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    Home»Tech News»Artificial intelligence: Yann LeCun works on more flexible AI
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    Artificial intelligence: Yann LeCun works on more flexible AI

    Ironside NewsBy Ironside NewsJuly 3, 2026No Comments3 Mins Read
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    “We do not have robots which are almost pretty much as good at understanding the bodily world as a rat,” says Yann LeCun, one of many main figures on this planet of synthetic intelligence.

    He labored at Fb-owner, Meta, for a decade, the place he was chief AI scientist, however left in 2025 and based Superior Machine Intelligence Labs (AMI Labs).

    His aim is to maneuver AI past present techniques like ChatGPT, Claude and Gemini. They’ve their makes use of, he says, however won’t ever be capable of deal with sophisticated conditions in the actual world, like getting a robotic to do family chores.

    “They are not a path in the direction of human stage or human-like intelligence, and even animal-like intelligence, as a result of they can not take care of actual world information, they simply will not be constructed for that,” he tells me on the sidelines of VivaTech, France’s main expertise convention.

    So, Paris-based AMI Labs is busy creating a brand new kind of synthetic intelligence not primarily based on the tech behind ChatGPT and its rivals.

    Traders assume it has potential. Earlier this 12 months AMI Labs introduced that it had raised greater than $1bn (£760m), with buyers together with US laptop chip large Nvidia and the fund that manages the personal wealth of Amazon-founder Jeff Bezos.

    That so-called seed funding spherical – the earliest spherical of start-up fundraising – was one of many largest of its sort in Europe.

    Giant Language Fashions (LLMs) like ChatGPT are extraordinarily good at some issues like coding, mathematical issues and producing textual content, LeCun says.

    However he argues that these are effectively outlined and predictable issues.

    “They [LLMs] principally simply accumulate data… They’ll regurgitate one thing, you prepare them to regurgitate, however they don’t seem to be notably sensible. They do not have an underlying understanding,” he says.

    In the actual world there’s a bewildering array of outcomes to any motion, which requires a extra versatile kind of synthetic intelligence.

    LeCun holds a pen upright on its tip. What occurs once you let go, he asks? Even a toddler would know that the pen would topple over. However no human would trouble to guess during which route the pen may fall, there is not any strategy to inform.

    However an LLM may attempt to generate a single prediction in regards to the pen’s subsequent transfer primarily based on statistical patterns from its coaching information.

    The prediction would nearly actually be flawed, as a result of the system shouldn’t be reasoning in regards to the bodily actuality of the state of affairs – it’s producing what seems to be statistically believable.

    LeCun says the system his firm is creating, referred to as Joint Embedding Predictive Structure (JEPA), is ready as much as take care of issues like that.

    It creates abstractions of the actual world that permit it to evaluate the outcomes of actions.

    Creating these abstractions entails tough maths, however basically they filter out ineffective data, simply leaving the AI with helpful footage of the world.

    Within the case of the pen, the AI would know that there is not any level in attempting to foretell which approach the pen would fall.



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