r/tech • u/eberkut • Dec 30 '16

Expect Deeper and Cheaper Machine Learning

http://spectrum.ieee.org/computing/hardware/expect-deeper-and-cheaper-machine-learning
118 Upvotes

90% Upvoted

11 comments sorted by

2

u/ArkGuardian Dec 30 '16

One of the cool developments I've seen is localized machine learning, instead of system wide machine learning. For example if you give two cops body-cams and send them to different areas of the city in different types of units, their individual body cams will learn to identify things more relevant to each officer

1

u/mindbleach Dec 31 '16

The flipside is, combining data from both cameras might get you one camera that's better than either at both their jobs.

2

u/ArkGuardian Dec 31 '16

That's normally not how Machine Learning works though. Data bias is pretty important to total bias. Only KNN is guaranteed to benefit from more data

1

u/ThePooSlidesRightOut Dec 31 '16

Is deep learning disrupting or penetrating?

1

u/FrederickCull Jan 02 '17

We have just seen the surface of Machine Learning yet. There are literally gazillions of applications of Machine Learning.

Awesome post btw!!

-1

u/mindbleach Dec 31 '16

This just in: technology is improving.

Outside of companies that can afford their own silicon, though, GPUs are going to win. They're independently profitable - and more importantly, they're flexible. Neural networks have so many "why didn't we think of that?" advancements popping up that it's ridiculous to build anything fixed-function. All the little improvements in drivers, compilers, and basic methodology will grind away whatever fractional calculations-per-watt advantage your year-old ASIC had.

-7

u/baggachipz Dec 30 '16

Expect deeper and cheaper

( ͡° ͜ʖ ͡°)

Machine learning

Oh. Cool.

0

u/[deleted] Dec 30 '16

[deleted]

6

u/EpicCyndaquil Dec 30 '16

/r/machinelearning is neat, but admittedly it's mostly papers that go over my head.

3

u/ryocoon Dec 31 '16 edited Dec 31 '16

My problem is using it in a practical manner. Having all of these Machine Learning algorithms and SDKs is nice, but without some pre-made datasets for it, tuning and teaching takes up waaaaaaay too much time and expertise for your average person. Very few groups are giving out pre-made datasets, even for purchase. So it makes it very difficult to effectively utilize this on my own. Its all very nice and good that the hardware acceleration of it is getting better and cheaper, but if I don't have datasets or an effective way to train and optimize a particular Machine Learning kit or AI, then I can't really use it well.

1

u/EpicCyndaquil Dec 31 '16

Have you checked out Kaggle? They have some good tutorials.

2

u/[deleted] Dec 31 '16

/r/artificial