Earlier quoted context omitted.
Language is a set of behaviors Behavior for humans and other animals requires a brain and body (almost always) The organisation, growth, and function of the brain and body are influenced by genetics. So we can say first and formost that language is influenced by genetics. Having a tongue, vocal chords, hands, ears. These all help to acquire language. So now the question is to what degree does genetics influence langu…
What's really fascinating is wild chimps use a rich form of communication that's far from an actual language. But, they can be trained use complex sign langue which they will then use to communicate with each other. So, language may have developed fairly rapidly relative to the underlying biology.
Noam Chomsky on Where Artificial Intelligence Went Wrong
111–120 of 184 posts
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#112The field is now called AGI. It isn't mentioned in this article. Everyone seems to be ignoring the whole field of AGI (artificial general intelligence). Or maybe they truly are ignorant of it. Anyway, suffice to say, AI and AGI didn't stop progressing, and Chomsky is no longer any sort of expert in those fields. Even Norvig isn't up to speed on the most advanced approaches to AGI, but at least he enters the same room…
I've heard of OpenCog before and it, along with the Singularity crowd gives me a weird amateur, bullshitty, vague, generalist feeling that Noam Chomsky does. Basically - where's the beef? What has been done by either crowd apart from taking credit from those who do things in the actual industry/real world? My fundamental aversion to both OpenCog and the entire Singularity crowd is a) their statements are so general a…
http://en.wikipedia.org/wiki/Noam_Chomsky_bibliography
He's no quack.
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#113Earlier quoted context omitted.
AI has forever been filled with buzzwords and trendy absurdity. Most of this lies on the soft computing end of the field, where self-styled visionaries hold forth with holistic mumbo-jumbo while valuable work is done by reputable researchers elsewhere. AGI is one of those little goofy microtrends: so far as I can tell it's essentially a rebranding of Strong AI by soft computing reactionaries responding to AI getting…
I thoroughly agree - see my comment above. The Singularity and SENS peeps give me the exact same feeling - as does Noam Chomsky. All talk - no walk. I think it's fundamentally the difference between soft bullshit and hard calculations. Everyone can talk about AI, or linguistics, or statistics (or any complex field) in very general, undefined and bullshitty terms. But what we need, and what the machine learning guys a…
Chomsky's a pretty substantial walker.
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#114Earlier quoted context omitted.
What do you think of http://en.wikipedia.org/wiki/Nicaraguan_Sign_Language ? It certainly makes me doubt language (the technology of it) as purely cultural and learned.
Language is a set of behaviors Behavior for humans and other animals requires a brain and body (almost always) The organisation, growth, and function of the brain and body are influenced by genetics. So we can say first and formost that language is influenced by genetics. Having a tongue, vocal chords, hands, ears. These all help to acquire language. So now the question is to what degree does genetics influence langu…
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#115Earlier quoted context omitted.
I've heard of OpenCog before and it, along with the Singularity crowd gives me a weird amateur, bullshitty, vague, generalist feeling that Noam Chomsky does. Basically - where's the beef? What has been done by either crowd apart from taking credit from those who do things in the actual industry/real world? My fundamental aversion to both OpenCog and the entire Singularity crowd is a) their statements are so general a…
So I figured it out. Basically, they take the idea of AGI seriously, and actually consider and talk about the repercussions, and therefore you dismiss them and their ideas as fringe and not worth investigating. I know that, because if you had investigated at all, you would see that all of those projects had really interesting results and these people are not being vague and hand-waving. Not all of those projects I li…
I know Chomsky is a serious scientist with considerable accomplishment.
I have seen totally loony stuff in videos of AGI conferences (Tachyons and stuff). Open Cog may be better than that. But it hasn't proved that it is better than that.
The 1970-80's AI involved the Chomskyan paradigm of "draw up a naive design of the mind and/or brain and implement it". That failed so badly that you need a really good argument why you can do things differently - at least to move into mainstream science. That is, Ben Goertzel seems nice, smart and enthusiastic but I can't see him bringing anything new to the "table". Jeff Hawkins had interesting ideas with his temporal paradigm but it seemed like the model he chose to instantiate wasn't all that different from that used by the statistical-brute-force crowd. And Numenta has had really few announcements for a six year old enterprise.
