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I'm not entirely sure why low resource languages are seen as such a high priority for AI research. It seems that by definition there's little payoff to solving translation for them.
I'm not entirely sure why low resource languages are seen as such a high priority for AI research. It seems that by definition there's little payoff to solving translation for them.
Some numbers (but you can not exactly infer from them such accumulated numbers): https://en.wikipedia.org/wiki/List_of_languages_by_total_num...
Some more numbers from here: https://www.sciencedirect.com/science/article/pii/S016763931...
"96% of the world’s languages are spoken by only 4% of its people."
Although this statement is more about the tail from the approx 7000 languages.
I'm not entirely sure why low resource languages are seen as such a high priority for AI research. It seems that by definition there's little payoff to solving translation for them.
Furthermore, Facebook considers the internet to consist of Facebook and Wikipedia (Zero).
I view this as just another extension of their Next Billion initiative, an effort to ensure that another billion people are monopolised by Facebook.
That's the payoff.
I'm not entirely sure why low resource languages are seen as such a high priority for AI research. It seems that by definition there's little payoff to solving translation for them.
The point is that there are lots of humans who speak these languages and use tech. They just don’t use Wikipedia so getting a good translation corpus going was harder.
We're at a point where it's now possible to determine the shape of every language, provided there are enough speakers of the language left who are both able and willing to help.
Once done, Facebook can then commodify their dissent, and sell it back to them in their native language.
Earlier quoted context omitted.
I think the reason low resource languages are prioritized is to compensate for the fact that AI research normally has a tendency to marginalize these languages.
yes, but what principles justify the importance placed on low resource languages?
The reason for emphasis is in my opinion twofold: 1) Allowing these people to use the fancy language technology in their own language is good in and of itself. 2) Training neural networks on fewer resources is more difficult than using more resources and therefore a fun and interesting challenge.
So they have a system that can translate to languages for which there isn't as much data as English, Spanish, etc. Waiting for a Twitter thread from a native speaker of one of these "low resource languages" to let us know how good the actual translations are. Cynically, I'd venture that they hired some native speakers to cherry pick their best translations for the story books. But mostly this just seems like a nice b…
Jeff Wang here with my fellow Meta AI colleague Angela Fan from No Languages left Behind, seeing the comments flowing through. If you want to ask us anything, go for it!