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The Limits of Machine Learning

nautil.us

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Re: The Limits of Machine Learning

#31

Post by ilaksh »

djit wrote: post #26
joe_the_user wrote: post #20

Earlier quoted context omitted.

We're not sure what intelligence is, and it is easy to show that it is not "a general ability to solve problems". Humans are great at solving some problems and pretty terrible at others. Now wait a second. I would say humans are better at solving some problems directly and computers programmed by humans are better at solving other problems. However, a computer with a single, fixed program alone will choke completely…

I wonder if trying to emulate"human intelligence" is the way to go. What if we could develop a synthetic form of intelligence distinct from our ability to analyse and solve problems? If I had to build an AI, I would like to "train it" by pitching it against other AIs. Imagine an open AI network where bots will learn by challenging each others. Does such a thing exist?

> where bots will learn by challenging

Many such things exist and have existed for years, just google it.

Also google AGI (artificial general intelligence) or see the videos I linked to on youtube in this thread.

Really the questions you are asking are sort of interesting but it indicates that you are completely unfamiliar with the decades of AI and AGI research that have been done.

Re: The Limits of Machine Learning

#32

Post by xapata »

Animats wrote: post #16
mturmon wrote: post #8

Note to casual commenters: the precise real-world implications of the NFL theorems proved by Wolpert and collaborators have been difficult to appreciate, even to people well-versed in the computational learning world. Starting point: http://www.santafe.edu/media/workingpapers/12-10-017.pdf where we read: "However, arguably, much of that research has missed the most important implications of the theorems."

Is that a corollary of the information theory theorem that for any lossless compressed representation, there must some data pattern for which the compressed representation is bigger?

Anything with more information/entropy requires more space to store.

Re: The Limits of Machine Learning

#33

Post by ilaksh »

AI/AGI is so interesting, everyone (including me) wants to have their own unique take on it. And comment. Even though we are not really that familiar with the field.

I think that the group of researchers who have been calling their work AGI should get a lot of credit, and their research should be a starting point for discussions. Rather than people just spouting off as I am about to do.

Here are some AGI videos https://www.youtube.com/channel/UCCwJ8AV1zMM4j9FTicGimqA/pla...

I think that some type or combination of (deep or something) neural networks, _in_ a general intelligence framework with things like attention, (virtual?) embodiment, etc., may be enough for us to be able to more or less emulate (general) human capabilities and behavior. That's my guess. The biggest issue is slow learning or requiring quite a bit of data. If typical artificial neurons aren't enough, there are actually some promising advances in spiking neural networks some of which are actually able to perform quite accurately and learn much more quickly. So that is another possibility. Can't be sure. I think we should be optimistic that it doesn't require too many more major breakthroughs (if any).

The reason that I think some (many?) people are sooo skeptical still is that deep down they may believe that the cause or explanation for _animalis_ (animus?) is somehow uniquely human or magic. What I mean is the thing that makes animals and people seem (or be) alive and conscious. This is somewhat related to the concept of https://en.wikipedia.org/wiki/Panpsychism which my understanding is somewhat more popular in Asia.

I think that with existing techniques, maybe some type of deep neural net, combined with more dexterous and anatomically correct, dynamic and sensory-integrating robots, we will shortly (if not already) have robots that do seem to be quite alive. Consider a lizard. How many robots do we have that can really emulate the dynamic and lithe behavior and interaction of a lizard? Perhaps none. Our robots are quite slow and generally have limited freedom of movement. I bet that if we did a good job of emulating most of the entire complex anatomy of a lizard with some type of robot (including the breathing) (maybe use some type of EAP muscles like https://www.seas.harvard.edu/news/2016/07/artificial-muscle-...) and then came of up with a way to train its behavior generation as based on a deep neural network from detailed videos of interactions with human handlers, people would say "that thing is alive" and change their minds about the reality of even human-like AIs in the next few decades.

Re: The Limits of Machine Learning

#34

Post by djit »

ilaksh wrote: post #31
djit wrote: post #26

Earlier quoted context omitted.

I wonder if trying to emulate"human intelligence" is the way to go. What if we could develop a synthetic form of intelligence distinct from our ability to analyse and solve problems? If I had to build an AI, I would like to "train it" by pitching it against other AIs. Imagine an open AI network where bots will learn by challenging each others. Does such a thing exist?

> where bots will learn by challenging Many such things exist and have existed for years, just google it. Also google AGI (artificial general intelligence) or see the videos I linked to on youtube in this thread. Really the questions you are asking are sort of interesting but it indicates that you are completely unfamiliar with the decades of AI and AGI research that have been done.

Never claimed any expertise on AI research. Thanks for the suggestion nonetheless.

