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Gone are the days when a single company could dominate any aspect of technology to the exclusion of all others. That was how the tech world started out, with Intel (INTC - Free Report) dominating chips, Microsoft (MSFT - Free Report) operating systems, Cisco (CSCO - Free Report) networking, IBM (IBM - Free Report) computers, and so on.
Intel has enjoyed its dominance long enough, first in client devices and then in servers. And there’s little reason to think that its position in these two markets will shrink materially, at least in the next few years. So even as growth in the client computing market remains elusive and its data center business remains impacted by transition issues at enterprises, Intel will still generate substantial cash flows.
We can rue over the company’s missing out on the huge mobile opportunity, but let’s also remember that the market doesn’t offer good margins and isn’t that compute intensive, which is Intel’s core expertise. This is partly why Intel tried and failed to grab a toe-hold in the segment. So what’s the next big growth engine for Intel that it simply can’t afford to miss out on? And is the company devoting adequate resources to the area that will bear fruit in time for it to generate some growth for investors?
Enter Artificial Intelligence
We’ve been told from the start that graphic processing units (GPUs) are best suited in situations where parallel processing is required because that’s what they do to help the machine understand images and video. So when computer models called deep neural networks (DNNs) are built replicating the logic patterns of human brains (to read input signals in sounds, pictures and text), GPUs prove very effective. Sequential processing isn’t required until this information is properly categorized and a decision with respect to them is required, which is when Intel’s processors enter the picture.
Does this mean that there’s no scope for Intel technology in a segment of this emerging high-compute market? That may not be the case. Intel closed its $16.7 billion acquisition of field-programmable-gate-array (FPGA) maker Altera in Dec 2015 after working together for a while. It also picked up Nervana for $350 million, hoping that its Nervana Engine (to launch this year) will give it a leg up. The Nervana Engine trims down the general purpose GPU architecture to make it more efficient in handling deep-learning algorithms to deliver (hopefully) 10X as much compute power as the best GPUs today. These algorithms can imitate tasks by searching for and comparing with previously stored and labelled data.
The Intel mode of operation goes something like this: let the main processor pick up data signals and offload complexity to an integrated FPGA called accelerator, such that the main processor isn’t over-burdened. This way, even if it doesn’t exactly offer parallel processing, the Intel solution can handle complex data.
But why should somebody switch from the tried and tested GPU system that NVIDIA (NVDA - Free Report) already offers to Intel’s untried model, especially if it can’t offer much superior performance? An Intel prototype isn’t available yet for performance comparison with GPUs, but earlier this year, Intel did discuss some of its own findings.
To cut a long and very technical story short, DNN algorithms are evolving toward compact low precision data types (smaller data units) and sparsing (skipping computations involving only 0s), that greatly increase system efficiency but require irregular parallel processing. Intel believes that its solutions are better equipped to handle this irregularity than GPUs in their current state because FPGAs can be reconfigured.
Here are the numbers: Intel Stratix 10 FPGA is 10%, 50%, and 5.4x better in performance (TOP/sec) than Titan X Pascal GPU on GEMMs for sparse, Int6, and binarized DNNs, respectively. On Ternary-ResNet, the Stratix 10 FPGA can deliver 60% better performance over Titan X Pascal GPU, while being 2.3x better in performance/watt. So there’s a chance that the Intel solution can be better, but we’ll have to wait for a real product and independent testing and of course NVIDIA won’t be sitting around waiting for Intel to grab its market.
Intel's Broader Product Range
While NVIDIA’s model allows it to make more profit from its CUDA platform, Intel can offer a deep learning solution, complete with all the software, storage and compute components. It is also investing to build comprehensive solutions for self-driving (a huge opportunity), retail and other IoT, where artificial intelligence will be a necessary part. So Intel could end up with not only higher sales but also higher profits.
So How Big Is the Opportunity?
Mr. Sachin Garg, Associate Director at MarketsandMarkets, says that the global artificial intelligence chipset market should be worth $16.06 billion by 2022, growing at a CAGR of 62.9% between 2016 and 2022.
Wrapping Up
Intel may have posted decent enough results this past quarter, a natural consequence of the stronger PC market, over which it has a strangle-hold. But it isn’t an indication of what’s coming. The future such as we know it today seems to be brightening for Intel, as it prepares for the AI revolution. And in spite of the growing competition from NVIDIA and others, it doesn’t look like it will be locked out.
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Image: Bigstock
Should You Invest in Intel (INTC) Now?
Gone are the days when a single company could dominate any aspect of technology to the exclusion of all others. That was how the tech world started out, with Intel (INTC - Free Report) dominating chips, Microsoft (MSFT - Free Report) operating systems, Cisco (CSCO - Free Report) networking, IBM (IBM - Free Report) computers, and so on.
