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Meet the algorithm that can learn “everything about anything”

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Re: Meet the algorithm that can learn “everything about anything”

#21

Post by peterwiese »

baddox wrote: post #5
cyborgx7 wrote: post #3

The problem with all approaches to machine learning I see today is that they only focus on grouping and separating concepts based on certain characteristics. They seem to be all fundamentally statistical. None of them seem to work towards a fundamental understanding of what the concepts mean. I'm not sure how that could be accomplished though. Is there even a meaningful distinction to be made between beeing able to i…

I don't think there is a meaningful distinction. Do chess computers have a "fundamental understanding" of chess, which humans traditionally considered a benchmark of human intelligence/strategy? Analogous to the philosophical zombie thought experiment, I think that "real intelligence/understanding" is indistinguishable from simply being able to perform actions to accomplish the same tasks that humans traditionally co…

I appreciate your opinion, because its food for thought, which is always great. Actually, it's really hard to refute your point after giving it some thought. But then again, I am pretty sure that there is a difference. I think it lies in the "universality" of our knowledge creation capabilities. In the end, we (humans) are the ones who fathered (mothered?) the algorithms driving the chess computer. I.e. we discovered an alternative way to reason about problems arising in a play of chess. It turns out, that the alternative solution we discovered, is actually better suited to make a successful move than the one humans use when reasoning about chess problems. This is because there is no "fundamental principle" of a successful chess move. It's all just predictions down different branches of possibilities. This is something a computer is naturally much better at than a human brain. Compare this to problems in different domains, those that cannot be modeled with our mathematical tool set: creativity, morality, consciousness, etc. Those a random concepts that may exist on different levels of emergence, but they are nonetheless real, or at least i'd say there is a consensus among most people that these phenomena have a bearing in reality.

The assumption that our brains are nothing but glorified (bio-) computers naturally leads to the conclusion that there is not a single thing humans can do, that cannot be done by any other equally capable computing platform, be it implemented in silicon-based or dna-based hardware. While I agree with this assumption, you shouldn't be so quick as to assume that we are already at the point where we can effectively re-implement the software which defines a human on any platform. There are a still "hard" problems of which we have no clue at all how to model them, even conceptually. The fact that we can do statistical analysis on an ordinary computer superior to a human doesn't mean much.

Re: Meet the algorithm that can learn “everything about anything”

#23

Post by wfn »

resdirector wrote: post #18
sparky_z wrote: post #15

This strongly reminds me of the first chapter of Greg Egan's Diaspora [1] (which I can't recommend enough) in which newly-formed AIs bootstrap their way to consciousness in part by connecting randomly to an online library and using the various data streams to build up an associative model of the world. [1] http://gregegan.customer.netspace.net.au/DIASPORA/01/Orphano...

Seconded. Diaspora is one of the best sci if books I've read. Highly recommend it (and all of Egan's work) to the HN community.

Thirded. Before Diaspora, I first read "Wang's Carpets"[1] which is a short story of his. Then found out this story had later been incorporated as a chapter into the book. I remember basically immediately ordering said book that night.

fwiw, that "Webly-Supervised Visual Concept Learning" reminds me of the stuff that Hinton et al. do re: unsupervised (concept, etc.) learning (using restricted Boltzmann machines, and so on.) Good talk on the subject (of deep learning, etc.): https://www.youtube.com/watch?v=AyzOUbkUf3M

[1]: read online here: http://bookre.org/reader?file=222997

Re: Meet the algorithm that can learn “everything about anything”

#24

Post by cedias »

Shizka wrote: post #20
cedias wrote: post #13

(Disclaimer: I am not an native english speaker) The title of the article and of the algorithm (learn everything about anything) is a bit misleading. You might believe that it learns everything, period. Actually it's more about finding every variation of a "concept", I quote their website: "a fully automated method that given any concept, e.g., horse, discovers an exhaustive vocabulary for it that explains all variat…

I wonder. If they have an exhaustive vocabulary would it be possible to generate a picture of what the system believes an object to look like? I know that there is something called generative models in machine learning and my guess is that it could be applied here.

Well you'd have to build a probabilistic model for each concepts, whether on pixels or on features, and you could use it to generate images randomly. It might show up some good shapes.

Re: Meet the algorithm that can learn “everything about anything”

#25

Post by cedias »

motyar wrote: post #22

Where is the code? is that opensource? and which programming language it uses?

You have everything here: http://levan.cs.washington.edu/?state=show_about

I quote the readme:

> This is an implementation of the "Learning Everything about Anything" system. The system is implemented in MATLAB, with various helper functions written in Shell, Python, MEX C++ for efficiency reasons. For details about the method, please see [1].

