So prescient. I definitely think this will be a thing in the near future ~12-18 months time horizon

And these are consumer options, affordable to you and me, not only to some military. If those are the commonly available options... there may be way more advanced stuff that we haven't seen.

I asked for real examples from someone who claimed to have first hand experience, not more marketing bullshit

y'all are in a religion

https://developer.nvidia.com/isaac/gr00t

What's with this insane desire for anthropomorphism? What do you even MEAN learn in its dreams? Fine-tuning overnight? Just say that!

  > What's with this insane desire for anthropomorphism?

Whether a computational medium is carbon-based or silicon-based seems irrelevant. Call it "carbon-chauvinism".

Since consciousness is closely linked to being a moral patient, it is all the more important to err on the side of caution when denying qualia to other beings.

No-one cares. It's just terminology.

This is generally a bad idea, but a few of the results like "neural networks" did work out… eventually.

"World model" is another example of a metaphor like this. They've assumed that humans have world models (most likely not true), and that if they program something and call it a "world model" it will work the same way (definitely not true) and will be beneficial (possibly true).

(The above critique comes from Phil Agre and David Chapman.)

A neural net can produce information outside of its original data set, but it is all and directly derived from that initial set. There are fundamental information constraints here. You cannot use a neural net to itself generate from its existing data set wholly new and original full quality training data for itself.

You can use a neural net to generate data, and you can train a net on that data, but you'll end up with something which is no good.

There is an uncountably large number of models that perfectly replicate the data they're trained on; some generalize out of distribution much better. Something like dreaming might be a form of regularization: experimenting with simpler structures that perform equally well on training data but generalize better (e.g. by discovering simple algorithms that reproduce the data equally well as pure memorization but require simpler neural circuits than the memorizing circuits).

Once you have those better generalizing circuits, you can generate data that not only matches the input data in quality but potentially exceeds it, if the priors built into the learning algorithm match the real world.

We have truly reached peak hackernews here.

The LLM has plenty of experts and approaches etc.

Give it tool access let it formulate it's own experiments etc.

The only question here is if it becomes a / the singularity because of this, gets stuck in some local minimum or achieves random perfection and random local minimum locations.

Are you sure? I've been ingesting boatloads of high definition multi-sensory real-time data for quite a few decades now, and I hardly remember any of it. Perhaps the average quality/diversity of LLM training data has been higher, but they sure remember a hell of a lot more of it than I ever could.

I.e. if the simulation has enough videos of firefighters breaking glass where it seems to drop instantaneously and in the world sim it always breaks, a firefighter robot might get into a problem when confronted with unbreakable glass, as it expects it to break as always, leading to a loop of trying to shatter the glass instead of performing another action.

To pick an almost trivial example, let's say OCR digit recognition. You'll train on the original data-set, but also on information-preserving skews and other transforms of that data set to add robustness (stretched numbers, rotated numbers, etc.). The core operation here is taking a smallset in some space (original training data) and producing some bigset in that same space (generated training data).

For simple things like digit recognition, we can imagine a lot of transforms as simple algorithms, but one can consider more complex problems and realize that an ML model would be able to do a good job of learning how to generate bigset candidates from the smallset.

It makes me think that Stargate might actually lead to AGI/ASI

Unbelievable. How is this not a miracle? So we're just stumbling onto breakthroughs?

It's basically what every major AI lab head is saying from the start. It's the peanut gallery that keeps saying they are lying to get funding.

Not to detract from what has been done here in any way, but it all seems entirely consistent with the types of progress we have seen.

It's also no surprise to me that it's from Google, who I suspect is better situated than any of its AI competitors, even if it is sometimes slow to show progress publicly.

I think this was the first mention of world models I've seen circa 2018.

This is based on VAEs though.

Hard to fault them as the process towards ASI now appears to be runaway and uncontrollable.

I suppose it depends what you count as "the start". The idea of AI as a real research project has been around since at least the 1950s. And I'm not a programmer or computer scientist, but I'm a philosophy nerd and I know debates about what computers can or can't do started around then. One side of the debate was that it awaited new conceptual and architectural breakthroughs.

I also think you can look at, say, Ted Talks on the topic, with guys like Jeff Hawkins presenting the problem as one of searching for conceptual breakthroughs, and I think similar ideas of such a search have been at the center of Douglas Hofstadter's career.

I think in all those cases, they would have treated "more is different" like an absence of nuance, because there was supposed to be a puzzle to solve (and in a sense there is, and there has been, in terms of vector space and back propagation and so on, but it wasn't necessarily clear that physics could "pop out" emergently from such a foundation).

[1] http://www.incompleteideas.net/IncIdeas/BitterLesson.html

Even if his broader point might be valid (about the most fruitful directions in ML), calling something a "bitter lesson" while insulting a whole field of science is ... something.

Also as someone involved in early RL, he should know better.

We had one breakthrough a couple of years ago with GPT-3, where we found that neural networks / transformers + scale does wonders. Everything else has been a smooth continuous improvement. Compare today's announcement to Genie-2[1] release less than 1 year ago.

