Lol, I doubt they will make any progress. Institutional learning doesn't
teach you how to think outside the box.




On Fri, Feb 21, 2014 at 9:11 AM, Ted <[email protected]> wrote:

> More details, Mark Zucklberg personally called Yann LeCun on the phone to
> be the director of AI research.
>
> Here's an abstract from one of his latest papers:
>
> *Learning Hierarchical Features for Scene Labeling*, scheduled to appear
> in the special issue on deep learning of IEEE Trans. on Pattern Analysis
> and Machine Intelligence. The task is to label all the pixels in an image
> with the category of the object it belongs to. This is sometimes called
> scene labeling, scene parsing, or semantic segmentation. The bottom line is
> that our system beat all previously published scene labeling systems on
> accuracy on three standard datasets: Stanford Bakground (8 classes),
> SIFTflow (33 classes) and Barcelona (170 classes). It also beat the best
> competitors by a factor of 100 in speed. Our system is a multiscale
> convolutional network trained in purely supervised mode (with backprop) to
> label each pixel. The decisions are then cleaned up by a simple
> post-processing (the simplest one consisting in taking the majority
> category within a superpixel).
>
>
> On Friday, February 21, 2014 11:02:12 AM UTC-6, Ted wrote:
>>
>> Sounds like the same for deep learning, heard this on NRP radio while
>> driving home yesterday:
>>
>> http://www.npr.org/blogs/alltechconsidered/2014/02/20/
>> 280232074/deep-learning-teaching-computers-to-tell-things-apart
>>
>> On Wednesday, February 19, 2014 11:22:11 PM UTC-6, BenGoertzel wrote:
>>>
>>> http://www.technologyreview.com/news/524401/yahoo-
>>> launches-10-million-research-effort-to-invent-a-smarter-siri/#comments
>>>
>>>
>>>
>>> --
>>> Ben Goertzel, PhD
>>> http://goertzel.org
>>>
>>> "In an insane world, the sane man must appear to be insane". -- Capt.
>>> James T. Kirk
>>>
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