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Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

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Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#21

Post by sharemywin »

jonathanstrange wrote: post #6

Maybe good AI requires a combination of symbolic approaches for the knowledge representation, deep parsing for NLP and semantics/discourse models, and machine learning for pattern recognition tasks of any kind. The currently trendy "AI" looks more like massive data mining with powerful ML to me, that's very good for certain tasks but brings us nowhere near real AI. The knowledge representation problem has not yet bee…

AGI will need to be able to learn and represent any symbol system, just like we can. And it doesn't have to be that good at it(we arn't). There's millions of knowledge bases all around. You'll need something with a generative imagination. We model so much more than labels and relation ships.

Imagine a speech, by president Obama. Where you can actually hear his words. or imagine a ball dropping. We just use words to convey the basic idea. How many hairs does a bald person have?

And if we have a misunderstanding we just adjust our system. New word we use context, including social context etc.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#22

Post by goatlover »

YeGoblynQueenne wrote: post #11
jonathanstrange wrote: post #6

Maybe good AI requires a combination of symbolic approaches for the knowledge representation, deep parsing for NLP and semantics/discourse models, and machine learning for pattern recognition tasks of any kind. The currently trendy "AI" looks more like massive data mining with powerful ML to me, that's very good for certain tasks but brings us nowhere near real AI. The knowledge representation problem has not yet bee…

>> Generally speaking, logical modelling is too limited for good concept representations In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language. The problem is that in practice it is very hard to transfer into a logic language all the knowledge you might need for a useful system. In fact, this was one motivation for at least one branch of machine le…

> In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language.

I doubt this is the case since natural language makes a lot of use of metaphors, and our concepts are probably mostly based on the types of bodies we have and how we interact with the world. See embodied cognition and writings of Lakoff and Mark Johnson.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#23

Post by sgt101 »

goatlover wrote: post #22
YeGoblynQueenne wrote: post #11

Earlier quoted context omitted.

>> Generally speaking, logical modelling is too limited for good concept representations In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language. The problem is that in practice it is very hard to transfer into a logic language all the knowledge you might need for a useful system. In fact, this was one motivation for at least one branch of machine le…

> In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language. I doubt this is the case since natural language makes a lot of use of metaphors, and our concepts are probably mostly based on the types of bodies we have and how we interact with the world. See embodied cognition and writings of Lakoff and Mark Johnson.

In principle, but not consistently over various cases. Wikipedia shows some examples where it breaks down

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#24

Post by gremlinsinc »

One problem with ai (or general ai) is ai lives in a box, it experiences what we tell it to experience, unlike a child who learns organically with what it's exposed to randomly while trying to survive and thrive.

Perhaps the answer is to figure out all the things that make people tick via deep learning and other techniques, build one huge open api/db for vision/audio/movement in 3d planes/ethics/morality/understanding/discernment/language and then a more general ai could simply send out calls to api's of data already trained on specific foundations and create a 'whole' brain from multiple 'sub' brains (pre-learned open knowledge).

Unless we literally learn to clone the human brain technologically, in it's entirety.

I think another issue is not all working in AI are neuroscientists, and it may take understanding every mapped out facet of the human brain to come close to re-creating that in humans, it all can't be deep learning unfortunately, because that's not how we learn and we're the best guess solution to 'intelligence' as the only intelligent race (we know of) in the universe.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#25

Post by bglazer »

YeGoblynQueenne wrote: post #11
jonathanstrange wrote: post #6

Maybe good AI requires a combination of symbolic approaches for the knowledge representation, deep parsing for NLP and semantics/discourse models, and machine learning for pattern recognition tasks of any kind. The currently trendy "AI" looks more like massive data mining with powerful ML to me, that's very good for certain tasks but brings us nowhere near real AI. The knowledge representation problem has not yet bee…

>> Generally speaking, logical modelling is too limited for good concept representations In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language. The problem is that in practice it is very hard to transfer into a logic language all the knowledge you might need for a useful system. In fact, this was one motivation for at least one branch of machine le…

I agree totally that a "non-pure" deep learning approach is going to be necessary in pushing the field forward. World shattering results from new deep architectures like AlexNet are becoming more and more rare and improvements are becoming incremental. Language models, for example, showed some impressive results in recent years, but we're still a long long way from generating realistic and useful text. I'm not sure if throwing more data at larger architectures will get us there. Maybe, maybe not.

The work by Tenenbaum at MIT is a particularly interesting mix of psychology, computational statistics, and neuroscience. It really challenges the commonly repeated notion that neural networks are completely unrelated to actual brains.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#26

Post by YeGoblynQueenne »

paganel wrote: post #19
YeGoblynQueenne wrote: post #11

Earlier quoted context omitted.