This readme contains instructions on using the code, as well as accessing/using already trained models for various concepts.

For questions concerning the code please contact Santosh Divvala (http://homes.cs.washington.edu/~santosh) at santosh@cs.washington.edu.

The software has been tested on Linux using MATLAB versions R2011a. There may be compatibility issues with older versions of MATLAB. At least 4GB of memory (plus an additional 0.75GB for each parallel matlab worker) is assumed.

Re: Meet the algorithm that can learn “everything about anything”

#26

Post by [deleted] »

gtremper wrote: post #9
cyborgx7 wrote: post #3

The problem with all approaches to machine learning I see today is that they only focus on grouping and separating concepts based on certain characteristics. They seem to be all fundamentally statistical. None of them seem to work towards a fundamental understanding of what the concepts mean. I'm not sure how that could be accomplished though. Is there even a meaningful distinction to be made between beeing able to i…

This reminds me of one of my favorite Dijkstra quotes. "The question of whether machines can think... is about as relevant as the question of whether submarines can swim"

[deleted]

Re: Meet the algorithm that can learn “everything about anything”

#27

Post by MachineElf »

wfn wrote: post #23
resdirector wrote: post #18

Earlier quoted context omitted.

Seconded. Diaspora is one of the best sci if books I've read. Highly recommend it (and all of Egan's work) to the HN community.

Thirded. Before Diaspora, I first read "Wang's Carpets"[1] which is a short story of his. Then found out this story had later been incorporated as a chapter into the book. I remember basically immediately ordering said book that night. fwiw, that "Webly-Supervised Visual Concept Learning" reminds me of the stuff that Hinton et al. do re: unsupervised (concept, etc.) learning (using restricted Boltzmann machines, and…

Umm.. fourthed? I just couldn't help but jump in and also recommend Greg Egan's "Permutation City". That book is just wonderful... think simulation, cellular automata as a model for computation, artificial life and all that other good stuff :).

Also, about the LEVAN thing... given the amount of data available online, both in various structured formats and unstructured formats, don't be surprised if deep learning will yield better and better results moving forward. To me though, they mostly seem evolutionary rather than revolutionary. I mean if you look back at the AI field, during the days before the "AI winter" came, huge amounts of data is one thing researchers back then didn't have available. This is not to say that there haven't been advances in learning algorithms at all recently. ..

Re: Meet the algorithm that can learn “everything about anything”

#28

Post by hyp0 »

cyborgx7 wrote: post #3

The problem with all approaches to machine learning I see today is that they only focus on grouping and separating concepts based on certain characteristics. They seem to be all fundamentally statistical. None of them seem to work towards a fundamental understanding of what the concepts mean. I'm not sure how that could be accomplished though. Is there even a meaningful distinction to be made between beeing able to i…

have you seen chomsky and norvig's debate on this? http://norvig.com/chomsky.html

Re: Meet the algorithm that can learn “everything about anything”

#29

Post by knome »

[deleted] wrote: post #26
gtremper wrote: post #9

Earlier quoted context omitted.

This reminds me of one of my favorite Dijkstra quotes. "The question of whether machines can think... is about as relevant as the question of whether submarines can swim"

[deleted]

Do you happen to natively speak Russian? I've heard that in Russian the word used for people swimming is the same word used for ships sailing.

In English, swimming specifically refers to the motions living organisms use to move in water. Ships instead are said to "sail", even though most do not use sails for power.

Re: Meet the algorithm that can learn “everything about anything”

#30

Post by arethuza »

MachineElf wrote: post #27
wfn wrote: post #23

Earlier quoted context omitted.

Thirded. Before Diaspora, I first read "Wang's Carpets"[1] which is a short story of his. Then found out this story had later been incorporated as a chapter into the book. I remember basically immediately ordering said book that night. fwiw, that "Webly-Supervised Visual Concept Learning" reminds me of the stuff that Hinton et al. do re: unsupervised (concept, etc.) learning (using restricted Boltzmann machines, and…

Umm.. fourthed? I just couldn't help but jump in and also recommend Greg Egan's "Permutation City". That book is just wonderful... think simulation, cellular automata as a model for computation, artificial life and all that other good stuff :). Also, about the LEVAN thing... given the amount of data available online, both in various structured formats and unstructured formats, don't be surprised if deep learning will…

As well as adding my own strong recommedatios for Egan's "Permutation City" and "Diaspora" I would also recommend "Quarantine" - which has a rather splendid idea for mobile apps - "neural mods" that actually augment the brains own congnitive capabilities (including augmenting sensory data for the ultimate in VR).

And there is what one group chooses to do with a very special neural mod...

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