Re: The Limits of Machine Learning

#35

Post by ppod »

The universe is no narrow thing and the order within it is not constrained by any latitude in its conception to repeat what exists in one part in any other part. Even in this world more things exist without our knowledge than with it and the order in creation which you see is that which you have put there, like a string in a maze, so that you shall not lose your way. For existence has its own order and that no man's mind can compass, that mind itself being but a fact among others.” Cormac McCarthy

Re: The Limits of Machine Learning

#36

Post by visarga »

tree_of_item wrote: post #13
wrong_variable wrote: post #4

How is this article on nautil.us ? Did the author just read the wikipedia.com page on Machine Learning ? There is an entire field in ML called unsupervised learning. Labelling data that do not have labels attached to them. Its not a Fundamental (uggh) limit, I am not sure if the author even knows what Fundamental means, its not like the halting problem, or heat death of the universe. ML is also a very young field wit…

Christopher Columbus didn't discover "an entire new world", he was just one of the first Europeans to land on a continent that had already been there, with plenty of people, for thousands of years.

Well, it was a discovery, but just for Europe. American natives discovered Europe as well.

Re: The Limits of Machine Learning

#37

Post by AndrewOMartin »

ilaksh wrote: post #30
AndrewOMartin wrote: post #27

Earlier quoted context omitted.

Yes. The critiques of AI from Hubert Dreyfus have stood the test of time, those who want to understand or challenge them directly can read What Computers Can't Do (1972, 1979), or even better the updated reprint What Computers Still Can't Do (1992). He's a Heideggarian Philosopher but all you need to know is that modern AI is ignorant of vast swathes of 20th Century investigation into the human mind, and state of bei…

I just read a review of "How Brains Make Up Their Minds. Thanks for mentioning that. It looks like a good book with mostly correct information (based on the review). From the summary, I can tell you that researchers in fields such as AGI, deep learning, robotics, etc. have absolutely been working from many if not all of Freeman's assumptions for years and almost all (if not all) of that has been integrated into vario…

I strongly object to the ideas in that book bring described with the terms such as "higher-level abstractions", "sensory input and action output", and "meaning from global patterns".

As I read it, they were precisely the notions Freeman was arguing against.

There is no "input" when the history of a being, it's current sensitivities and orientation in the environment are all inseparable and mutually defining.

There are no higher level abstractions, and none needed, when you're so poised in a situation with your whole brain and body that any appropriate stimulation is already meaningful.

Freeman, for me turned thought upside down. I.e. we don't go, "I've detected that as being food, so I may eat it", rather we go "I've noticed I interact with all these things in a similar way (e.g. eating) that's how I recognise them as related".

Re: The Limits of Machine Learning

#38

Post by sgt101 »

Animats wrote: post #15

Right, not too helpful. Also, the machine shown in the picture isn't even a computer. It was a special-purpose machine used to read microfilms of mark-sense Census forms and write the results on tape. (I once had a summer job at Census HQ in Suitland MD, and saw the FOSDIC machine.) There are fundamental limits to hill-climbing. So far, nobody has something that just keeps running and continues to get better. Hill-cl…

I think that the work on Leonardo at MIT showed how interaction could provide an alternative way of training an agent, and I think that the ongoing development of SOAR shows how learning can be done as a series of capability creations/integrations by an agent.

It interesting to me how both efforts seem to be peripheral to the main focus of the Machine Learning and Autonomous Agents communities.

Re: The Limits of Machine Learning

#39

Post by ilaksh »

AndrewOMartin wrote: post #37
ilaksh wrote: post #30

Earlier quoted context omitted.

I just read a review of "How Brains Make Up Their Minds. Thanks for mentioning that. It looks like a good book with mostly correct information (based on the review). From the summary, I can tell you that researchers in fields such as AGI, deep learning, robotics, etc. have absolutely been working from many if not all of Freeman's assumptions for years and almost all (if not all) of that has been integrated into vario…

I strongly object to the ideas in that book bring described with the terms such as "higher-level abstractions", "sensory input and action output", and "meaning from global patterns". As I read it, they were precisely the notions Freeman was arguing against. There is no "input" when the history of a being, it's current sensitivities and orientation in the environment are all inseparable and mutually defining. There ar…

Your conclusion aligns with my statements. So I think you are interpreting what I wrote incorrectly.

Re: The Limits of Machine Learning

#40

Post by katherineduh »

visarga wrote: post #36
tree_of_item wrote: post #13

Earlier quoted context omitted.

Christopher Columbus didn't discover "an entire new world", he was just one of the first Europeans to land on a continent that had already been there, with plenty of people, for thousands of years.

Well, it was a discovery, but just for Europe. American natives discovered Europe as well.

It wasn't even a discovery for Europe because Vikings had already been to the Americas in the 10th century.
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