11–20 of 189 posts
> An international A.I. mission focused on teaching machines to read could genuinely change the world for the better — the more so if it made A.I. a public good, rather than the property of a privileged few. > author: Gary Marcus is a professor of psychology and neural science at New York University. Not sure what he has in mind. There are already a lot of smart people building Q&A systems. We need tests to establish…
What a sigh of relief to read a refreshing take on the real progress of AI. Yes, it's stuck, and that's the real problem of AI, that we haven't been able to do anything significant after perception. However, unlike the author, I don't think the solution is to nationalize AI research (we're not close enough for that), but to fund more non-deeplearning research for 5-10 years, and then we might see some progress in non-perception tasks.
> An international A.I. mission focused on teaching machines to read could genuinely change the world for the better — the more so if it made A.I. a public good, rather than the property of a privileged few. > author: Gary Marcus is a professor of psychology and neural science at New York University. Not sure what he has in mind. There are already a lot of smart people building Q&A systems. We need tests to establish…
Check out Winograd Schema: https://en.wikipedia.org/wiki/Winograd_Schema_Challenge
Overview by an expert: http://www.cs.nyu.edu/faculty/davise/papers/WinogradSchemas/...
An example: The city councilmen refused the demonstrators a permit because they [feared/advocated] violence.
When you switch between "fear" and "violence", the meaning of 'they' change. There are many more examples like this.
The best performance in the first round of the 2016 challenge was 58% by a neural network based system. Random guessing would yield 44% (some questions had more than 2 choices). Human performance was 90.89% with a standard deviation of 7.6%.
Here are the challenge problems used in the first round: http://www.cs.nyu.edu/faculty/davise/papers/WinogradSchemas/...
Human Subject Test Performance: http://www.cs.nyu.edu/faculty/davise/papers/WinogradSchemas/...
Most of the AI progress in last years is just tuning pattern recognition algorithms. We can not expect these algorithms to produce results like humans, because humans have a lot of information not just from percieving the world, but their patterns of thinking are also vastly dependend on the underlying structure of brain, that has developed over milions of years of evolution. If there is a cliff, toddlers are scared…
I don't know about a study proving that, might be true. But from my own experience, toddlers are not afraid of anything until a. they hurt themselves, b. they develop more and understand the concepts like height, c. the parent repeats "no" to them and/or shows them what to do or not to do until they learn.
So there might be evolutionary pre-programming in the human brain, but toddlers brain still needs to develop until those became active. I think there should be more research into how toddlers learn to crawl, stand and walk, how they learn to speak, etc.
That doesn't seem to be very surprising given the limited complexity compared to say a fly's brain. Artificial NNs manage to work because they are highly specialized to a specific task.
Click-baity. AI tech isn't stuck. There are many forthcoming breakthroughs, particularly in medicine, which should really benefit humanity. Radiology is poised to let CNNs make radiologists a lot more efficient. We just need to build the labeled datasets. If we invest heavily in some AI tech, let it be to produce huge medical datasets. The software and hardware is ready. We're only lacking sufficient data to make mor…
Most of the AI progress in last years is just tuning pattern recognition algorithms. We can not expect these algorithms to produce results like humans, because humans have a lot of information not just from percieving the world, but their patterns of thinking are also vastly dependend on the underlying structure of brain, that has developed over milions of years of evolution. If there is a cliff, toddlers are scared…
Not sure if you are a parent, but this isn't the case at all!
Therefore teaching someone/something else how to learn will be almost inherently impossible, because we don't understand it ourselves (yet?)
And if we do learn how to learn, why would we need an AI to do it for us?