And the companies paying for AI to be added to their systems. That happened from the start but it wasn't ever enough. What's different here from the stuff from twenty years ago?
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#116Earlier quoted context omitted.
> His contributions to science are negligible if not entirely detrimental. I think it would be nice to have some more references or more explanation before declaring Chomsky detrimental to science.
He dominated the field of linguistics for decades with anti-empiricist theories. You could argue that the popularity of his ideas held back alternative approaches; hence his contributions could be considered detrimental.
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#117Earlier quoted context omitted.
I thoroughly agree - see my comment above. The Singularity and SENS peeps give me the exact same feeling - as does Noam Chomsky. All talk - no walk. I think it's fundamentally the difference between soft bullshit and hard calculations. Everyone can talk about AI, or linguistics, or statistics (or any complex field) in very general, undefined and bullshitty terms. But what we need, and what the machine learning guys a…
http://en.wikipedia.org/wiki/Noam_Chomsky_bibliography Chomsky's a pretty substantial walker.
> Every time I fire a linguist, the performance of the speech recognizer goes up.
-- http://en.wikipedia.org/wiki/Frederick_Jelinek
I still don't see Chomsky robots walking around, Chomsky translation translating my text to French or Chomsky AI driving cars. Nope - all Google/IBM/Microsoft/DARPA/Boston Dynamics/etc. AKA Hard science-engineers utilising statistics, not soft science blowhards.
Only thing I see Chomsky doing is talk - a lot.
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#118Chomsky is right up there with Minsky in being part of the problem. His ideas about language being part of the genome are fanciful nonsense. Skinner produce reams of reproducible empirical observations of behavior which are, today, critical to the evaluation of the performance of AIs. Chomsky has produced interesting theories, but mostly derailed linguistics on the basis of the argument 'language is complicated, some…
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#119Earlier quoted context omitted.
I've heard of OpenCog before and it, along with the Singularity crowd gives me a weird amateur, bullshitty, vague, generalist feeling that Noam Chomsky does. Basically - where's the beef? What has been done by either crowd apart from taking credit from those who do things in the actual industry/real world? My fundamental aversion to both OpenCog and the entire Singularity crowd is a) their statements are so general a…
Chomsky's expertise is in linguistics and political analysis. Stephen Pinker's The Language Instinct is a good, readable introduction to some of Chomsky's work (and the wider field to which he is pivotal.) Chomsky's Manufacturing Consent is probably his classic work of political analysis. http://en.wikipedia.org/wiki/Noam_Chomsky_bibliography He's no quack.
> are effective and powerful ideological institutions that carry out a system-supportive propaganda function by reliance on market forces, internalized assumptions, and self-censorship, and without overt coercion
-- http://en.wikipedia.org/wiki/Manufacturing_Consent:_The_Poli...
That's pretty self-evident to the point of being, well, pointless - admen of the 60s made their bread using this, and the PR pioneers of the 30s were already experts. But please let's all listen to what he has to say next. Let me guess: killing people is bad, and not killing people is good. If you call that amazing thinking, I'd hate to see the idiotic version.
Even better:
> Geoffrey Sampson maintains that universal grammar theories are not falsifiable and are therefore pseudoscientific theory. He argues that the grammatical "rules" linguists posit are simply post-hoc observations about existing languages, rather than predictions about what is possible in a language. Similarly, Jeffrey Elman argues that the unlearnability of languages assumed by Universal Grammar is based on a too-strict, "worst-case" model of grammar, that is not in keeping with any actual grammar. In keeping with these points, James Hurford argues that the postulate of a language acquisition device (LAD) essentially amounts to the trivial claim that languages are learnt by humans, and thus, that the LAD is less a theory than an explanandum looking for theories.
