ArchiTECHt Daily: Why Intel's big opportunity in AI might be IoT

The Economist has a smart (go figure) article about Intel's future in a world where artificial intell
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ArchiTECHt Daily: Why Intel's big opportunity in AI might be IoT
By ARCHITECHT • Issue #25
The Economist has a smart (go figure) article about Intel’s future in a world where artificial intelligence is all the rage—something upon which rival Nvidia is already capitalizing. While the article is correct to paint this mainly as a battle of CPU vs. GPU at the moment, it also wisely points out that Intel made a big investment in the FPGA space when in bought Altera, as well as a smaller investment in the area of AI-specific processors when it acquired Nervana Systems.
The biggest factor for Intel’s future as far as AI is concerned (there’s still a lot of money to be made in CPU-based enterprise workloads) is where all those machine learning workloads will run. If they’re running primarily in the cloud, it does not look good.
The huge web companies leading the way in AI at the moment (Google, Facebook, Amazon, Microsoft, etc.) seem to have settled on GPUs as the right architecture for training their machine learning models, a situation that’s pretty good for Nvidia. It’s an even better situation if these companies opt to also run their production AI models on GPUs, which I believe they do in many cases.
Facing GPUs and other custom-built technologies inside these companies, Intel has an uphill battle to achieve mass adoption of FPGAs and data-center-scale AI processors.
However, we’re also seeing a lot of work already to make AI frameworks run on CPUs, which are still the default option in nearly every enterprise server and consumer desktop. The idea being that if developers and enterprises actually do want to train models themselves, many will want to use chip architectures they’re with which they’re already familiar and on which they’ve already invested a lot of money.
And then there are the specialized chips designed with the Internet of Things in mind, which I’ve covered many times already in this newsletter. Intel may have missed the smartphone wave (and all the AI algorithms that will run on them going forward) but the market for AI-optimized IoT chips is still wide open, and Intel has a deep pocketbook to buy up innovative technologies. In fact, in September, Intel acquired a startup called Movidius that builds low-power hardware and software targeting computer vision.
Connected devices might actually be the killer app for brain-based chips in the shortish term, because small devices will require their smarts in a small, low-power package. The consumer world might never again care if their devices have “Intel Inside,” but they will care that they work. 
It’s always fashionable to write off Intel, and AI represents another good opportunity to do it, but there’s still room for Intel to capitalize on AI as the market matures. 
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Around the web: Artificial intelligence
What Floyd is trying to do could be really powerful. The X factor is how many developers are willing to pay (even on-demand) for infrastructure and tools, versus just messing around with TensorFlow on a laptop.
There’s probably more value in bringing all that data together into a single view than there is in automatically generating “stories.”
fortune.com  •  Share
Seems like a good recipe, or at least a good set of starting principles, for generating enough AI talent in universities to fill the need in the private sector.
medium.com  •  Share
That’s it. Although it is a pretty long list. Not on present: “Understand what it’s doing or why it’s doing it.”
medium.com  •  Share
Someone’s first order of business was to test the limits of “Perspective” and find out it’s not great at nuance. I believe it’s trainable, though, which is how it should be given the differences among publications.
This is the $64,000 question. IMHO, the biggest challenge we need to solve for is filter bubbles, which algorithms are great at creating and which are getting worse.
Around the web: Cloud and infrastructure
I suggested this when AWS announced Chime a couple weeks ago. Enterprises, especially, often buy into platforms. Displacing Microsoft at scale will require challenging it on all fronts.
And the center-of-gravity shift from server makers to cloud providers is complete. Interesting, Intel has a lot of reasons to play nice with cloud providers and perhaps less leverage than in its heyday.
fortune.com  •  Share
Not a lot new here, but Merv is a voice worth listening to in this space. Buyers and cloud providers intrigued by (or even selling) Cloud Spanner should pay attention.
Only if by “industry cloud” you mean “more SaaS, bordering on PaaS at times.” This article points to vertically focused machine learning and IoT platforms as opportunities; I think the Amazons of the world will handle the latter just fine.
Like any new processor, finding a market willing to adopt Rex’s technology will be critical. But now is definitely the time to push something new. Oh, and founder Thomas Shomers was a teenager when he started the company.
Just because
There’s a lot to be said about teaching computer science as a way of thinking, and also understanding how it fits into the greater scheme of life.
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