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> While AGI isn't going to be created any time soon, machines have learned how to master complex tasks like: > translating text into practically every language

by cbanek 7y ago

> While AGI isn't going to be created any time soon, machines have learned how to master complex tasks like: > translating text into practically every language Note: they said they have mastered these tasks. Yeah... I'm not sure a lot of native speakers would agree. Here's a great example of using Google Translate to automatically translate a video game. https://www.youtube.com/watch?v=_uNkubEHfQU https://www.youtube.com/watch?v=_uNkubEHfQU > Driving cars I'm not so sure about that one either. I think we're in the valley that AI can do a lot of things, but are hitting limits in accuracy where humans are still better at some of these things sometimes. That is, the AI isn't always better than humans, even at a specific, non-general task. Now don't get me wrong, we've made a lot of progress, but I wonder if we can get these things to a place better than humans before the next economic recession. I think the biggest risk to AI is having the money dry up. Right now the hype is strong and the money is (nearly) free. If one of those changes, we could put this back on the shelf for another decade. If we go into a recession, labor will be cheap, so why bother automating with AI? For example, we had self driving freeway cars back in the 90's.[0][1] Here's one of the lessons learned: > In 1987, some UK Universities expressed concern that the industrial focus on the project neglected import traffic safety issues such as pedestrian protection. And who doesn't remember the brilliant Dr. Sbaitso, my childhood therapist. [2] [0] https://en.wikipedia.org/wiki/Eureka_Prometheus_Project https://en.wikipedia.org/wiki/Eureka_Prometheus_Project [1] https://www.youtube.com/watch?v=I39sxwYKlEE https://www.youtube.com/watch?v=I39sxwYKlEE [2] https://en.wikipedia.org/wiki/Dr._Sbaitso https://en.wikipedia.org/wiki/Dr._Sbaitso

ggggtez 7y ago
As amusing as the Final Fantasy translation project is, it simply is not the right comparison. It's a case of using the wrong tool for the job. There are better systems for natural language translation that attempt to keep track of the subject, something that is very often implicit from context in Japanese. Additionally, that subject could be implicit based on the visuals of what is on screen. The enemy names are abbreviations due to artificial limits of the system... All in all, it's like using a hammer to drive a screw. It might sort of work, but you shouldn't be surprised when it fails. It's just a case of using the wrong tool for the job. That is hardly proof that Hammers are bad, or the screws can never be successfully inserted into a board.
- cbanek 7y ago
  Right, I get what you're saying about Japanese, I took a few years of Japanese in school, and it is a really interesting grammatical problem. (Which is why I love this example even more) If you read the released book about the project, one of the problems he brings up is that also the AI will pick words that start with the same letter as the first kana, seemingly at random, when it gets confused. While I don't disagree that using AI might not be the best tool for Japanese translation, or that there might be better specific Japanese translators that use AI, I think the idea that AI has "mastered translation" is honestly going a bit too far, which was the point I was attempting to make.
AlexCoventry 7y ago
> Now don't get me wrong, we've made a lot of progress, but I wonder if we can get these things to a place better than humans before the next economic recession. I don't think it's necessary to completely solve superhuman performance to achieve automation of great economic value. Some of the most famous AI achievements leverage a fairly modest intelligence improvement with massive amounts of classic automation. E.g., the AlphaGo policy/value networks, combined with MCTS. It may also be possible for automation to reliably determine when it's encountering a situation it's going to fare badly in, and then hand off to human telepresence control. It wouldn't surprise me if the first self-driving systems worked that way.
- philipov 7y ago
  > and then hand off to human telepresence control. It wouldn't surprise me if the first self-driving systems worked that way. The issue is that humans fare badly in situations where they don't have to pay attention until they suddenly have a short time to react before disaster, and that's exactly the problem that "supervised" self-driving systems have been suffering from when they crash. And if you have to pay constant attention to the road anyway, I'd rather be driving myself. What's going to win won't be self-driving tech, it will be driver assist, like advanced anti-lock brakes, or self-adjusting cruise control.
- Piskvorrr 7y ago
  They do. FTR, this is what killed EH: "computing...computing...computing...oh well, let's alert the human - so they can watch the crash about to happen in the next second."
redisman 7y ago
What makes me somewhat bullish is that parallel compute keeps getting better, cheaper and more widely available.
Veedrac 7y ago
I don't disagree that translation is far from mastered, but bear in mind that Google Translate isn't state of the art, mostly because of computational constraints, and 2016 GTranslate was even worse.
- Piskvorrr 7y ago
  No true Scotsman? What is, then, the state of the art in 2020 machine translation?
  - Veedrac 7y ago
    I'm not actually sure, but DeepL[1] is probably the best online one, and Google's larger M4 models[2] are probably up there too. [1] https://www.deepl.com/translator https://www.deepl.com/translator [2] https://ai.googleblog.com/2019/10/exploring-massively-multilingual.html https://ai.googleblog.com/2019/10/exploring-massively-multil...
Piskvorrr 7y ago
As for the translations - even a seemingly innocent sentence like "the sand people ride single file to hide their numbers" is fraught with ambiguity. I wouldn't call "unable to tell file-the-tool from file-the-data-representation from file-the-line" mastery. Useful for a rough meaning in a completely unfamiliar language, sure - the hyperhype surrounding current SoA is actually contributing to the descent to AI winter. https://www.everything2.com/title/The+sand+people+ride+in+single+file+to+hide+their+numbers https://www.everything2.com/title/The+sand+people+ride+in+si...

