robertfortner

To some degree, I'm critiquing Ray Kurzweil who generalizes about progress. So, for better or worse, I take a lesson from that which is to be empiricist: look closely at each field to see whether it's vaulting forward or not.

It's not happening in space (although hypersonics seem to be getting more real). It's not happening in AI or speech recognition/understanding. It's not happening in medicine.

So the net empirical situation looks like the opposite of what Kurzweil says. Only IT and Moore's Law are going totally nuts. One can conjecture about why, but I think that's conjecture and there aren't deep fundamental principles about scientific and technological progress, at least that we've found so far.

Correct surmise: I'm not a speech recognition researcher. I'm a science and technology writer.

I was very surprised to find that recognition accuracy stopped getting better a long time ago. I do poke fun, but I also think Kurzweil (as I said in the piece) very reasonably believed that Moore's Law would get us a long way to AI. And surprisingly, it hasn't.

I like to think I don't have a stake in the argument and just let what's actual decide whether or not we're going to get to computer understanding of language and/or AI.

What word(s) are we looking at in the .gif?

Thanks for reading. But I think a key take-away is that even with infinite computing power, you only increase the chance of being right a little. It's still a guess.

That's the real surprise. It's not a question of computing power.

I'd say they aren't really conflicting. Commercial speech recognition really started in the medical field. Accuracy is much higher with a controlled vocabulary.

Speaker-specific characteristics, e.g. accent, by contrast are much harder for recognizers.