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Artificial intelligence pioneer says we need to start over

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Re: Artificial intelligence pioneer says we need to start over

#111

Post by skybrian »

iandanforth wrote: post #22

Brief description of the issue for non-experts: Supervised learning You can judge the output of your network against ground truth. You say that's a cat? Nope, it's a dog! And then slightly adjust your network so it's less likely to give that wrong answer in the future. How exactly you adjust the network is what backpropagation describes (in combination with something called a learning rate). Unsupervised learning You…

Biological brains try to predict the immediate future: what they will sense next. That's the ground truth.

Re: Artificial intelligence pioneer says we need to start over

#112

Post by goatlover »

bryananderson wrote: post #105
goatlover wrote: post #90

Earlier quoted context omitted.

But nature also evolved a bunch of other organisms alongside humans that are fit in their own way. How do you evolve for just the (human level) intelligent entity and not a cockroach or rat? Point is that you're going to end up with a massive ecosystem of organisms if you could fully simulate an evolutionary history. It's not even clear that human level intelligence would evolve. It's only happened once in our planet…

Excellent points! One would have to figure out which evolutionary pressures to apply in order to select for the desired traits. For example, at some point in the past, humans and rats had a common ancestor. That ancestor had two offspring. One offspring's descendants faced a series of evolutionary pressures that led to rats. The other's descendants faced a different series of pressures, leading to humans. The designe…

Sounds like the making of a really interesting game, at the very least.

Re: Artificial intelligence pioneer says we need to start over

#113

Post by dnautics »

red75prime wrote: post #29
dnautics wrote: post #19

Earlier quoted context omitted.

I don't think that's correct. There are a lot of people who should know better that think that the current ml technology will lead to agi.

Let me guess. You think so, because we don't know what the general intelligence is, but the current approaches of ML are surely can't be extended to produce it.

We have some simple models of not even general intelligence that ml can't do. To steal from hofstadter:. Let's say I have a function that maps two strings. I'll give you an example function. "abc" -> "abd". What does "efg" map to? And how do you train current generation of ml to solve those problems in one shot like you just did?

I don't want to knock machine learning. There's a very huge set of very interesting problems that it does solve that were basically intractable till now and we haven't even scratched the surface of applications for. But the existing techniques have understandable restrictions to the scope of soluble problem.

I would also not be surprised if the best models included current ml strategies in some way, for example, in supervisor threads or initial processing of complicated input data into semantic-ish vector valued forms.

Re: Artificial intelligence pioneer says we need to start over

#114

Post by yters »

iandanforth wrote: post #22

Brief description of the issue for non-experts: Supervised learning You can judge the output of your network against ground truth. You say that's a cat? Nope, it's a dog! And then slightly adjust your network so it's less likely to give that wrong answer in the future. How exactly you adjust the network is what backpropagation describes (in combination with something called a learning rate). Unsupervised learning You…

Solomonoff induction captures the algorithm, but it cannot be implemented. Perhaps that means the mind is non algorithmic.

Re: Artificial intelligence pioneer says we need to start over

#115

Post by ezioamf »

bryananderson wrote: post #86

At first glance, the obvious solution seems to be to create intelligence the same way nature did: some sort of evolution. Some sort of algorithm where multiple "networks" mutate and reproduce in some way, in response to some fitness function. Mutations that make a network more fit result in an increased reproductive rate, while other mutations decrease that rate. Evolutionary algorithms have been around for a while b…

How to create intelligent systems are already encoded in human DNA. You just have to find a way to decode it

Re: Artificial intelligence pioneer says we need to start over

#117

Post by makapuf »

dtech wrote: post #98
samfisher83 wrote: post #93

Earlier quoted context omitted.

Well your teachers, parents, society tell you what is right and wrong so we really aren't learning unsupervised.

Also things like pain, hunger and pleasure also are for the most part generated outside of the "learning" parts of the brain, so similar to a pre-defined utility function/oracle.

Yes a 1yo child has a good way of getting feedback from the environment when learning to walk. They fall and it hurts !

Re: Artificial intelligence pioneer says we need to start over

#118

Post by amiramir »

Animats wrote: post #45

Machine learning may be nearing its ceiling. The history of AI goes in cycles. Someone has a good idea which solves some problems, followed by "strong AI Real Soon Now" enthusiasm, followed by that idea hitting its ceiling. AI has been through search, backtracking, the General Problem Solver, hill-climbing, and expert systems. Each was overhyped at the time, and each hit its ceiling. The big difference this time is t…

>How long until the next big idea? The last "AI winter", after expert systems, was 15 years.

Oddly enough neural nets languished in the frozen tundra for 50+ years if you take it back to perceptrons (mid 60's)[1]. Misnky and Papert's take down of perceptrons set the field back years. If you want to be more strict then it's been 31 years since Rummelhart and McClelland published their book[2], based on their earlier work that Hinton co-authored. They laid out multilayer NN with back-propagation. I got hold of the book in the UK in '87 and used it to code a multi-layer back-propagation network. It was a machine that would read out aloud given some text, even for words it had not seen before (good luck with through, though, and trough.) The problems were data and processing speed. I had to hand code features and wait for overnight training runs on VAXen and later a Sun-3 clocked at 16.67MHz[3]. It took big data an brute force to get the glimpses or magic that we see now. The fundamentals have been around for a long time.

It may be the case that one of the many approaches that fell by the wayside will make a comeback a al NN. NN added more layers and tweaked backprop, plus data and speed. It may be the expert systems will rejuvenate as something "new" with machines writing their own rules and somehow getting over showstoppers like the unmanageability of a large rule bases. It's probably going to be some combination of things that we already know about, along with yet more data, and processing power that will get us to the next level. The odds are that whatever that beast is will be self-training and regulating in an analogous way to back-prop but with logic thrown in. Good luck to us all for inventing such things, and for trying to understand what they are really doing.

[1]https://en.wikipedia.org/wiki/Perceptron [2]https://mitpress.mit.edu/books/parallel-distributed-processi... [3]https://en.wikipedia.org/wiki/Sun-3

Re: Artificial intelligence pioneer says we need to start over

#119

Post by tbabb »

It is fantastic to hear this from a seasoned academic about his own field-- People get trapped in orthodoxy and become unconsciously unwilling to explore bold ideas in favor to minor tweaks. The framework of thinking itself becomes precious, but big advances usually come from discarding the old framework in favor of something radically new. The kind of humility and bold thinking needed for that kind of change is rare and hard to foster (especially while still remaining grounded by empiricism).

Re: Artificial intelligence pioneer says we need to start over

#120

Post by inetknght »

tbabb wrote: post #119

It is fantastic to hear this from a seasoned academic about his own field-- People get trapped in orthodoxy and become unconsciously unwilling to explore bold ideas in favor to minor tweaks. The framework of thinking itself becomes precious, but big advances usually come from discarding the old framework in favor of something radically new. The kind of humility and bold thinking needed for that kind of change is rare…

I currently work in DNA analysis. I wholeheartedly agree.
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