Category: ai

Meta’s chief AI scientist and Turing Award winner Yann LeCun plans to leave the company to launch his own startup focused on a different type of AI called “world models,” the Financial Times reported. The French-US scientist has reportedly told associates he will depart in the coming months and is already in early talks to raise funds for the new venture. The departure comes as CEO Mark Zuckerberg radically overhauled Meta’s AI operations after deciding the company had fallen behind rivals such as OpenAI and Google.

World models are hypothetical AI systems that some AI engineers expect to develop an internal “understanding” of the physical world by learning from video and spatial data rather than text alone. Unlike current large language models (such as the kind that power ChatGPT) that predict the next segment of data in a sequence, world models would ideally simulate cause-and-effect scenarios, understand physics, and enable machines to reason and plan more like animals do. LeCun has said this architecture could take a decade to fully develop.

While some AI experts believe that Transformer-based AI models—such as large language models, video synthesis models, and interactive world synthesis models—have emergently modeled physics or absorbed the structural rules of the physical world from training data examples, the evidence so far generally points to sophisticated pattern-matching rather than a base understanding of how the physical world actually works.

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Google’s current mission is to weave generative AI into as many products as it can, getting everyone accustomed to, and maybe even dependent on, working with confabulatory robots. That means it needs to feed the bots a lot of your data, and that’s getting easier with the company’s new Private AI Compute. Google claims its new secure cloud environment will power better AI experiences without sacrificing your privacy.

The pitch sounds a lot like Apple’s Private Cloud Compute. Google’s Private AI Compute runs on “one seamless Google stack” powered by the company’s custom Tensor Processing Units (TPUs). These chips have integrated secure elements, and the new system allows devices to connect directly to the protected space via an encrypted link.

Google’s TPUs rely on an AMD-based Trusted Execution Environment (TEE) that encrypts and isolates memory from the host. Theoretically, that means no one else—not even Google itself—can access your data. Google says independent analysis by NCC Group shows that Private AI Compute meets its strict privacy guidelines.

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We’re running out of ways to tell you that Google is releasing more generative AI features, but that’s what’s happening in Google Photos today. The Big G is finally making good on its promise to add its market-leading Nano Banana image-editing model to the app. The model powers a couple of features, and it’s not just for Google’s Android platform. Nano Banana edits are also coming to the iOS version of the app.

Nano Banana started making waves when it appeared earlier this year as an unbranded demo. You simply feed the model an image and tell it what edits you want to see. Google said Nano Banana was destined for the Photos app back in October, but it’s only now beginning the rollout. The Photos app already had conversational editing in the “Help Me Edit” feature, but it was running an older non-fruit model that produced inferior results. Nano Banana editing will produce AI slop, yes, but it’s better slop.

Google says the updated Help Me Edit feature has access to your private face groups, so you can use names in your instructions. For example, you could type “Remove Riley’s sunglasses,” and Nano Banana will identify Riley in the photo (assuming you have a person of that name saved) and make the edit without further instructions. You can also ask for more fantastical edits in Help Me Edit, changing the style of the image from top to bottom.

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For months, extremely personal and sensitive ChatGPT conversations have been leaking into an unexpected destination: Google Search Console (GSC), a tool that developers typically use to monitor search traffic, not lurk private chats.

Normally, when site managers access GSC performance reports, they see queries based on keywords or short phrases that Internet users type into Google to find relevant content. But starting this September, odd queries, sometimes more than 300 characters long, could also be found in GSC. Showing only user inputs, the chats appeared to be from unwitting people prompting a chatbot to help solve relationship or business problems, who likely expected those conversations would remain private.

Jason Packer, owner of an analytics consulting firm called Quantable, was among the first to flag the issue in a detailed blog last month.

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