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We have spent the last seventy or more years working on machine translation. All the way back in the 1950s, big money went into it. Decades of hard work, mathematical models of human language, all manner of study, enormous bilingual corpuses of text with phonetic annotation, programmed in general-knowledge databases, fuzzy reasoning algorithms. The amount of work put into it is quite staggering, in hindsight. I remember the cutting edge in the 1990s - SYSTRAN for example, could with some significant human guidance and a limited context domain, translate technical material sometimes usefully. All of that work has been rendered moot by deep learning. All of it. A machine can, simply with the correct deep learning algorithm and mass exposure to language plus a few bilingual texts, learn an algorithm for translation. It does so automatically, no verb conjugation algorithms, no general knowledge databases, no expert systems with fuzzy reasoning, no parsers, not like a specifically-designed old-school translator had. And yet these deep-learning systems are vastly superior to the old school architectures, completely supplanting them a couple years after their development. It is the same story in many other areas. Chess, Go? They learn to play chess and go better than any AI designed specifically to do so. Image classification? Better than the previous 60 years of work on machine vision, and again, accidentally falls out of it. Speech recognition? An algorithm to write a bad poem? Well, we now have an algorithm to find an algorithm to write you that bad poem, if you want it. That's the thing. These are algorithms to solve very tricky problems, and we didn't have to discover, find, or otherwise create the algorithm. The machine did it for us. I am not sure I'm communicating it well, but to me that's probably the most significant advance since the computer. It was understood - theoretically - that this was possible for a long time; but personally at least, I assumed it would forever require more data and compute than could be realized. |
Take GP's "stagnant for decades" with tech and turn it into "stagnant for centuries" with these. When it first started I remember professional Go players talking about just how big a shakeup it was.