This seems to be comparing them on their own terms. In more curious on features. Dragon naturally speaking and some other products have been really impressive for years now. Far beyond what my phone is capable of.
Not to say that the likes of the echo and others aren't impressive. Just that the speech recognition is the least of those products. Fully transcribed voice mail was available for years with Google voice (even before it was Google voice), yet that seems to happen less now than it did when I first for the product.
So what changed? And why?
Re:The Looming Battle Over AI Chips
by jacksmith21006 on Monday April 23, 2018 @08:46AM
(#16902887)
What? You are comparing processing a NN. How is that comparing on "own terms"?
Did the old methods use neutral networks? I wouldn't be surprised if they did, but I would be surprised if they were as deep of networks as what people use today.
That is, I am interested in comparing them on speed of transcription, speech synthesises, error rates, etc. Not on speed of network execution.
Re:The Looming Battle Over AI Chips
by jacksmith21006 on Tuesday April 24, 2018 @10:38AM
(#16912921)
No the old method did NOT use NN. I hope Google writes a paper and shares more details.
It is hard to believe they are able to do 16k samples a second through a NN even with the TPUs.
So be curious to see if reduced and how much?
If they really do have the ability to do 16k a second at scale that opens the door for all kinds of other applications.
Surprised. Curious if you can compare the inference per joules of Google 1st gen TPUs compared? Google shared a paper and the numbers are pretty impressive and was not aware of anyone else close to the gen 1 TPUs?
Here is the paper that you can use for the TPU side. Love so see someone else in the ball park? We really do not want just one company but competition.
https://arxiv.org/ftp/arxiv/papers/1704/1704.04760.pdf