The speed is insane, but not surprising if you put in context on how fast AI is advancing. Again, nothing _new_. Just absurdly fast continuous progress.

[1] - https://deepmind.google/discover/blog/genie-2-a-large-scale-...

We don't inherit any software, so cognitive function must bootstrap itself from it's underlying structure alone.

https://media.ccc.de/v/38c3-self-models-of-loving-grace

Hardware and software, as metaphors applied to biology, I think are better understood as a continuum than a binary, and if we don't inherit any software (is that true?), we at least inherit assembly code.

To stay with the metaphor, DNA could be rather understood as firmware that runs on the cell. What I mean with software is the 'mind' that runs on a collection of cells. Things like language, thoughts and ideas.

There is also a second level of software that runs not on a single mind alone, but collection of minds, to form cliques or a societies. But this is not encoded in genes, but in memes.

I think it's like Chomsky said, that we don't learn this infrastructure for understanding language any more than a bird "learns" their feathers. But I might be losing track of what you're suggesting is software in the metaphor. I think I'm broadly on board with your characterization of DNA, the mind and memes generally though.

   > We don't inherit any software

If you say that this is emergent from the "underlying structure alone", doesn't this mean that it would still be "inherited" software (though in this case, maybe we think of it like punch cards).

But then you have things like language or societal customs that are purely 'software'.

A biological example that I like: the neural structures for vision develop almost fully formed from the very beginning. The state of our network at initialization is effectively already functional. I’m not sure to which extent this is true for humans, but it is certainly true for simpler organisms like flies. The way cells achieve this is through some extremely simple growth rules as the structure is being formed for the first time. Different kinds of cells behave almost independently of each other, and it just so happens that the final structure is a perfectly functional eye. I’ve seen animations of this during a conference talk and it was one of the most fascinating things I’ve ever seen. It truly shows how the complexity of a biological organism is just billions of times any human technology. And at the same time, it’s a beautiful illustration of the lack of intelligent design. It’s like watching a Lego assemble by just shaking the pieces.

An example that might be useful: dragonflies lay their eggs in water. Since a dragonfly has like a 4-bit CPU you might be amazed at how it manages to get all the processing required to identify a body of water from a distance into its tiny mind, and also marvel at what sort of JPEG+++ encoding must be used to convey what water looks like from generation to generation.

But they don't do that at all: instead they have eyes that are sensitive to polarized light. The surface of water polarizes reflected light. So do things like polished gravestones. So dragonflies will lay their eggs on gravestones too.

One I like to ponder is: beavers building damns. Do they have an encoded algorithm that knows that they need to damn the river to have a place to live, by gnawing on trees, carrying them to the right place on the river bed, etc? Nope, certainly they don't have that. Perhaps they have teeth that grow so long that they hurt, motivating the animal to gnaw on something solid to wear them down. The only solid thing they have available is a tree.

How do you claim to know this?

Kind of like how a single neuron doesn't do much, but connect 100 billion of them and well...

He seems to me too enthusiastic, such that I feel Google asked him in particular because they trusted him to write very positively.

https://en.wikipedia.org/wiki/Manufacturing_Consent#:~:text=...

https://www.goodreads.com/book/show/12617.Manufacturing_Cons...

The lead in to the quote starts at https://youtu.be/GjENnyQupow?t=662

"I don't say you're self-censoring - I'm sure you believe everything you're saying; but what I'm saying is, if you believed something different, you wouldn't be sitting where you're sitting." -- Noam Chomksy to Andrew Marr

Thank you for finding that link for me :)

https://chomsky.info/19890315/

& you're basically seeing GPT-3 and saying it will never be used in any serious application.. the rate of improvement in their model is insane

Use the CPU and RAM for world state, then pass it off to the model to render.

Regardless of how this is done, Unreal Engine with all of its bells and whistles is toast. That C++ pile of engineering won't outdo something this flexible.

I've been thinking about this a while and it's obvious to me:

Put Minecraft (or something similar) under the hood. You just need data structures to encode the world. To enable mutation, location, and persistence.

If the model is given additional parameters such as a "world mesh", then it can easily persist where things are, what color or texture they should be, etc.

That data structure or server can be running independently on CPU-bound processes. Genie or whatever "world model" you have is just your renderer.

It probably won't happen like this due to monopolistic forces, but a nice future might be a future where you could hot swap renderers between providers yet still be playing the same game as your friends - just with different looks and feels. Experiencing the world differently all at the same time. (It'll probably be winner take all, sadly, or several independent vertical silos.)

If I were Tim Sweeny at Epic Games, I'd immediately drop all work on Unreal Engine and start looking into this tech. Because this is going to shore them up on both the gaming and film fronts.

I think in this context, it could be amazing for game creation.

I’d imagine you would provide item descriptions to vibe-code objects and behavior scripts, set up some initial world state(maps), populated with objects made of objects - hierarchically vibe-modeled, make a few renderings to give inspirational world-feel and textures, and vibe-tune the world until you had the look and feel you want. Then once the textures and models and world were finalised, it would be used as the rendering context.

