151–160 of 172 posts
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I believe that there was a sort of "learning freeze" for AlphaGo during the Lee Sedol games and there was no manual modification of its strategy either. If I recall correctly this was part of the commentary during the matches so I can't find a good source for it right now.
https://youtu.be/l-GsfyVCBu0?t=2866
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I have always found the idea that there's a hard line between strong and not-strong AI extremely naive. The whole thing is a long gradient of progress. Strong AI is going to creep up on most programmers like the proverbial boiling frog, and internet forums will be full of people denying its existence throughout that process.
> I have always found the idea that there's a hard line between strong and not-strong AI extremely naive You probably haven't studied much or any AI. In my opinion, those who haven't researched a subject don't understand the details and are likely to make more inaccurate predictions than experts.
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Then why not title the article "Alphago is not strong AI"?
Read the article. The title isn't a substitute for reading. It's short because your attention span is short.
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> I have always found the idea that there's a hard line between strong and not-strong AI extremely naive You probably haven't studied much or any AI. In my opinion, those who haven't researched a subject don't understand the details and are likely to make more inaccurate predictions than experts.
What a randomly self-serving assumption to make.
In the past 50 years, AI has seen hundreds of small successes in narrow tasks that used to require humans. But none so far has shown the potential to scale up, generalize, and serve tasks other than the narrow one for which it was designed. Like IBM Watson, AlphaGo too is likely to be consigned to the AI scrapheap in the sky.
BUT... the deep net technique used by AlphaGo shows more promise to solve the remaining unsolved AI tasks than any AI method before it. Yes, we still don't know DL's limits, like whether it can integrate one-shot learning, or build and reuse a diverse knowledgebase, or transfer specific methods to solve new more general problems. But as of right now, it's shown greater promise to solve novel weak AI tasks than any past technique I've seen. The author overlooks that potential deliberately and provocatively, and IMO, pointlessly.
Can DL scale up into strong AI too? I think the important thing here isn't that the answer isn't obviously yes (as the author posits), but that the answer isn't obviously no. And in the 50+ year quest for strong AI, that's a first, at least for me.
The headline for this piece is clickbait. AlphaGo is AI, it's just not strong AI. No AI is strong AI for the moment, but that doesn't mean that the AI we have is uninteresting or a dead end, as the author seems to think. The author and his editors deliberately conflate the two terms in the headline, and clarify after about a paragraph. Sure, AlphaGo is not strong AI. And Abraham Lincoln is dead. And there are lots of…
> Then he makes the point that this requires embodiment, that they have a physical body in space He makes even a stronger curious claim: That "This realization is often called the “embodiment problem” and most researchers in AI now agree that intelligence and embodiment are tightly coupled issues." That makes it sound like it is a consensus between researchers, that strong AI requires a robotic body. Which I doubt.
I'm intrigued by the potential of deep nets to 'simulate' the bases for symbolic grounding using something like thought vectors (TVs), especially if they can be revised and augmented through personal experience. Bootstrapping one's knowledgebase using someone else's rich set of TVs may go a long way for an AI to become grounded vicariously.
The headline for this piece is clickbait. AlphaGo is AI, it's just not strong AI. No AI is strong AI for the moment, but that doesn't mean that the AI we have is uninteresting or a dead end, as the author seems to think. The author and his editors deliberately conflate the two terms in the headline, and clarify after about a paragraph. Sure, AlphaGo is not strong AI. And Abraham Lincoln is dead. And there are lots of…
The first Chomskyan argument looks plausible (though still speculative) to me, but I share your skepticism of the ‘embodiment problem’ claim that a body and rich set of senses are necessary prerequisites. Anyone seduced by that argument should consider the life story of Helen Keller, who did have two-way interaction with the world, but only through the biological equivalent of a teletype.
Helen Keller had smell, taste, touch, and proprioception all functioning. In what way did she have no senses but a teletype?
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I'm not sure about human players, but it might be possible to build an adversarial neural network that beats AlphaGo (and only AlphaGo).
I thought AlphaGo is trained in an adversarial manner already (it plays against itself).
Also the objective was different - they tried to train a network that would play well against any opponent. It should be easier to train a network that exploits some very narrow weakness in specific AlphaGo version.
For example, my phone consistently beats me at chess. But I found a sequence of moves in one opening where is always makes the same mistake, and I after that I can win easily.
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Speaking as an AI researcher, almost nothing is "AI" research. In practice i feel most current AI research falls into two categories: * Fuzzy problems -- image, sound and free text recognition. Where there is no real "true answer". * Problems too hard to solve in a reasonable time without heuristics -- SAT, scheduling, etc. In practice NP-hard problems and further up the complexity heirachy -- AlphaGo goes here. Once…
is there any research into making a "generic" AI that can solve any problem without the researcher first having to know what that problem is? i.e., human style learning.
The headline for this piece is clickbait. AlphaGo is AI, it's just not strong AI. No AI is strong AI for the moment, but that doesn't mean that the AI we have is uninteresting or a dead end, as the author seems to think. The author and his editors deliberately conflate the two terms in the headline, and clarify after about a paragraph. Sure, AlphaGo is not strong AI. And Abraham Lincoln is dead. And there are lots of…
I'll just stick the nomenclature most agree with, "machine learning", and not bother with another superfluous debate
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No, clickbait is "10 ways to find your spouse" This is just a short title, and ITT people didn't read the first paragraph.
There's a clear and meaningful difference between "not AI" and "not strong AI". With respect, you are being pedantic.
I think that's what the author was thinking when he wrote the title, and I'm giving him the benefit of the doubt.
I'm being flexible, not picky. Disagree with me? Fine, I really don't care.