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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”

#11

Post by goblin89 »

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…

> Is there even a meaningful distinction to be made between beeing able to identify a concept and understanding what a concept actually means?

How would you define “understanding” and “actually means” in your question?

See also: http://en.wikipedia.org/wiki/Chinese_room

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

#12

Post by thret »

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…

If fictional media is anything to go by, the single defining aspect of human intelligence is love. This is the last bastion of human understanding that is incomprehensible to evil, machines and aliens.

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

#13

Post by cedias »

(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 variations (i.e., actions, interactions, attributes, etc) that modify its appearance."

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

#14

Post by mattmanser »

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…

What do you want?

Until I can just talk to a computer and it always understands what I'm asking, there's no AI is there? It's a fuzzy concept to exactly define, but it's pretty obvious what we all mean when we talk about it.

Brute forcing billions of moves of chess isn't going to achieve that, so it's nothing more than a cute trick that lay people don't understand is a trick so we have to tell them it is.

David Copperfield can "fly" but he can't just fly on demand, he can only fly in very special circumstances in a tightly controlled environment.

He's no more a flying man than deep blue is a thinking computer.

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

#15

Post by sparky_z »

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...

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

#16

Post by tegeek »

pavpanchekha wrote: post #4
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 is in fact a classic criticism of modern AI. Classic approaches tried to replicate human reasoning mechanisms. The work was very cool, but far harder to understand and scale, compared to modern statistical algorithms. To some extent, you are faced with a choice: a small palette of mediocre techniques whose workings are beautiful theories of the human mind; or, a broadly-applicable, incredibly practical set of to…

I think one of source of intelligence in humans is "imagination".

IMO "Imagination" itself isn't intelligence but an input to the last "intelligent" activity.

Computers can be taught to exhibit different "intelligent" activities and that is AI & Machine learning is all about.

Human imagination works without any knowledge skill or learning (it is just my understanding, and i might be wrong).

Producing rough and wild-west imagination isn't problem of AI.

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

#18

Post by resdirector »

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.

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

#19

Post by herendin »

thret wrote: post #12
baddox wrote: post #5

Earlier quoted context omitted.

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…

If fictional media is anything to go by, the single defining aspect of human intelligence is love. This is the last bastion of human understanding that is incomprehensible to evil, machines and aliens.

Humans can already fall in love with computers and virtual personalities, so we're halfway there

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

#20

Post by Shizka »

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.
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