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They probably weren’t inspired by [Jeff Dunham’s] jalapeno on a stick, but Intel have created the Movidius neural compute stick which is in effect a neural network in a USB stick form factor. They don’t rely on the cloud, they require no fan, and you can get one for well under $100.
What distinguishes AI systems on a chip from traditional mobile processors is that they come with specialized neural-network processors, such as graphics processing units or GPUs, tensor processing units or TPUs, and field programming gate arrays or FPGAs. These AI-optimized chips offload neural-network processing from the device’s central processing unit chip, enabling more local autonomous AI processing
Are we about to see another computing revolution and what will the technological and sociopolitical landscape look like after this?
(Score: 4, Interesting) by Virindi on Sunday April 29 2018, @02:06PM (5 children)
"AI" is currently a hype bubble, just like "blockchain".
While neural networks are genuinely useful for a lot of search and pattern matching tasks, people who don't really understand are hyping up the subject as though it can solve every problem and change civilization. I do not believe the end result will be so stark a change.
One area that "AI" is being pushed hard to operate in is systems that guess what the user wants to do, such as Netflix shows, "suggested items" for sale, Google searches, etc. Many act like this is the most promising application. However, the results of these systems are all horrible. Netflix cannot magically guess what I want to watch (the suggestions are terrible, the better results are from merely listing categories that are most frequently viewed). Amazon suggests stupid products that I would never buy. Google searches still return hundreds of pages of SEO except when they can filter them by rating higher "pages that other people have clicked on". Google autocomplete almost never gives a useful search.
Natural language processing? It is a little better now but not much. Still everytime someone uses an Echo, I witness them struggle with the device misunderstanding, or merely not being able to deal with the request. To interact, you have to use a fixed vocabulary and grammatical structure...just like the old days, but now it knows more words and more ways of phrasing each request. A natural result of a huge development effort to input such things.
Now don't get me wrong, neural networks have certainly demonstrated they can improve some things, and will continue to. For instance, from the example above, speech recognition. Or, object recognition. Neural networks are good at finding patterns...however, people act like they will be able to find a pattern where no pattern exists. This is hype.
Also, they are mostly applicable only to recognition or filtering tasks where a large amount of data can be gathered for training. When you have a small amount of data, it won't work too well either.
Basically "AI" is not some earth shattering, society changing thing. It is in reality a set of incremental improvements to matching and filtering tasks. But right now the hype level is off the charts, far out of proportion with the actual results. The big tech companies are responsible for this; they want to collect as much information as possible on you. Using it to train any kind of neural network they can think of is a good use for it.
(Score: 2) by takyon on Sunday April 29 2018, @02:24PM (2 children)
We're getting to a point where all new smartphone SoCs will include dedicated machine learning/neural network hardware:
Apple Wants to Add Machine Learning Chips to Smartphone SoCs [soylentnews.org]
The AI hardware doesn't necessarily need a plethora of third-party killer apps to become useful. For example, Google's Pixel 2 smartphone includes the "Pixel Visual Core" [engadget.com] to assist the camera. The amount of people with this hardware will rise even before third-party developers do anything useful with it [techcrunch.com].
Netflix, Amazon, and Google have all been returning irrelevant results/recommendations for many years, coloring your perception of what's possible. That's not to say that Netflix recommendations will become perfect one day, but they are probably not crunching your view history to the extent that they could be. And if storage (personal data + habits) and ML processing power increase by an order of magnitude, that could allow another percent or two of "correctness" to be squeezed out of these models. This will tide people over until brain-computer interfaces gain traction.
[SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
(Score: 2) by Virindi on Sunday April 29 2018, @02:30PM (1 child)
A percent or two? Sure, probably more than that. But we have a massive hype machine grinding away telling us that the magic AI can anticipate our every desire before we desire it. This is marketing. Current systems are nowhere near as good as they act like they are, and the performance of future systems is hypothetical and subject to diminishing returns as it gets harder to get more training data, you approach the best possible confidence based on signal/noise ratio, etc.
(Score: 2) by takyon on Sunday April 29 2018, @02:45PM
They can do pretty interesting things [youtube.com]. Get used to hype, every new thing gets hyped.
[SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
(Score: 2) by VLM on Sunday April 29 2018, @03:12PM (1 child)
I'm old enough to remember the original "AI Winter" and when the present bubble bursts the second AI winter will likely be kinda icky.
(Score: 2) by takyon on Sunday April 29 2018, @03:30PM
Google's TPUs speed up the company's translation, search, etc. while reducing costs and power consumption. It's also behind many image/pattern recognition techniques and driverless cars. Even people not financially involved can use their GPUs to create #deepfake porn. Machine learning is not going away, no matter what you may think. Any bubble bursting will be a temporary speed bump and a great time for the tech giants to snap up companies and talent for cheap. Yes, they would welcome the burst with faces of glee. They worry about the advertising bubble bursting, not AI.
[SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]