I think this is a place that there is enough feedback loops and supervision that with decent tools along these lines, you could 100x the efficiency of game development.

It would blow up the game industry, but also spawn a million independent one or two person studios producing some really imaginative niche experiences that could be much, much more expansive (like a AAA title) than the typical indie-studio product.

> It would blow up the game industry, but also spawn a million independent one or two person studios producing some really imaginative niche experiences that could be much, much more expansive (like a AAA title) than the typical indie-studio product.

All video games become Minecraft / Roblox / VRChat. You don't need AAA studios. People can make and share their own games with friends.

Scary realization: YouTube becomes YouGame and Google wins the Internet forever.

I've seen Roblox's creative tools, even their GenAI tools, but they're bolted on. It's the steam powered horse problem.

Can you make a basically indistinguishable copy of other games in Roblox? If so, that’s pretty cool, even without AI integration.

I think this puts Epic Games, Nintendo, and the whole lot into a very tough spot if this tech takes off.

I don't see how Unreal Engine, with its voluminous and labyrinthine tomes of impenetrable legacy C++ code, survives this. Unreal Engine is a mess, gamers are unhappy about it, and it's a PITA to develop with. I certainly hate working with it.

Innovator's Dilemma fast approaching the entire gaming industry and they don't even see it coming it's happening so fast.

Exciting that building games could become as easy as having the idea itself. I'm imagining something like VRChat or Roblox or Fortnite, but where new things are simply spoken into existence.

It's absolutely terrifying that Google has this much power.

This is 100% going to happen on-device. It's just a matter of time.

Maybe just as kind of a DLSS on steroids where the engine only renders very simple objects and a world model translates these to the actual graphics.

https://kylekukshtel.com/diffusion-aaa-gamedev-doom-minecraf...

But even when I wrote that I thought things were still a few years out. I facetiously said that Rockstar would be nerd-sniped on GTA6 by a world model, which sounded crazy a few months ago. But seeing the progress already made since GameNGen and knowing GTA6 is still a year away... maybe it will actually happen.

I'm having trouble parsing your meaning here.

GTA isn't really a "drive on the street simulator", is it? There is deliberate creative and artistic vision that makes the series so enjoyable to play even decades after release, despite the graphics quality becoming more dated every year by AAA standards.

Are you saying someone would "vibe model" a GTAish clone with modern graphics that would overtake the actual GTA6 in popularity? That seems extremely unlikely to me.

I despise the creative and artistic vision of GTA online, but I’m clearly in a minority there gauging by how much money they’ve made off it.

I didn't think the story was earth-shattering; it was fine, but no Baldur's Gate.

Edit: In retrospect, the characters were fairly iconic. I still distinctly remember Trevor.

GTA6 will not actually be nerd-sniped, but it's easy to see how a lot of what makes the game defensible is being rapidly commoditized.

But someone creative having a vision in their head and then just guiding AI to flesh out the assets, details, etc.

GenAI will never get there because it can't, by design. It can riff on what was, and it can please the prompter, but it cannot challenge anyone creatively. No current LLM's can, either. I'll eat my hat if this is wrong in ten years, but it won't be.

It will generate refined slop ad nauseam, and that will train people's brains into spotting said slop faster using less energy. And then it'll be shunned.

I'm starting to think some of the names behind LLMs/GenAI are cover names for aliens and any actual humans involved have signed an NDA that comes with millions of dollars and a death warrant if disobeyed.

Anyways, crafting pretty looking worlds is one thing, but you still need to fill them in with something worth doing, and that's something we haven't really figured out. That's one of the reasons why the sandbox MMORPG was developed as opposed to "themeparks". The underlying systems, the backend is the real meat here. At most with the world models right now is that you're replacing 3d artists and animators, but I would not say that is a real bottleneck in relation to one's own limitations.

https://kylekukshtel.com/game-design-mimetics

Maybe I’m misinterpreting what you’re saying here, but 2021 til present has been a glut of some of the best titles ever made, by pretty much any measure

Not for video games it isn’t.

I for one would love a video game where you're playing in a psychedelic, dream-like fugue.

It is not currently, or near term, realistic to make a video game where a meaningful portion of the simulation is part of the model.

There will probably be a few interactive model-first experiences. But they’ll be popular as short novelties not meaningful or long experiences.

A simple question to consider is how would you adjust a set of simple tunables in a model-first simulator? For example giving the player more health, making enemies deal 2x damage, increasing move speed, etc etc. You can not.

Reality is not composed of words, syntax, and semantics. A human modal is.

Other human modals are sensory only, no language.

So vision learning and energy models that capture the energy to achieve a visual, audio, physical robotics behavior are the only real goal.

Software is for those who read the manual with their new NES game. Where are the words inside us?

Statistical physics of energy to make machine draw the glyphs of language not opionated clustering of language that will close the keyboard and mouse input loop. We're like replicating human work habits. Those are real physical behaviors. Not just descriptions in words.

https://www.theguardian.com/technology/2025/aug/05/google-st...

Gemini Robot launch 4 mo ago:

https://news.ycombinator.com/item?id=43344082