Intel has enjoyed its dominance long enough, first in client devices and then in servers. And there’s little reason to think that its position in these two markets will shrink materially, at least in the next few years. So even as growth in the client computing market remains elusive and its data center business remains impacted by transition issues at enterprises, Intel will still generate substantial cash flows.
We can rue over the company’s missing out on the huge mobile opportunity, but let’s also remember that the market doesn’t offer good margins and isn’t that compute intensive, which is Intel’s core expertise. This is partly why Intel tried and failed to grab a toe-hold in the segment. So what’s the next big growth engine for Intel that it simply can’t afford to miss out on? And is the company devoting adequate resources to the area that will bear fruit in time for it to generate some growth for investors?
Enter Artificial Intelligence
We’ve been told from the start that graphic processing units (GPUs) are best suited in situations where parallel processing is required because that’s what they do to help the machine understand images and video. So when computer models called deep neural networks (DNNs) are built replicating the logic patterns of human brains (to read input signals in sounds, pictures and text), GPUs prove very effective. Sequential processing isn’t required until this information is properly categorized and a decision with respect to them is required, which is when Intel’s processors enter the picture.
Does this mean that there’s no scope for Intel technology in a segment of this emerging high-compute market? That may not be the case. Intel closed its $16.7 billion acquisition of field-programmable-gate-array (FPGA) maker Altera in Dec 2015 after working together for a while. It also picked up Nervana for $350 million, hoping that its Nervana Engine (to launch this year) will give it a leg up. The Nervana Engine trims down the general purpose GPU architecture to make it more efficient in handling deep-learning algorithms to deliver (hopefully) 10X as much compute power as the best GPUs today. These algorithms can imitate tasks by searching for and comparing with previously stored and labelled data.
The Intel mode of operation goes something like this: let the main processor pick up data signals and offload complexity to an integrated FPGA called accelerator, such that the main processor isn’t over-burdened. This way, even if it doesn’t exactly offer parallel processing, the Intel solution can handle complex data.
But why should somebody switch from the tried and tested GPU system that NVIDIA (NVDA - Free Report) already offers to Intel’s untried model, especially if it can’t offer much superior performance? An Intel prototype isn’t available yet for performance comparison with GPUs, but earlier this year, Intel did discuss some of its own findings.
To cut a long and very technical story short, DNN algorithms are evolving toward compact low precision data types (smaller data units) and sparsing (skipping computations involving only 0s), that greatly increase system efficiency but require irregular parallel processing. Intel believes that its solutions are better equipped to handle this irregularity than GPUs in their current state because FPGAs can be reconfigured.
Here are the numbers: Intel Stratix 10 FPGA is 10%, 50%, and 5.4x better in performance (TOP/sec) than Titan X Pascal GPU on GEMMs for sparse, Int6, and binarized DNNs, respectively. On Ternary-ResNet, the Stratix 10 FPGA can deliver 60% better performance over Titan X Pascal GPU, while being 2.3x better in performance/watt. So there’s a chance that the Intel solution can be better, but we’ll have to wait for a real product and independent testing and of course NVIDIA won’t be sitting around waiting for Intel to grab its market.
Intel's Broader Product Range
While NVIDIA’s model allows it to make more profit from its CUDA platform, Intel can offer a deep learning solution, complete with all the software, storage and compute components. It is also investing to build comprehensive solutions for self-driving (a huge opportunity), retail and other IoT, where artificial intelligence will be a necessary part. So Intel could end up with not only higher sales but also higher profits.
So How Big Is the Opportunity?
Mr. Sachin Garg, Associate Director at MarketsandMarkets, says that the global artificial intelligence chipset market should be worth $16.06 billion by 2022, growing at a CAGR of 62.9% between 2016 and 2022.
Wrapping Up
Intel may have posted decent enough results this past quarter, a natural consequence of the stronger PC market, over which it has a strangle-hold. But it isn’t an indication of what’s coming. The future such as we know it today seems to be brightening for Intel, as it prepares for the AI revolution. And in spite of the growing competition from NVIDIA and others, it doesn’t look like it will be locked out.
Intel shares carry a Zacks Rank #2 (Buy). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.
5 Trades Could Profit "Big-League" from Trump Policies
If the stocks above spark your interest, wait until you look into companies primed to make substantial gains from Washington's changing course.
Today Zacks reveals 5 tickers that could benefit from new trends like streamlined drug approvals, tariffs, lower taxes, higher interest rates, and spending surges in defense and infrastructure.
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