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This sounds like a problem that could be solved around the corner with a caveat. Games generally are solvable for AI because they have feedback loops and a cle

This sounds like a problem that could be solved around the corner with a caveat. Games generally are solvable for AI because they have feedback loops and a clear success or failure criteria. If the "picking up a Joystick" part is the limiting factor, sure. But why would we want robots to use an interface (especially a modern controller) heavily optimized for human hands; that seems like the definition of a horseless carriage. I'm sure if you compared a monkey and a dolphins performance using a joystick you'd get results that aren't really correlated with their intelligence. I would guess that if you gave robots an R2D2 like port to jack into and play a game, that problem could be solved relatively quickly.

mellosouls 1y ago
The point isn't about learning video games its about learning tasks unrelated to its specific competency generally.
johnb231 1y ago
No, the joystick part is really not the limiting factor. They’ve already done this with a direct software interface. Physical interface is a new challenge. But overall you are missing the point.
xnickb 1y ago
Just like OpenAI early on promised us an AGI and showed us how it "solved" Dota 2. They also claimed it "learned" to play by playing itself only however it was clear that most of the advanced techniques were borrowed from existing AI and by observing humans. No surprise they gave up on that project completely and I doubt they'll ever engage in anything like that again. Money better spent on different marketing platforms.
- jsheard 1y ago
  It also wasn't even remotely close to learning Dota 2 proper. They ran a massively simplified version of the game where the AI and humans alternated between playing one of two pre-defined team compositions, meaning >90% of the games characters and >99.999999% of the possible compositions and matchups weren't even on the table, plus other standard mechanics were also changed or disabled altogether for the sake of the AI team. Saying you've solved Dota after stripping out nearly all of its complexity is like saying you've solved Chess, but on a version where the back row is all Bishops.
  - xnickb 1y ago
    Exactly. What I find surprising in this story though is not the OpenAI. It's investors not seeing through these blatant.. lets call them exaggerations of the reality and still trusting the company with their money. I know I wouldn't have. But then again, maybe that's why I'm poor.
    - deleted 1y ago
      [deleted]
    - ryandrake 1y ago
      In their hearts, startup investors are like Agent Mulder: they Want To Believe. Especially after they’ve already invested a little. They are willing to overlook obvious exaggerations up to and including fraud, because the alternative is admitting their judgment is not sound. Look at how long Theranos went on! Miraculous product. Attractive young founder with all the right pedigree, credentials, and contacts, dressed in black trurtlenecks. Hell, she even talked like Steve Jobs! Investors never had a chance.
    - jdross 1y ago
      They already have 400 million daily users and a billion people using the product, with billions of consumer subscription revenue, faster than any company ever. They are also aggregating R&D talent at a density never before seen in Silicon Valley That is what investors see. You seem to treat this as a purity contest where you define purity
      - xnickb 1y ago
        I'm speaking about past events. Perhaps I didn't make it clear enough
      - zaphar 1y ago
        Also apparently still not making a profit.
        deleted 1y ago
- fennecfoxy 1y ago
  To be fair humans have had quite a few million years across a growing population to gather all of the knowledge that we have. As we're learning with LLMs, the dataset is what matters - and what's awesome is that you can see that in us, as well! I've read that our evolution is comparatively slow to the rate of knowledge accumulation in the information age - and that what this means is that you can essentially take a caveman, raise them in our modern environment and they'll be just as intelligent as the average human today. But the core of our intelligence is logic/problem solving. We just have to solve higher order problems today, like figuring out how to make that chart in excel do the thing you want, but in days past it was figuring out how to keep the fire lit when it's raining. When you look at it, we've possessed the very core of that problem solving ability for quite a while now. I think that is the key to why we are human, and our close ancestors monkeys are...still just monkeys. It's that problem solving ability that we need to figure out how to produce within ML models, then we'll be cooking with gas!
jappgar 1y ago
A human would learn it faster, and could immediately teach other humans. AI clearly isn't at human level and it's OK to admit it.
jandrese 1y ago
> But why would we want robots to use an interface (especially a modern controller) heavily optimized for human hands; that seems like the definition of a horseless carriage. Elon's response to this is that if we want these androids to replace human jobs then the lowest friction alternative is for the android to be able to do anything a human can do in a human amount of space. A specialized machine is faster and more efficient, but comes with engineering and integration costs that create a barrier to entry. Elon learned this lesson the hard way when he was building out the gigafactories and ended up having to hire a lot of people to do the work while they sorted out the issues with the robots. To someone like Elon a payroll is an ever growing parasite on a companies bottom line, far better if the entire thing is automated.