>> Generally speaking, logical modelling is too limited for good concept representations In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language. The problem is that in practice it is very hard to transfer into a logic language all the knowledge you might need for a useful system. In fact, this was one motivation for at least one branch of machine le…

> In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language. Is there any proof about an existing non-leaky abstraction between natural language and First Order Logic (or logic in general)? Afaik there is none, but I might me wrong. For example (one amongst thousands): “I don’t like you” can actually mean (and it often does) the exact opposite, and the…

Well, going by formal language theory, FOL is equivalent to a universal Turing machine, which is probably also the full expressive power of human language. Therefore, everything that can be said in human language should in principle be possible to say in FOL. I don't think this is controversial.

Notice again that I don't think this is feasible in practice. At least not with hand-crafted FOL expressions and certainly not with existing technology.

I'm not sure what "non-leaky abstraction" means. Would formal language theory fit the bill?

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#27

Post by narag »

paganel wrote: post #19
YeGoblynQueenne wrote: post #11

Earlier quoted context omitted.

>> Generally speaking, logical modelling is too limited for good concept representations In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language. The problem is that in practice it is very hard to transfer into a logic language all the knowledge you might need for a useful system. In fact, this was one motivation for at least one branch of machine le…

> In principle, First Order Logic and equivalent languages can represent anything that can be represented in natural language. Is there any proof about an existing non-leaky abstraction between natural language and First Order Logic (or logic in general)? Afaik there is none, but I might me wrong. For example (one amongst thousands): “I don’t like you” can actually mean (and it often does) the exact opposite, and the…

Does it matter, though? Understanding sarcasm or other forms of language twisting seems like only important for a very advanced and specific set of applications. There's another post in the front page about the death of a gorilla that was able to do signs language. I'm sure nobody cared if he could catch jokes.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#28

Post by choxi »

gremlinsinc wrote: post #24

One problem with ai (or general ai) is ai lives in a box, it experiences what we tell it to experience, unlike a child who learns organically with what it's exposed to randomly while trying to survive and thrive. Perhaps the answer is to figure out all the things that make people tick via deep learning and other techniques, build one huge open api/db for vision/audio/movement in 3d planes/ethics/morality/understandin…

> it all can't be deep learning unfortunately, because that's not how we learn

If you could humor me, why can't it all be deep learning? It seems like a robust model for how we learn: we start with some priors (random weights), experience something that either confirms or negates those priors (sampling), and then adjust our priors based on that experience.

Of course there are a wide variety of architectures and the human brain is more sophisticated than one conv net. Our brains have on the order of 100 billion neurons and I believe the largest neural networks are on the order of 10's of millions. I would argue that a combination of better architectures and scale could simulate human intelligence.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#29

Post by russdill »

gremlinsinc wrote: post #24

One problem with ai (or general ai) is ai lives in a box, it experiences what we tell it to experience, unlike a child who learns organically with what it's exposed to randomly while trying to survive and thrive. Perhaps the answer is to figure out all the things that make people tick via deep learning and other techniques, build one huge open api/db for vision/audio/movement in 3d planes/ethics/morality/understandin…

Seen a few people claim from time to time that real world experience is the "special sauce" of general AI. I've never seen anything to substantiate this claim. We all live in a box, we all experience our world through simple electrical signals.

Other than being unsubstantiated, the real world only runs at 1x, simulated world can run at any rate your computing platform supports.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#30

Post by pessimizer »

gremlinsinc wrote: post #24

One problem with ai (or general ai) is ai lives in a box, it experiences what we tell it to experience, unlike a child who learns organically with what it's exposed to randomly while trying to survive and thrive. Perhaps the answer is to figure out all the things that make people tick via deep learning and other techniques, build one huge open api/db for vision/audio/movement in 3d planes/ethics/morality/understandin…

Have you ever done any reading about "embodied cognition"?

https://blogs.scientificamerican.com/guest-blog/a-brief-guid...

It seems there's nothing logical about human cognition, it just ends up resembling logic because movement through space either works or it doesn't, and humans have the ability to assign physical analogies to abstractions and to respond to those metaphors with the same heuristics and physical reflexes that it was born with; heuristics and reflexes designed over a few billion years to allow your ancestors to survive and reproduce.

The problem with training things on artificial datasets is that they are not rich (resolution is too low) or surprising (generated by simple algorithms.) An AI that worked as well as the human brain would just end up reading them back to you. The real world is, information-wise, incompressible. It has such fine distinctions that its impossible to examine them beyond a certain level without the act of observation changing them.

I always thought there was some potential in using robotic bodies with good sensors that fed into some processing theory of mind in order to grow an AI.

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