The world’s natural language researchers soon overhauled their approach, embracing the kind of statistical models unveiled that afternoon at the lab outside Seattle. This was just one of many mathematical methods that spread across the larger community of AI researchers in the 1990s and on into the 2000s, with names like “random forests,” “boosted trees,” and “support vector machines.” Researchers applied some to natural language understanding, others to speech recognition and image recognition. As the progress of neural networks stagnated, many of these other methods matured and improved and
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