by campbellmorgan on 8/24/16, 8:19 AM with 37 comments
by gomox on 8/24/16, 5:49 PM
One of his preliminary results was that his algorithms successfully "discovered" 4 big classical music movements on their own, i.e. without any prior labelling or classification, by using clustering algorithms. He posted about it on his blog with a link to his paper [2].
I always had a hard time explaining to non-computer people how amazing that seems.
[1] http://www.peachnote.com/ [2] http://pablozivic.com.ar/post/51774763596/perceptual-basis-o...
by monkmartinez on 8/24/16, 5:14 PM
My eight year old son is enamored with "Ok Google" on my phone. He can ask it questions until we tell him "that is enough, let google rest"... and it is very interesting to see where it takes him.
He has learned to tailor his questions to elicit a voice response in addition to the actual google search. The questions must use keywords to achieve this desired response. It is like a new form of boolean search logic, just used verbally. Not only that, but "Ok, Google" according to him "knows everything"...
We call it searching the internet to learn something, an eight year has decided that "Ok, Google" already knows everything. He just has to ask it to see a video of the Puff adder eating its prey and it will show him. In fact, there are not many things that have stumped "Ok, Google" and my son assumes the problem was with his question, not with the machine.
So to circle back to my original question, I didn't know about the Taipan snake or smallest person in the world, or seen videos of Puff adders eating prey... If all I have to do is ask, isn't the machine already smarter than I?
by codeulike on 8/24/16, 3:47 PM
If this [huge google] network had been fed thousands of images labelled as ‘contains cats’ or ‘doesn’t contain cats’ and trained to work out the difference for itself by iteratively tweeking its 1.7 billion parameters until it had found a classification rule, that would have been impressive enough, given the scale of the task involved in mapping from pixels to low-level image features and then to something as varied and complex as a cat’s face. What Google actually achieved is much more extraordinary, and slightly chilling. The input images weren’t labelled in any way: the network distilled the concept of ‘cat face’ out of the data without any guidance.
by sosuke on 8/24/16, 4:04 PM
I love AI, but I have that hope too. That somehow we won't be made irrelevant by our own creations. Makes me think of our autonomous vehicle fun taking over the trucking industry. Millions of people made irrelevant through no fault of their own.
by carapace on 8/24/16, 7:59 PM
What I mean is, some of the "cat faces" they identify will correspond to things that are "real" but that also violate our assumptions about reality. When this happens the typical reaction is to shut the door and burn the room.
by fegu on 8/24/16, 9:46 PM