11–20 of 24 posts
@10:08 on the right merc sls classified as SUV on the left one SUV classified as two VANs Their algorithm works at about 1Hz rate when doing signs. This is ~state of the art from 20 years ago, but running on small mobile SoC at a slow rate.
Earlier quoted context omitted.
As far as state-of-the-art classification goes, this is not terribly impressive. See the recent results in something like: http://cs.stanford.edu/people/karpathy/deepimagesent/ I think the impressive thing here is that the GPU is presumably doing GIANT matrix multiplications in real time. A prediction from a neural net is just a series of matrix multiplications, and matrix multiplications are about n^2.8 in complexit…
From what i can understand what's even more impressive is that it was running on a beefed up version of their latest mobile SOC and not on some 5000$ compute GPU card. Which means that this application can be both very affordable and very practical since people won't put a 300W GPU in their car.
The CEO butting in all the time was really annoying, had a business partner that did this in meetings all the time - its fucking annoying and rude. On the surface I have no idea if this is ground breaking or not, my first thought was ahh nVidia using Linux!
The CEO butting in all the time was really annoying, had a business partner that did this in meetings all the time - its fucking annoying and rude. On the surface I have no idea if this is ground breaking or not, my first thought was ahh nVidia using Linux!
The CEO butting in all the time was really annoying, had a business partner that did this in meetings all the time - its fucking annoying and rude. On the surface I have no idea if this is ground breaking or not, my first thought was ahh nVidia using Linux!
Earlier quoted context omitted.
From what i can understand what's even more impressive is that it was running on a beefed up version of their latest mobile SOC and not on some 5000$ compute GPU card. Which means that this application can be both very affordable and very practical since people won't put a 300W GPU in their car.
Definitely agreed. When well-maintained and easy to use machine learning libraries meet very powerful, highly embeddable GPUs (or other dedicated linear algebra sort of hardware), I think we'll see a big revolution in the whole "smart object" field. Right now you have iPhones and whatnot doing touch ID with fingerprints, but imagine if your phone could recognize you just by quickly analyzing the gyro data as you rais…
https://www.youtube.com/watch?v=Gn83Psbv61I
ps: I'm not sure it was fully real-time though, the door avoidance restart seemed a little too nicely cued.
Looks great! Can anyone with more knowledge about deep learning say whether this is an exceptional achievement in the field ?
If the net learns based on pixels you still have to somehow solve rotation and scale invariance. Or is there something new in deep-learning vs. old-school neural nets that fixes the issues that bedeviled neural nets the first time they were popular?
Cool demo but I still wonder if fundamentally this is just a brute-force approach. Wouldn't it be better to do some traditional preprocessing (e.g. recognizing rectangles, circles, etc.) and feeding higher-level descriptors into the classifier? If the net learns based on pixels you still have to somehow solve rotation and scale invariance. Or is there something new in deep-learning vs. old-school neural nets that fix…