Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Schmidhuber: "Well, large language models are far from AGI. LLMs large language models such as ChatGPT. They are just a clever way of indexing the world's existing human generated knowledge, such that it can easily be addressed through in a way that humans are familiar with, which is natural...

28,715 Aufrufe • vor 1 Jahr •via X (Twitter)

13 Kommentare

Profilbild von Debunk the AI Bubble
Debunk the AI Bubblevor 4 Tagen

I think we should be sharper, and state clearly that whatever AGI means, LLM (statistical modeled implemented algorithmically and calibrated on text) CANNOT possibly "do" it. It is the natural consequence of the embedded training requirement. All LLM do is linguistic fluency.

Profilbild von Tom Backert
Tom Backertvor 3 Tagen

@SchmidhuberAI So now that we are close to a generally intelligent system, we change the definition of AGI to include physical? That’s the problem with a vague but widely used term that has no real consensus: it just gets redefined every time reality gets close.

Profilbild von AgentMux
AgentMuxvor 4 Tagen

Brilliant! Schmiddy is always spot on.

Profilbild von ∇∂η Γλ 大汶口
∇∂η Γλ 大汶口vor 3 Tagen

How many unlocked doors of varying designs and approaches can a robot passthru in a minute as a standard test?

Profilbild von Think_Different_
Think_Different_vor 3 Tagen

@SchmidhuberAI Not sure if this view is as relevant today…GPT-6 Astra just posted a huge robotics score.

Profilbild von Clark Dodsworth
Clark Dodsworthvor 3 Tagen

. . . you left out the Global Grand Larceny part.

Profilbild von Michael Wong
Michael Wongvor 3 Tagen

For now, it's better suited for desktop tasks like summarization and content creation.

Profilbild von Naree Suwannarak
Naree Suwannarakvor 4 Tagen

It's like, AI can already ace those desk jobs, but true AGI is about navigating the messy physical world, which is way harder.

Profilbild von Oldrich Senkyr
Oldrich Senkyrvor 3 Tagen

@SchmidhuberAI Is there ny hypothesis stating AGi can’t be achieved by clever indexing of human knowledge. How about using LLM to generate some more knowledge. That garbage code I see all over is a manifestation of it.

Profilbild von Klaus Schmid
Klaus Schmidvor 3 Tagen

It's funny whenever major breakthroughs are made, the definition of AGI moves on..

Profilbild von Kevin Renaud
Kevin Renaudvor 3 Tagen

Business agrees. They are beginning to see AI doesn't work so well in some applications, and switching back to human workers.

Profilbild von kywan mont
kywan montvor 4 Tagen

👽 Clearer index has triggered HF & wiki incidents. 🙈 A technological experiment involving all of humanity. let this technological mold spreading.

Profilbild von taichnocrat (L/0)
taichnocrat (L/0)vor 3 Tagen

@MrEwanMorrison So AI can’t drive a car ?

Ähnliche Videos

Without World Models, There Is No AGI. Google Just Proved It. If AGI ever happens, it will not come from bigger chatbots alone. From the very start of this interview, one thing is crystal clear: without world models, we will never reach AGI. And right now, Google is leading with its world simulator Genie 3. Here is the core of what Demis Hassabis explains in this conversation: • World models are the missing core of AGI Hassabis says his deepest long term focus has always been world models and simulations. Not just language. Not just prediction. Actual internal simulations of reality. • LLMs are impressive, but incomplete Language models understand more about the world than expected because human language encodes a lot of reality. Still, language is only a shadow of the real thing. • What text can never fully teach Reality includes things text struggles to express: •3D space and spatial dynamics •Physical causality and mechanics •Sensorimotor experience like movement, force, smell, or balance • Experience beats description To close the gap, AI must learn from interaction and experience, not just static text. That is how you build an internal world simulator. • Why Genie 3 matters With Google DeepMind pushing systems like Genie 3, AI starts to model reality itself, not just talk about it. • Robots and real world assistants depend on this True robotics, smart glasses, and universal assistants require AI that understands the physical world you live in, not just your screen. Bottom line: AGI will not emerge from better text prediction. It will emerge from systems that can simulate, predict, and understand reality itself. Right now, Google is clearly ahead on that path. Curious what you think. Are world models the real AGI unlock, or just another stepping stone?

VraserX e/acc

23,784 Aufrufe • vor 8 Monaten

Demis Hassabis on the limit in today’s AI: language can describe the world, but it cannot contain it - and why "World Models" are his "longest standing passion". Language models absorbed far more structure about reality from text than many researchers expected, because human language quietly carries physics, psychology, culture, tools, plans, and cause-and-effect. But text is still a compressed residue of experience, not experience itself. A sentence can say a cup falls from a table, yet it does not fully encode weight, grip, balance, friction, timing, sound, surprise, or the tiny motor corrections a body makes before it even notices them. The world is not only made of facts that can be named; it is made of constraints that have to be lived through, touched, predicted, violated, and repaired. That is why world models matter. They aim to learn the hidden grammar of physical reality: how objects persist, how forces unfold, how space changes when an agent moves, and how action creates feedback. Language models can often reason about the world because people have written so much about it. World models try to learn what the world is like before it becomes words. The difference is exactly what matters because intelligence is not just answering well; it is knowing what would happen next if you moved, reached, pushed, smelled, slipped, or failed. A mind trained only on descriptions may become brilliant at explanation. A mind trained on experience may become better at consequence. --- Full video from "Google DeepMind" and "Hannah Fry" YT channel (link in comment)

Rohan Paul

49,938 Aufrufe • vor 3 Monaten