Why Nvidia's stock Has Soared, Whereas Intel's Remains Flatlined?

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Intel on the outside l The rise of artificial intelligence is creating new variety in the chip market, and trouble for Intel; The success of Nvidia and its new computing chip signals rapid change in IT architecture. Economist, Feb 23, 2017.
http://www.economist.com/news/bu ... nge-it-architecture

Quote:

"A big part of Nvidia's success is because demand is growing quickly for its chips, called graphics processing units (GPUs), which turn personal computers into fast gaming devices. But the GPUs also have new destinations: notably data centres where artificial-intelligence (AI) programmes gobble up the vast quantities of computing power that they generate.  Soaring sales of these chips are the clearest sign yet of a secular shift in information technology.

"Whether in PCs or in servers (souped-up computers in data centres), one kind of microprocessor, known as a 'central processing unit' (CPU), could deal with most 'workloads,' as classes of computing tasks are called. Because Intel made the most powerful CPUs, it came to rule not only the market for PC processors (it has a market share of about 80%) but the one for servers, where it has an almost complete monopoly. In 2016 it had revenues of nearly $60bn [compared with Nvidia's $6.91bn, up 38% from revenue of $5.01 billion in the year ago same period: Nvidia announced on Feb 09, 2017].  This unipolar world is starting to crumble. Processors [CPUs] are no longer improving quickly enough to be able to handle, for instance, machine learning and other AI applications, which require huge amounts of data and hence consume more number-crunching power than entire data centres did just a few years ago.

"GPUs have hundreds of specialised 'cores' (the 'brains' of a processor), all working in parallel, whereas CPUs have only a few powerful ones that tackle computing tasks sequentially [take notice: not parallelly]. Nvidia's latest processors boast 3,584 cores; Intel's server CPUs have a maximum of 28.

"The company's [Nvidia's] lucky break came in the midst of one of its near-death experiences during the 2008-09 global financial crisis. It discovered that hedge funds and research institutes were using its chips for new purposes, such as calculating complex investment and climate models. It developed a coding language, called CUDA [acronym for 'Compute Unified Device Architecture'], that helps its customers program its processors for different tasks. When cloud computing, big data and AI gathered momentum a few years ago, Nvidia's chips were just what was needed.

"And GPUs are only one sort of 'accelerator,' as such specialised processors are known. The range[:] * * * At one end of the range are ASICs, an acronym for 'application-specific integrated circuits.' As the term suggests, they are hard-wired for one purpose and are the fastest on the menu as well as the most energy-efficient. * * * The other extreme is field-programmable gate arrays (FPGAs). These can be programmed, meaning greater flexibility

"the quickening rise of accelerators appears to be bad news for the company [Intel]

Note: "Intel on the outside" needles Intel's "Intel Inside" commercials.