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| ▲ | jsheard 11 hours ago | parent | next [-] | | 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 11 hours ago | parent | next [-] | | 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. | | |
| ▲ | ryandrake 10 hours ago | parent | next [-] | | 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. | |
| ▲ | 11 hours ago | parent | prev | next [-] | | [deleted] | |
| ▲ | jdross 10 hours ago | parent | prev [-] | | 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 | | |
| ▲ | zaphar 9 hours ago | parent | next [-] | | Also apparently still not making a profit. | | | |
| ▲ | xnickb 10 hours ago | parent | prev [-] | | I'm speaking about past events. Perhaps I didn't make it clear enough |
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| ▲ | rowanG077 9 hours ago | parent | prev | next [-] | | I agree that restricting the hero pool is a huge simplification. But they did play full 5v5 standard dota with just a restricted hero pool of 17 heroes and no illusions/control units according to theverge (https://www.theverge.com/2019/4/13/18309459/openai-five-dota...). It destroyed the professionals. As an ex dota player, I don't think this is that far off from having full on, all heroes dota. Certainly not as far of as you are making it sound. And dota is one of the most complex games, I expect for example that an AI would instantly solve CS since aim is such a large part of the game. | | |
| ▲ | Jensson 8 hours ago | parent | next [-] | | > It destroyed the professionals. Only the first time, later when it played better players it always lost. Players learned the faults of the AI after some time in game and the AI had very bad late game so they always won later. | | | |
| ▲ | mistercheph 8 hours ago | parent | prev [-] | | Another issue with the approach is that the model had direct access to game data, that is simply an unfair competitive advantage in dota, and it is obvious why that advantage would be unfair in CS. It is certainly possible, but
i won't be impressed by anything "playing CS" that isn't running a vision model on a display and moving a mouse, because that is the game. The game is not abstractly reacting to enemy positions and relocating the cursor, it's looking at a screen, seeing where the baddy is and then using this interface (the mouse) to get the cursor there as quickly as possible. It would be like letting an AI plot its position on the field and what action its taking during a football match and then saying "Look, The AI would have scored dozens of times in this simulation, it is the greatest soccer player in the world!" No, sorry, the game actually requires you to locomote, abstractly describing your position may be fun but it's not the game | | |
| ▲ | rowanG077 8 hours ago | parent [-] | | Did you read the paper? It had access to the dota 2 bot API, which is some gamestate but very far from all gamestate. It also had artifially limited reaction to something like 220ms, worse then professional gamers. But then again, that is precisely the point. A chess bot also has access to gigabytes of perfect working memory. I don't see people complaining about that. It's perfectly valid to judge the best an AI can do vs the best a human can do. It's not really fair to take away exactly what a computer is good at from an AI and then say: "Look but the AI is now worse". Else you would also have to do it the other way around. How well could a human play dota if it only had access to the bot API. I don't think they would do well at all. | | |
| ▲ | lukeschlather 3 hours ago | parent [-] | | > But then again, that is precisely the point. A chess bot also has access to gigabytes of perfect working memory. I don't see people complaining about that. There are ~86 billion neurons in the human brain. If we assume each neuron stores a single bit a human also has access to gigabytes of working memory. If we assume each synapse is a bit that's terabytes. Petabytes is not unreasonable assuming 1kb of storage per synapse. (And more than 1kb is also not unreasonable.) The whole point of the exercise is figuring out how much memory compares to a human brain. |
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| ▲ | scotty79 11 hours ago | parent | prev [-] | | It was 6 years ago. I'm sure now there'd be no contest now if OpenAI dedicated resources to it, which it won't because it's busy with solving entirety of human language before others eat their lunch. | | |
| ▲ | spektral23 10 hours ago | parent | next [-] | | Funnily enough, even dota2 has grown much more complex than it was 6 years ago, so it's a harder problem to solve today than it was back then | |
| ▲ | xnickb 11 hours ago | parent | prev [-] | | What do you base your certainty on? Were there any significant enough breakthroughs in the AGI? | | |
| ▲ | scotty79 10 hours ago | parent [-] | | ARC-AGI, while imagined as super hard for AI, was beaten enough that they had to come up with ARC-AGI-2. | | |
| ▲ | hbsbsbsndk 10 hours ago | parent [-] | | "AI tend to be brittle and optimized for specific tasks, so we made a new specific task and then someone optimized for it" isn't some kind of gotcha. Once ARC puzzles became a benchmark they ceased to be meaningful WRT "AGI". | | |
| ▲ | scotty79 5 hours ago | parent [-] | | So if DOTA became a benchmark same way Chess or Go became earlier it would be promptly beaten. It just didn't stick before people moved to more useful "games". |
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| ▲ | fennecfoxy 6 hours ago | parent | prev [-] | | 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! |
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