mellosouls 1y ago

The point isn't about learning video games its about learning tasks unrelated to its specific competency generally.

johnb231 1y ago

No, the joystick part is really not the limiting factor. They’ve already done this with a direct software interface. Physical interface is a new challenge. But overall you are missing the point.

xnickb 1y ago

Just like OpenAI early on promised us an AGI and showed us how it "solved" Dota 2. They also claimed it "learned" to play by playing itself only however it was clear that most of the advanced techniques were borrowed from existing AI and by observing humans. No surprise they gave up on that project completely and I doubt they'll ever engage in anything like that again. Money better spent on different marketing platforms.

jsheard 1y ago
It also wasn't even remotely close to learning Dota 2 proper. They ran a massively simplified version of the game where the AI and humans alternated between playing one of two pre-defined team compositions, meaning >90% of the games characters and >99.999999% of the possible compositions and matchups weren't even on the table, plus other standard mechanics were also changed or disabled altogether for the sake of the AI team. Saying you've solved Dota after stripping out nearly all of its complexity is like saying you've solved Chess, but on a version where the back row is all Bishops.
- xnickb 1y ago
  Exactly. What I find surprising in this story though is not the OpenAI. It's investors not seeing through these blatant.. lets call them exaggerations of the reality and still trusting the company with their money. I know I wouldn't have. But then again, maybe that's why I'm poor.
  - deleted 1y ago
    [deleted]
  - ryandrake 1y ago
    In their hearts, startup investors are like Agent Mulder: they Want To Believe. Especially after they’ve already invested a little. They are willing to overlook obvious exaggerations up to and including fraud, because the alternative is admitting their judgment is not sound. Look at how long Theranos went on! Miraculous product. Attractive young founder with all the right pedigree, credentials, and contacts, dressed in black trurtlenecks. Hell, she even talked like Steve Jobs! Investors never had a chance.
  - jdross 1y ago
    They already have 400 million daily users and a billion people using the product, with billions of consumer subscription revenue, faster than any company ever. They are also aggregating R&D talent at a density never before seen in Silicon Valley That is what investors see. You seem to treat this as a purity contest where you define purity
    - xnickb 1y ago
      I'm speaking about past events. Perhaps I didn't make it clear enough
    - zaphar 1y ago
      Also apparently still not making a profit.
      - deleted 1y ago
fennecfoxy 1y ago
To be fair humans have had quite a few million years across a growing population to gather all of the knowledge that we have. As we're learning with LLMs, the dataset is what matters - and what's awesome is that you can see that in us, as well! I've read that our evolution is comparatively slow to the rate of knowledge accumulation in the information age - and that what this means is that you can essentially take a caveman, raise them in our modern environment and they'll be just as intelligent as the average human today. But the core of our intelligence is logic/problem solving. We just have to solve higher order problems today, like figuring out how to make that chart in excel do the thing you want, but in days past it was figuring out how to keep the fire lit when it's raining. When you look at it, we've possessed the very core of that problem solving ability for quite a while now. I think that is the key to why we are human, and our close ancestors monkeys are...still just monkeys. It's that problem solving ability that we need to figure out how to produce within ML models, then we'll be cooking with gas!

jappgar 1y ago

A human would learn it faster, and could immediately teach other humans. AI clearly isn't at human level and it's OK to admit it.

jandrese 1y ago

> But why would we want robots to use an interface (especially a modern controller) heavily optimized for human hands; that seems like the definition of a horseless carriage. Elon's response to this is that if we want these androids to replace human jobs then the lowest friction alternative is for the android to be able to do anything a human can do in a human amount of space. A specialized machine is faster and more efficient, but comes with engineering and integration costs that create a barrier to entry. Elon learned this lesson the hard way when he was building out the gigafactories and ended up having to hire a lot of people to do the work while they sorted out the issues with the robots. To someone like Elon a payroll is an ever growing parasite on a companies bottom line, far better if the entire thing is automated.