Finding Use of Graphic Chips in Artificial Intelligence

choi

Jack Clark and Ian King, Getting Graphic Chips to Think Their Own. Bloomberg BusinessWeek, Mar 7, 2016.
http://www.bloomberg.com/news/ar ... -ai-not-just-gaming

Quote:

"Nvidia’s microprocessors have long been the chips of choice for computer game addicts who crave realistic graphics * * * The same powerful semiconductors are now being put to new uses [for artificial intelligence that] underpin[ s] speech recognition systems, software to develop gene therapies, and programs that transform satellite photos into detailed maps[, as well as Google-owned and London-based DeepMind to train a computer to play Go]

"Artificial intelligence’s big advance over traditional software is that it can learn and improve without the assistance of human programmers * * * Graphics processing units, or GPUs, are well-suited for this kind of pattern recognition work because they can perform thousands of simple calculations at the same time. In contrast, standard central processors [central processing unit (CPU)] made by Intel perform more complex calculations very quickly but are limited when it comes to doing multiple things in parallel.

"Nvidia's GPUs is "helped by the chipmaker’s support of a programming language called CUDA, which lets developers repurpose GPUs for uses other than graphics. Rival Advanced Micro Devices hasn’t made a comparable investment, which has hampered the adoption of its graphics chips in this emerging field.

"AI plays a role in everything from Google searches to self-driving cars * * * Data centers are a relatively new area for Nvidia * * * Still, luring customers away from Intel’s Xeon processors, the heart of more than 99 percent of the world’s servers, may prove difficult.

Note:
(a) summary underneath the title in print: Nvidia’s processors are powering breakthroughs in deep learning

(b)
(i) CUDA
https://en.wikipedia.org/wiki/CUDA
(table: Developer(s)        NVIDIA Corporation, Initial release 2007, Stable release 2015; "When it was first introduced by NVIDIA, the name CUDA was an acronym for Compute Unified Device Architecture,[3] but NVIDIA subsequently dropped the use of the acronym" (sic; should be "dropped the use of full name" because currently full name is nowhere to be found in Nvidia's website)]
(ii) What Is CUDA?
www.nvidia.com/object/cuda_home_new.html
("CUDA® is a parallel computing platform and programming model invented by NVIDIA")

(c) "Intel’s Xeon processors"
(i) Xeon
https://en.wikipedia.org/wiki/Xeon
(CPU; a brand of x86 microprocessors; 1998- )
(ii) Not to be confused with Xenon
https://en.wikipedia.org/wiki/Xenon
(atomic number 54; a noble gas' pronunciation in the table at right; section 1 History: name)

(d) "Serkan Piantino, director of engineering for AI Research at Facebook, which uses thousands of Nvidia GPUs for AI. Still Piantino is keeping his eyes peeled for new developments. 'There’s a lot of promising stuff that’s going to land in the coming year,' he says."
(i) keep one's eyes peeled
https://en.wiktionary.org/wiki/keep_one%27s_eyes_peeled
(etymology: US, 19th century. Peeled probably refers to keeping one'e [upper] eyelids retracted [ie, keep eyes open])
(ii)  also: keep one's eyes skinned