This article was published on Hacker News today, a good overview and criticism of the current hype around NLP and speech-to-text in general. I like this comparison:
Stable production-grade NLP models usually are built upon data which is several orders of magnitude larger or the task at hand should be much more simple. For example - it is safe to assume that a neural network can do NER reliably, but as for answering questions or maintaining dialogue - this is just science fiction now. I like an apt analogy - building AGI with transformers is like going to the Moon by building towers
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