Sampson, Roediger, Elman and Hurford are hardly alone in suggesting that several of the basic assumptions of Universal Grammar are unfounded. Indeed, a growing number of language acquisition researchers argue that the very idea of a strict rule-based grammar in any language flies in the face of what is known about how languages are spoken and how languages evolve over time. For instance, Morten Christiansen and Nick Chater have argued that the relatively fast-changing nature of language would prevent the slower-changing genetic structures from ever catching up, undermining the possibility of a genetically hard-wired universal grammar. In addition, it has been suggested that people learn about probabilistic patterns of word distributions in their language, rather than hard and fast rules (see the distributional hypothesis). It has also been proposed that the poverty of the stimulus problem can be largely avoided, if we assume that children employ similarity-based generalization strategies in language learning, generalizing about the usage of new words from similar words that they already know how to use.
Another way of defusing the poverty of the stimulus argument is to assume that if language learners notice the absence of classes of expressions in the input, they will hypothesize a restriction (a solution closely related to Bayesian reasoning). In a similar vein, language acquisition researcher Michael Ramscar has suggested that when children erroneously expect an ungrammatical form that then never occurs, the repeated failure of expectation serves as a form of implicit negative feedback that allows them to correct their errors over time. This implies that word learning is a probabilistic, error-driven process, rather than a process of fast mapping, as many nativists assume.
Finally, in the domain of field research, the Pirahã language is claimed to be a counterexample to the basic tenets of Universal Grammar. This research has been primarily led by Daniel Everett, a former Christian missionary. Among other things, this language is alleged to lack all evidence for recursion, including embedded clauses, as well as quantifiers and color terms. Some other linguists have argued, however, that some of these properties have been misanalyzed, and that others are actually expected under current theories of Universal Grammar.
-- http://en.wikipedia.org/wiki/Universal_grammar#Criticisms
Looks like I'm not the only one that sees through bullshit.
Let me repeat - just to imprint on people's minds:
> This implies that word learning is a probabilistic, error-driven process, rather than a process of fast mapping, as many nativists assume.
Chomsky's theories are, and always were, DOA.
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#120Earlier quoted context omitted.
What do you think of http://en.wikipedia.org/wiki/Nicaraguan_Sign_Language ? It certainly makes me doubt language (the technology of it) as purely cultural and learned.
Language is a set of behaviors Behavior for humans and other animals requires a brain and body (almost always) The organisation, growth, and function of the brain and body are influenced by genetics. So we can say first and formost that language is influenced by genetics. Having a tongue, vocal chords, hands, ears. These all help to acquire language. So now the question is to what degree does genetics influence langu…
Consider a different example: constructing artificial vision. Human vision is the result of evolution, of course. It is incredibly inefficient, but evolution is blind (sorry). When we now construct computer vision, we capture an optical image and transmit it optically as long as possible, since this preserves information. The human eye does not: it sends information via neurons to the visual cortex, compromising immensely in bandwidth. That's why we need visual error-correction mechanisms in the brain, and redundancy of visual information (achieved by the eye moving rapidly many times per second, for example).
When we construct optical computer vision that achieves the a similar thing as human vision, the two have nothing in common. You can't plug in the artificial front end into the biological back end. The two systems produce literally different images, that are not comparable. The systems will not communicate with each other. We have skipped the legacy of biological evolution completely. To create an artificial system that accurately corresponds to the biological would be an immense waste.
The same goes for intelligence. Our 'wet' evolved intelligence is an entirely different picture from the project of Strong AI. They will produce very different manifestations of interacting with the world. Why would the latter ever result in the illusion of free will or the self-referentiality of personal identity, two things we assume are parts of human-level intelligence? They are like the neurological channels for conveying an optical image: hopelessly inefficient, but the ones that make sense in the light of our evolutionary legacy.
As a side note, yes we know of a time when there was no language, but it not a good representation to consider that a binary switch. We know of complex communication between other animals, and given that even current languages are in rapid flux, I think it is is fair to think of the transition from pre-language to language a continuum. Language is still arising.