2 ms·

But does the translation use word2vec or anything similar? The original Altavista Babelfish (which used SYSTRAN) used rule-based machine translation. It has

But does the translation use word2vec or anything similar? The original Altavista Babelfish (which used SYSTRAN) used rule-based machine translation. It has been replaced by Bing Translator, but my recollection of the Babelfish was that it was accurate enough to be usable, and better than Google Translate was when it was first released. Google Translate has improved a lot recently. My only problem with it is that it doesn't understand the meaning of the words it's translating. Neural networks are perfectly suitable for perception, e.g. image recognition. No argument there.

matt4077 10y ago
> My only problem with it is that it doesn't understand the meaning of the words it's translating. I think that's a fallacy that will haunt AI forever (or, more likely, will be the definitive civil rights struggle ca. March 25, 2035 6:25:45am to March 25, 2035 6:25:48am) We tend to move the goalpost whenever AI makes advances. Where many people would have considered chess a pretty good measure of at least some aspect of intelligence, it seems like mundane number crunching once you know how it works. It may be that we really mean consciousness when we say "intelligence", although if we ever find an easy formulation that creates a perfect "illusion" of consciousness, it may end up having some strong effects on people's conception of themselves that I don't necessarily want to witness.
- williamtrask 10y ago
  thanks for sharing this... stirring thoughts. Did my best to paraphrase here (https://twitter.com/iamtrask/status/818090203990659072 https://twitter.com/iamtrask/status/818090203990659072) but I really think we should spend more time on this as a society.
barrkel 10y ago
I think a vector of weights in different dimensions constitutes meaning. Words don't have a single meaning; they're a shared implicit web of allusions and hints. We only understand one another to the degree that our allusions are shared - it's why nonnative speakers miss nuance, and it's why poetry is a thing. If there are symbols, they're in the dimensions of the vector; but words only probabilistically suggest meaning, they don't categorically denote it.
- DonaldFisk 10y ago
  Words with multiple meanings will have multiple vectors each depending on context, and if you train your system without taking that into account the vectors will be averaged and the individual meanings will be lost. With a symbolic approach, the right thing is to use a different symbol for each meaning, and disambiguate based on context (which you could identify either statistically or by using rules).
  - barrkel 10y ago
    I feel that you don't appreciate how plastic language is, and how indirectly meaning is conveyed. New words and meanings become cultural shared knowledge on a weekly if not daily basis, and shades of meanings are added to existing words and phrases simply by being used in a milieu or by a sufficiently famous person. Symbols might be used as hidden variables representing concepts, but to fully represent how vague and allusive language is, you've got no choice but to make everything fractional. I don't see the result being anything other than isomorphic with a vector. In particular, words are not repositories of meaning. They allude to concepts; new concepts are created and get forgotten on a regular basis. The connection between words and concepts waxes and wanes over time, and even the very timeline of a connection's strength can be used for allusion: using language to represent concepts that can only be coherently mapped by using previously-stronger allusions conveys a sense of being old-fashioned, while the reverse conveys future-thinking. Using allusions that are stronger within a milieu conveys social signalling information about group membership. Etc. There's no way a human-maintained database is going to capture the subtlety here on anything like a timely basis. There's no universal truth, everyone's map is a little bit different, and the map is changing all the time.
    - DonaldFisk 10y ago
      Yet we've evolved to use symbols, which are short sequences of phonemes or glyphs, and to connect these together to form sentences, which are lists of symbols. People who speak the same language are able to communicate perfectly well, almost all of the time, across continents and centuries. New words are rare compared to existing vocabulary and often soon disappear from use. New concepts can readily be mapped onto existing vocabulary. People are able to learn other languages and improve their own with the help of dictionaries and grammar books. Things like humour, cryptic crosswords, and social signalling are edge cases. And things like deception are unrelated to language understanding at the semantic level. We're discussing the best way for computers to understand natural language and communicate with people, and in practice that's either going to use unambiguous language or it's going to need human help or verification.
coldtea 10y ago
>My only problem with it is that it doesn't understand the meaning of the words it's translating. Wouldn't that mean it was an actual full AI?

matt4077 10y ago

> My only problem with it is that it doesn't understand the meaning of the words it's translating. I think that's a fallacy that will haunt AI forever (or, more likely, will be the definitive civil rights struggle ca. March 25, 2035 6:25:45am to March 25, 2035 6:25:48am) We tend to move the goalpost whenever AI makes advances. Where many people would have considered chess a pretty good measure of at least some aspect of intelligence, it seems like mundane number crunching once you know how it works. It may be that we really mean consciousness when we say "intelligence", although if we ever find an easy formulation that creates a perfect "illusion" of consciousness, it may end up having some strong effects on people's conception of themselves that I don't necessarily want to witness.

williamtrask 10y ago
thanks for sharing this... stirring thoughts. Did my best to paraphrase here (https://twitter.com/iamtrask/status/818090203990659072 https://twitter.com/iamtrask/status/818090203990659072) but I really think we should spend more time on this as a society.

barrkel 10y ago

I think a vector of weights in different dimensions constitutes meaning. Words don't have a single meaning; they're a shared implicit web of allusions and hints. We only understand one another to the degree that our allusions are shared - it's why nonnative speakers miss nuance, and it's why poetry is a thing. If there are symbols, they're in the dimensions of the vector; but words only probabilistically suggest meaning, they don't categorically denote it.

DonaldFisk 10y ago
Words with multiple meanings will have multiple vectors each depending on context, and if you train your system without taking that into account the vectors will be averaged and the individual meanings will be lost. With a symbolic approach, the right thing is to use a different symbol for each meaning, and disambiguate based on context (which you could identify either statistically or by using rules).
- barrkel 10y ago
  I feel that you don't appreciate how plastic language is, and how indirectly meaning is conveyed. New words and meanings become cultural shared knowledge on a weekly if not daily basis, and shades of meanings are added to existing words and phrases simply by being used in a milieu or by a sufficiently famous person. Symbols might be used as hidden variables representing concepts, but to fully represent how vague and allusive language is, you've got no choice but to make everything fractional. I don't see the result being anything other than isomorphic with a vector. In particular, words are not repositories of meaning. They allude to concepts; new concepts are created and get forgotten on a regular basis. The connection between words and concepts waxes and wanes over time, and even the very timeline of a connection's strength can be used for allusion: using language to represent concepts that can only be coherently mapped by using previously-stronger allusions conveys a sense of being old-fashioned, while the reverse conveys future-thinking. Using allusions that are stronger within a milieu conveys social signalling information about group membership. Etc. There's no way a human-maintained database is going to capture the subtlety here on anything like a timely basis. There's no universal truth, everyone's map is a little bit different, and the map is changing all the time.
  - DonaldFisk 10y ago
    Yet we've evolved to use symbols, which are short sequences of phonemes or glyphs, and to connect these together to form sentences, which are lists of symbols. People who speak the same language are able to communicate perfectly well, almost all of the time, across continents and centuries. New words are rare compared to existing vocabulary and often soon disappear from use. New concepts can readily be mapped onto existing vocabulary. People are able to learn other languages and improve their own with the help of dictionaries and grammar books. Things like humour, cryptic crosswords, and social signalling are edge cases. And things like deception are unrelated to language understanding at the semantic level. We're discussing the best way for computers to understand natural language and communicate with people, and in practice that's either going to use unambiguous language or it's going to need human help or verification.

coldtea 10y ago

>My only problem with it is that it doesn't understand the meaning of the words it's translating. Wouldn't that mean it was an actual full AI?