> “The reason this is exciting is it’s scalable,” he added. “We cannot afford to hire operators for the entire world to be their personal assistant.”
Why all the praise when the goal will look nothing like it looks now. They don't actually know that it's scalable, otherwise we'd be seeing a completely non-human dependent AI with limited functionality (like ordering food) first. The current approach is just getting more data to see if the real version can work at scale.
> Why all the praise when the goal will look nothing like it looks now
Because the media machine needs to keep spinning. Rather than give a balanced statement now, which takes more effort to put together, it's easier to post "Wow, this is amazing" now and then "Wow, that was disappointing" later, and then get double the hits.
Reminds me of Google's 411 service back in the day. People thought "cool, Google is offering a free service". But Google was just collecting voice samples to train its voice recognition algorithms.
It's not pre-computing an answer, it's training a neural network that will be able to answer that and similar questions with minimal or no human interaction.
Whether that works out or not remains to be seen, but it's definitely worth investing research effort in to.
> We are still far away from having computer's truly be able to learn on their own, without having a human optimizing the responses.
Could say the same about humans, though. We can't truly learn on our own without having others calibrating the process, or otherwise things set up by others.
AI in large part is supervised learning. I think the more important question here is when that becomes feasible for general purpose stuff for facebook.
[+] [-] pgodzin|10 years ago|reply
Why all the praise when the goal will look nothing like it looks now. They don't actually know that it's scalable, otherwise we'd be seeing a completely non-human dependent AI with limited functionality (like ordering food) first. The current approach is just getting more data to see if the real version can work at scale.
[+] [-] visakanv|10 years ago|reply
Because the media machine needs to keep spinning. Rather than give a balanced statement now, which takes more effort to put together, it's easier to post "Wow, this is amazing" now and then "Wow, that was disappointing" later, and then get double the hits.
Relevant: https://medium.com/backchannel/how-the-tech-press-forces-a-n...
[+] [-] discardorama|10 years ago|reply
[+] [-] x5n1|10 years ago|reply
[+] [-] jsprogrammer|10 years ago|reply
A user may never ask A. Or, a user may only ask A once; in which case, did we really need to pre-compute the answer?
[+] [-] imron|10 years ago|reply
Whether that works out or not remains to be seen, but it's definitely worth investing research effort in to.
[+] [-] dump100|10 years ago|reply
[+] [-] dennisnedry|10 years ago|reply
[+] [-] visakanv|10 years ago|reply
Could say the same about humans, though. We can't truly learn on our own without having others calibrating the process, or otherwise things set up by others.
[+] [-] nikolay|10 years ago|reply
[+] [-] ganwar|10 years ago|reply