected situations. (In Austin, the example used was the emergence of bats from the city’s famed Congress Avenue Bridge.) 

Meta said its new model simplifies the process and makes it more efficient for real-world applications because it doesn’t rely on all of that training data. 

Technologies

Meta Says Its New AI Model Understands Physical Rules Like Gravity

The new model could allow robots to better predict changes in their environment and make better decisions.

A new generative AI model Meta released this week could change how machines understand the physical world, opening up opportunities for smarter robots and more, the company said. 

The new open-source model, called Video Joint Embedding Predictive Architecture 2, or V-JEPA 2, is designed to help artificial intelligence understand things like gravity and object permanence, Meta said. 

«By sharing this work, we aim to give researchers and developers access to the best models and benchmarks to help accelerate research and progress,» the company said in a blog post, «ultimately leading to better and more capable AI systems that will help enhance people’s lives.»

Current models that allow AI to interact with the physical world rely on labeled data or video to mimic reality, but this approach emphasizes the logic of the physical world, including how objects move and interact. The model could allow AI to understand concepts like the fact that a ball rolling off of a table will fall.

Meta said the model could be useful for devices like autonomous vehicles and robots by ensuring they don’t need to be trained on every possible situation. The company called it a step toward AI that can adapt like humans can. 

One struggle in the space of physical AI has been the need for significant amounts of training data, which takes time, money and resources. At SXSW earlier this year, experts said synthetic data — training data created by AI — could help prepare a more traditional learning model for unexpected situations. (In Austin, the example used was the emergence of bats from the city’s famed Congress Avenue Bridge.) 

Meta said its new model simplifies the process and makes it more efficient for real-world applications because it doesn’t rely on all of that training data. 

The next steps for world models include training models that are capable of learning, reasoning and planning across different time and space scales, making them better at breaking down complicated tasks. Multimodal models, that can use other senses like audio and touch in addition to vision, will also help future AI models understand the real world. 

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Internet Outage Hits Hard as Google, AWS, Spotify and More Go Down

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Today’s NYT Strands Hints, Answers and Help for June 13, #467

Here are hints and answers for the NYT Strands puzzle No. 467 for June 13.

Looking for the most recent Strands answer? Click here for our daily Strands hints, as well as our daily answers and hints for The New York Times Mini Crossword, Wordle, Connections and Connections: Sports Edition puzzles.


Today’s NYT Strands puzzle is a fun and seasonal group of words. If you need hints and answers, read on.

I go into depth about the rules for Strands in this story. 

If you’re looking for today’s Wordle, Connections and Mini Crossword answers, you can visit CNET’s NYT puzzle hints page.

Read more: NYT Connections Turns 1: These Are the 5 Toughest Puzzles So Far

Hint for today’s Strands puzzle

Today’s Strands theme is: Scattering petals

If that doesn’t help you, here’s a clue: Name game

Clue words to unlock in-game hints

Your goal is to find hidden words that fit the puzzle’s theme. If you’re stuck, find any words you can. Every time you find three words of four letters or more, Strands will reveal one of the theme words. These are the words I used to get those hints but any words of four or more letters that you find will work:

  • TRITE, RITE, RITES, VILE, LAZY, PENT, GRAIN, RAIN, DIRE, GRAN, LEAR, SOUL, WEST, WETS, RUNT, TURN, VOTE, UNITE, UNTIE, LUNG, TINE. 

Answers for today’s Strands puzzle

These are the answers that tie into the theme. The goal of the puzzle is to find them all, including the spangram, a theme word that reaches from one side of the puzzle to the other. When you have all of them (I originally thought there were always eight but learned that the number can vary), every letter on the board will be used. Here are the nonspangram answers:

  • LILY, ROSE, DAISY, POPPY, AZALEA, VIOLET, PETUNIA

Today’s Strands spangram

Today’s Strands spangram is FLOWERGIRLS  To find it, start with the F that’s the fifth letter to the right on the top row, and wind down.

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