Google Translate (and all the new competing products) alone should be reason enough to demonstrate outstanding societal good.
You can now travel anywhere in the world and communicate in the local language. Using offline models that translate between any two languages. That’s almost literally biblical magic levels of social good.
(Plus we got amazing image recognition tech, LLMs, voice and NLU stuff, AlphaFold for protein analysis, etc)
I’m not sure, but I thought their business model involved applying machine learning on user answers, like their translations of excerpts of written text / handwriting samples.
I think what I was recalling is the crowdsourcing translations mechanic, which is far more low tech:
> But wait – how could a beginner-level student translate advanced sentences? The solution that Duolingo employs uses the power of crowdsourcing, which involves many students offering their attempts at translating individual sentences. As each student submits a sentence, they can rate others’ translations, and the most highly rated translations “rise to the top.”
Over time, entire documents are translated and students gain many skill points for their language practice. It’s easy to see how the data collected from users could be useful to improve the algorithms that underly computer translation[…]
You can now travel anywhere in the world and communicate in the local language. Using offline models that translate between any two languages. That’s almost literally biblical magic levels of social good.
(Plus we got amazing image recognition tech, LLMs, voice and NLU stuff, AlphaFold for protein analysis, etc)