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Ex Google AI Veteran Claims Worlds First AGI Capable System – And Nobodys Talking About it…

TheAIGRID | April 6, 2026



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Comments

This post currently has 35 comments.

  1. @timb350

    April 6, 2026 at 9:32 pm

    How stooopid are AGI projections? Consider this…over 90% of human communication is NON-VERBAL. Meaning…what LLM's are being trained on…is only 10% of human communication. Duplicating human experience is the definition of AGI (to the degree that there even IS a definition). So how can an AI duplicate human experience…when it is only being trained on 10% of it…??? And even that 10% is missing huge amounts of data about whatever-it-is that a human being is. IOW…AGI is nothing but a monumental joke!

  2. @josgraha

    April 6, 2026 at 9:32 pm

    The problems look like problems that would be associated with any embodied AI. Motion planning, future prediction, route planning. Very cool and impressive stuff but is that the "generalized" thing everyone was talking about?

  3. @travasgunnell1888

    April 6, 2026 at 9:32 pm

    You need to work on your reading comprehension. Nowhere do they say that they have achieved AGI. All they are saying is that they have a model–a scalable framework–that is (eventually) capable of achieving AGI after sufficient learning.

  4. @ariaden

    April 6, 2026 at 9:32 pm

    If a video offers a professional clip showcasing an analogy to eye movement (instead of a whitepaper) I immediately place my bets on the "hype" side of the hype-truth scale.

  5. @knightwalker5434

    April 6, 2026 at 9:32 pm

    According to Chat GPT the timeline for AGI is around 2035 if everything runs smoothly. Current limitation 1. Still limited in autonomy, grounded understanding, long-term goal pursuit, and true self-directed learning. 2. Depends heavily on human-defined objectives and guardrails.

  6. @mminde3616

    April 6, 2026 at 9:32 pm

    The "Sokoban" Demo: In recent presentations, they used Sokoban (a warehouse block-pushing game) as a benchmark. While impressive for a robot to learn this from scratch, most researchers argue that solving a 2D puzzle is a long way from the "General Intelligence" required to navigate the infinite complexity of human life… ehh and i had my hopes up.

  7. @Dan-z2c3n

    April 6, 2026 at 9:32 pm

    Learning is about making Mistakes . So to say it can't make mistakes thats not Really Realistic . Now it could run test in thw virtual world .but humans make tons of mistakes several times daily

  8. @The_Darkest_Black_Pill

    April 6, 2026 at 9:32 pm

    Google's early generative AI teams,,,
    ya don't say……..
    So is this the same guy that oversaw Google's early generative image models that basically erased white men from history by refusing to generate an image of one in the name of diversity and inclusion????? 😂😂😂

  9. @christian14329

    April 6, 2026 at 9:32 pm

    This is how stupid humans are! Do you really think these agi and robotics and microchip implants are all about to sell you better products? No! This is about summoning whats going to replace you!

  10. @ItsBushwick

    April 6, 2026 at 9:32 pm

    Al apparatuses are AGI-capable, your tv – AGI-Capable, your toaster – AGI-Capable, your coffee maker – you guessed it AGI-Capable hell my old speak and spell toy from the 1980s could have been classified AGI-Capable and an existential crisis away from giving its own Ted Talk. — Such bs hype… sheesh

  11. @BruceWayne15325

    April 6, 2026 at 9:32 pm

    The reason his claim is not getting as much traction as you'd expect is probably due to the fact that he's not claiming it's AGI. He's claiming it's AGI-capable. That's a claim that will only be proven out over time as it learns, it's not something you can point at now and say "look! this is it!" Interesting sure, but there's a mountain of salt that you need to shovel with the claim.

  12. @Shaw1023207

    April 6, 2026 at 9:32 pm

    You're looking at it from a single perspective, which is the perspective almost everyone takes. The perspective of face value. Other perspective examples to think about: Why reveal it now?
    Why show those demos?
    The perspective of investors.
    Why say AGI?
    Why take interviews?

    Just a few examples. Now put yourself in the guy's shoes and attempt to answer these questions in their perspective. And I don't mean just these questions either. You'll get a better overall picture of what's happening. My opinion is of no value, so I'm just trying to inspire more thought for/from others.

  13. @bioneuralai

    April 6, 2026 at 9:32 pm

    Fake Soothsayer – they'll be more of these from now until the end of 2026. Total BS they're literally still using predictive hallucinating GPT-based LLMs. 'Agents' are still LLMs. Pure BS.

  14. @davidlepold

    April 6, 2026 at 9:32 pm

    Like ur vids, but u start this one with 2 errors. His name, and the claim. If sth is capable of sth it doesn't mean it is already what it s capable to. It means that the basic potential is real. Someone is capable to run a mile doesn't mean he will do it yet. I know it is a fine difference. And maybe I misunderstood. Thx though beyond that

  15. @machinegod3000

    April 6, 2026 at 9:32 pm

    When all claims are true, then yes its AGI – but not the Colossus that pops into existence – its a BABY-AGI, who must learn and grow – so this little thing….still a newborn ..not the BIG ThING yet…but its AGI.

  16. @cacogenicist

    April 6, 2026 at 9:32 pm

    Yeah, this smells like BS. … they didn't, though, actually say they achieved AGI, they said they achieved an "AGI-capable model"

    But as far as I can tell, none of this is new.

  17. @noelwos1071

    April 6, 2026 at 9:32 pm

    I think this is one of the more promising directions we’re seeing right now learning through environment, embodiment, and interaction, rather than just through datasets. That genuinely matters, and it’s good to see serious teams moving there.

    At the same time, I can’t shake the feeling that many projects are still starting from the middle, not from the very beginning.

    When an agent is pushed too early toward competence, performance, or power even inside simulations something essential can be skipped. Before mastering the world, an intelligence should first learn how to be with a world. Not just to see itself reflected back, but to encounter something other than itself.

    Real understanding doesn’t come only from acting, but from being able to imagine consequences before acting not to control them, but to care about them. That’s where responsibility, empathy, and restraint start to grow.

    I’d love to see the biggest players lean more into this idea: if we’re going to build artificial intelligences, then let them grow. Let them evolve inside safe worlds. Let them explore, play, fail, and learn without being handed god-like abilities in a 3D or 4D reality too early.

    Otherwise, we risk becoming the very constraint that blocks real development and possibly our own long-term survival.

    This path feels closer to something sustainable. Not finished, not perfect but closer to a real beginning.

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