4 ms·

> The only "algorithm" that can effectively transform text between English and Chinese would be one that understands the source and target texts like a human.

by JadeNB 3y ago

> The only "algorithm" that can effectively transform text between English and Chinese would be one that understands the source and target texts like a human. How do you know?

pixl97 3y ago
Or the corollary viewpoint, that if ChatGPT can do this as the previous poster says, then it is a type of AGI.
- Jensson 3y ago
  Yeah, people used to think that since only humans can do arithmetics it was the peak of intelligence, and computers can do arithmetics better than humans, then AGI was just around the corner. Now people argue that since only humans have complex language it was the peak of intelligence, and now computers can do that language like humans, then AGI is just around the corner.
  - lacrimacida 3y ago
    Well, I think I need to remind you that humans invented arithmetics, humans invented computers, computer languages, artificial intelligence and so on. I think you are underestimating how complex the human thought is now that we have LLMs. They appear to have unlimited progress but they’re eventually bound to what they’re trained on.
    - Jensson 3y ago
      That was my point though. The AGI optimist community always think that when a computer solves a new thing that computers previously didn't solve then AGI is near. Then a decade later we realize that there are still plenty of things that only humans can solve.
- willprice89 3y ago
  To clarify, I'm using "understand" in a sense similar to the Turing Test. It doesn't matter if the machine actually understands in the same way as humans (or at all), only that it is able to make humans think it understands. If it can convince native speakers of both languages it is human, it has enough "understanding" to perform a good translation.
willprice89 3y ago
Because translation isn't a one-to-one transformation. A bilingual speaker doesn't have a single abstract thought that they are then able to express in two different languages. Rather the expressions themselves represent similar thoughts that are grounded in the overall cultural context surrounding the language. Translation attempts to minimize the difference these expressions have on their respective audiences, but doing so requires understanding the text like the target audience. Another way to think about it is that translation is not a question of "Express this English sentence in Chinese", but rather "Rewrite this sentence in the style of (some specific Chinese person)". You'll get a very different result if the target is "physics professors from Beijing" versus "rice farmers from Yunnan".

by JadeNB 3y ago

> The only "algorithm" that can effectively transform text between English and Chinese would be one that understands the source and target texts like a human. How do you know?

pixl97 3y ago

Or the corollary viewpoint, that if ChatGPT can do this as the previous poster says, then it is a type of AGI.

Jensson 3y ago
Yeah, people used to think that since only humans can do arithmetics it was the peak of intelligence, and computers can do arithmetics better than humans, then AGI was just around the corner. Now people argue that since only humans have complex language it was the peak of intelligence, and now computers can do that language like humans, then AGI is just around the corner.
- lacrimacida 3y ago
  Well, I think I need to remind you that humans invented arithmetics, humans invented computers, computer languages, artificial intelligence and so on. I think you are underestimating how complex the human thought is now that we have LLMs. They appear to have unlimited progress but they’re eventually bound to what they’re trained on.
  - Jensson 3y ago
    That was my point though. The AGI optimist community always think that when a computer solves a new thing that computers previously didn't solve then AGI is near. Then a decade later we realize that there are still plenty of things that only humans can solve.
willprice89 3y ago
To clarify, I'm using "understand" in a sense similar to the Turing Test. It doesn't matter if the machine actually understands in the same way as humans (or at all), only that it is able to make humans think it understands. If it can convince native speakers of both languages it is human, it has enough "understanding" to perform a good translation.

willprice89 3y ago

Because translation isn't a one-to-one transformation. A bilingual speaker doesn't have a single abstract thought that they are then able to express in two different languages. Rather the expressions themselves represent similar thoughts that are grounded in the overall cultural context surrounding the language. Translation attempts to minimize the difference these expressions have on their respective audiences, but doing so requires understanding the text like the target audience. Another way to think about it is that translation is not a question of "Express this English sentence in Chinese", but rather "Rewrite this sentence in the style of (some specific Chinese person)". You'll get a very different result if the target is "physics professors from Beijing" versus "rice farmers from Yunnan".