“ Generating unlimited diverse training environments for future general agents” it may seem unlimited but up to a limited point there will be a pattern. I don’t buy that an AI can use a static model and train itself with data generated from it
Genie 2: A large-scale foundation world model
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Re: Genie 2: A large-scale foundation world model
#72What is actually of value here? There's no actual game, it's incredibly expensive to compute, the behavior is erratic.. It's cool because it's new - but that will quickly wear off, and once that's gone, what's left? There's insane amounts of money being spent on this, and for what?
> What is actually of value here?
Noone knows yet. AI technology like this is closer to scientific research than it is to product development. AI is basically new magic, and people are in a "discovery" phase where we are still trying to figure out what is possible. Nothing of value was immediately created when they discovered DNA. Productization came much later when it was combined with other technologies to fit a particular use case.
Re: Genie 2: A large-scale foundation world model
#73This is.. super impressive. I'd like to know how large this model is. I note that the first thing they have it do is talk to agents who can control the world gen; geez - even robots get to play video games while we work. That said; I cannot find any: - architecture explanation - code - technical details - API access information Feels very DeepMind / 2015, and that's a bummer. I think the point of the "we have no moat…
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I honestly disagree. Google is the only FAANG member that has made AI features I actually consider helpful. Furthermore, I think their strategy is heads-and-shoulders above Microsoft and Apple, who are both desperately paying other businesses to do the "AI stuff" for them. Google is at least doing it in-house, and I don't feel at all like they're behind OpenAI's integrations.
Re: Genie 2: A large-scale foundation world model
#74Earlier quoted context omitted.
The things you list for previous centuries aren't limited to the first 20 years
19th century: electromagnetism, the voltaic pile, the double slit experiment for the light wave theory 20th century: general/special relativity, radioactive decay, discovery of the electron 21st century: crisp and deep learning Hard to argue that the big science of the first 20 years of the previous century looks way more impact than crisp and deep learning put TOGETHER.
its called crispr, not crisp.
Re: Genie 2: A large-scale foundation world model
#75Earlier quoted context omitted.
The things you list for previous centuries aren't limited to the first 20 years
19th century: electromagnetism, the voltaic pile, the double slit experiment for the light wave theory 20th century: general/special relativity, radioactive decay, discovery of the electron 21st century: crisp and deep learning Hard to argue that the big science of the first 20 years of the previous century looks way more impact than crisp and deep learning put TOGETHER.
100 years later, sure. What about in December 1924?
Re: Genie 2: A large-scale foundation world model
#76what for world models be equivalent of ChatGPT for LLM to really blow up in utility?
Re: Genie 2: A large-scale foundation world model
#77Wow.. I can't even imagine where we'll be in 5 or 10 years from now. Seems that it's only "consistent" up to a minute, but if the progress keeps the same rate.. just wow.
Progress is not linear. For all we know, in 2027 things will slow down to a virtual halt for the next 30 years. Look at how much big science progressed in the first 20 years of the 19th century/20th century and look how little it has progressed in the first 20 years of this century. We are on the downlow compared to the last centuries and even if you look at crisp or deep learning, they are not as impactful NOW as le…
>Look how little it has progressed in the first 20 years of this century
This is naivete on the scale of "Cars were much safer 70 years ago".
Re: Genie 2: A large-scale foundation world model
#78As impressive as this might seem let's think about fundamentals.
Statistical models will output a compressed mishmash of what they were trained on.
No matter how hard they try to cover that inherent basic reality, it is still there.
Not to mention the upkeep of training on new "creative" material on a regular basis and the never ending bugs due to non-determinism. Aside from contrived cases for looking up and synthesizing information (Search Engine 2.0).
The Tech Industry is over investing in this area exposing an inherent bias towards output rather than solving actual problems for humanity.
Re: Genie 2: A large-scale foundation world model
#79What is actually of value here? There's no actual game, it's incredibly expensive to compute, the behavior is erratic.. It's cool because it's new - but that will quickly wear off, and once that's gone, what's left? There's insane amounts of money being spent on this, and for what?
Well, what's next? Beyond prototyping, I imagine this is an early step towards more practical agents building their own world model. Better problem solving.
Prompt: Here's a blueprint of my new house and a photo of my existing furniture. Show me some interior design options.
Re: Genie 2: A large-scale foundation world model
#80I doubt it, but it would be interesting if they recorded Stadia sessions and trained on that data (... somehow removing the hud?), seems like it would be the easiest way for them to get the data for this.