by cbanek 7y ago

ggggtez 7y ago

As amusing as the Final Fantasy translation project is, it simply is not the right comparison. It's a case of using the wrong tool for the job. There are better systems for natural language translation that attempt to keep track of the subject, something that is very often implicit from context in Japanese. Additionally, that subject could be implicit based on the visuals of what is on screen. The enemy names are abbreviations due to artificial limits of the system... All in all, it's like using a hammer to drive a screw. It might sort of work, but you shouldn't be surprised when it fails. It's just a case of using the wrong tool for the job. That is hardly proof that Hammers are bad, or the screws can never be successfully inserted into a board.

cbanek 7y ago
Right, I get what you're saying about Japanese, I took a few years of Japanese in school, and it is a really interesting grammatical problem. (Which is why I love this example even more) If you read the released book about the project, one of the problems he brings up is that also the AI will pick words that start with the same letter as the first kana, seemingly at random, when it gets confused. While I don't disagree that using AI might not be the best tool for Japanese translation, or that there might be better specific Japanese translators that use AI, I think the idea that AI has "mastered translation" is honestly going a bit too far, which was the point I was attempting to make.

AlexCoventry 7y ago

> Now don't get me wrong, we've made a lot of progress, but I wonder if we can get these things to a place better than humans before the next economic recession. I don't think it's necessary to completely solve superhuman performance to achieve automation of great economic value. Some of the most famous AI achievements leverage a fairly modest intelligence improvement with massive amounts of classic automation. E.g., the AlphaGo policy/value networks, combined with MCTS. It may also be possible for automation to reliably determine when it's encountering a situation it's going to fare badly in, and then hand off to human telepresence control. It wouldn't surprise me if the first self-driving systems worked that way.

philipov 7y ago
> and then hand off to human telepresence control. It wouldn't surprise me if the first self-driving systems worked that way. The issue is that humans fare badly in situations where they don't have to pay attention until they suddenly have a short time to react before disaster, and that's exactly the problem that "supervised" self-driving systems have been suffering from when they crash. And if you have to pay constant attention to the road anyway, I'd rather be driving myself. What's going to win won't be self-driving tech, it will be driver assist, like advanced anti-lock brakes, or self-adjusting cruise control.
Piskvorrr 7y ago
They do. FTR, this is what killed EH: "computing...computing...computing...oh well, let's alert the human - so they can watch the crash about to happen in the next second."

redisman 7y ago

What makes me somewhat bullish is that parallel compute keeps getting better, cheaper and more widely available.

Veedrac 7y ago

I don't disagree that translation is far from mastered, but bear in mind that Google Translate isn't state of the art, mostly because of computational constraints, and 2016 GTranslate was even worse.

Piskvorrr 7y ago
No true Scotsman? What is, then, the state of the art in 2020 machine translation?
- Veedrac 7y ago
  I'm not actually sure, but DeepL[1] is probably the best online one, and Google's larger M4 models[2] are probably up there too. [1] https://www.deepl.com/translator https://www.deepl.com/translator [2] https://ai.googleblog.com/2019/10/exploring-massively-multilingual.html https://ai.googleblog.com/2019/10/exploring-massively-multil...

Piskvorrr 7y ago

As for the translations - even a seemingly innocent sentence like "the sand people ride single file to hide their numbers" is fraught with ambiguity. I wouldn't call "unable to tell file-the-tool from file-the-data-representation from file-the-line" mastery. Useful for a rough meaning in a completely unfamiliar language, sure - the hyperhype surrounding current SoA is actually contributing to the descent to AI winter. https://www.everything2.com/title/The+sand+people+ride+in+single+file+to+hide+their+numbers https://www.everything2.com/title/The+sand+people+ride+in+si...