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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

    Team_Prime US NewsBy Team_Prime US NewsJuly 3, 2026No Comments3 Mins Read
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    “We do not have robots which might be practically 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 difficult conditions in the true world, like getting a robotic to do family chores.

    “They are not a path in direction of human degree or human-like intelligence, and even animal-like intelligence, as a result of they can’t cope with actual world knowledge, they simply usually are not 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 based mostly on the tech behind ChatGPT and its rivals.

    Traders suppose it has potential. Earlier this yr AMI Labs introduced that it had raised greater than $1bn (£760m), with buyers together with US laptop chip big 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 variety 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 nicely outlined and predictable issues.

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

    In the true 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 while you let go, he asks? Even a toddler would know that the pen would topple over. However no human would trouble to guess by which course the pen may fall, there isn’t any solution to inform.

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

    The prediction would nearly definitely be unsuitable, as a result of the system isn’t reasoning in regards to the bodily actuality of the scenario – it’s producing what seems to be statistically believable.

    LeCun says the system his firm is creating, known as Joint Embedding Predictive Structure (JEPA), is ready as much as cope with issues like that.

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

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

    Within the case of the pen, the AI would know that there isn’t any level in making an attempt to foretell which manner the pen would fall.



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