01. Jim McHugh, NVIDIA, Visits theCUBE !. (00:21)
02. What Are The Hot Topics You've Been Talking About Here. (00:52)
03. What Happened With The Google Car Getting So Big. (02:48)
04. Is Every Run Of The Google Car Pick Up A Lot Of Data. (04:15)
05. Is The List Of What Human's Can Do That Machines Can't Dwindling. (05:45)
06. Is The Key To Change The Variable. (07:40)
07. Talk About The Ecosystem Around NVIDIA. (10:03)
08. What Is The Market Going To Look Like In Five Years. (12:32)
#theCUBE #NVIDIA #BigDataNYC #SiliconANGLE #BigDataWeek
--- ---
Will new GPUs steal your job, or make you better at it? | #BigDataNYC
by R. Danes | Sep 28, 2016
Employees at modern-day enterprises likely perform a host of tasks in a day — some of such complexity they require considerable thought; others can be achieved on autopilot. But through history, one sees that automated, seemingly insignificant tasks were once unimaginable feats. They are possible now only through the work of many innovators and technologists of yesteryear. Some say we are now on the cusp of another major jump in work efficiency and productivity thanks to emerging technologies — like GPU (graphics processing unit) computing, for one.
“I tell people it’s a new computing model,” said Jim McHugh, VP and GM of NVIDIA Corp. Sitting down with Dave Vellante (@dvellante) and Jeff Frick (@JeffFrick), cohosts of theCUBE, from the SiliconANGLE Media team, during BigDataNYC 2016, McHugh explained that the increased speed offered by GPU use is going to open undreamed of avenues to innovation and creativity.
“If you have to wait for a query for 10 seconds, but on your average dashboard, or as you’re looking at the data, there’s 10 to 15 queries — 10 seconds times each of those just adds up to too much time,” McHugh said.
Human resource revolution
McHugh said that GPUs give that time back to the employee for mental work. “You’re already on to your third or fourth exploration of the data, while the first guy is still waiting for it to return,” he said. The end result of this will be talent producing on a higher level than ever before possible.
“One of the most treasured people who work for you — a data scientist — we frustrate him,” McHugh said. “Where’s the gold in that? You’re trying to keep the guy there. Give him the tools that allow him to explore.”
AI: Artificial Imagination
McHugh also spoke about exciting uses for GPUs in self-driving cars. “We’re can now do augmented reality where we’re using that to train cars,” he said, adding that deep learning allows the cars to get smarter with every drive.
#BigDataNYC
#theCUBE
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Jim McHugh, NVIDIA | Big Data new York City 2016
01. Jim McHugh, NVIDIA, Visits theCUBE !. (00:21)
02. What Are The Hot Topics You've Been Talking About Here. (00:52)
03. What Happened With The Google Car Getting So Big. (02:48)
04. Is Every Run Of The Google Car Pick Up A Lot Of Data. (04:15)
05. Is The List Of What Human's Can Do That Machines Can't Dwindling. (05:45)
06. Is The Key To Change The Variable. (07:40)
07. Talk About The Ecosystem Around NVIDIA. (10:03)
08. What Is The Market Going To Look Like In Five Years. (12:32)
#theCUBE #NVIDIA #BigDataNYC #SiliconANGLE #BigDataWeek
--- ---
Will new GPUs steal your job, or make you better at it? | #BigDataNYC
by R. Danes | Sep 28, 2016
Employees at modern-day enterprises likely perform a host of tasks in a day — some of such complexity they require considerable thought; others can be achieved on autopilot. But through history, one sees that automated, seemingly insignificant tasks were once unimaginable feats. They are possible now only through the work of many innovators and technologists of yesteryear. Some say we are now on the cusp of another major jump in work efficiency and productivity thanks to emerging technologies — like GPU (graphics processing unit) computing, for one.
“I tell people it’s a new computing model,” said Jim McHugh, VP and GM of NVIDIA Corp. Sitting down with Dave Vellante (@dvellante) and Jeff Frick (@JeffFrick), cohosts of theCUBE, from the SiliconANGLE Media team, during BigDataNYC 2016, McHugh explained that the increased speed offered by GPU use is going to open undreamed of avenues to innovation and creativity.
“If you have to wait for a query for 10 seconds, but on your average dashboard, or as you’re looking at the data, there’s 10 to 15 queries — 10 seconds times each of those just adds up to too much time,” McHugh said.
Human resource revolution
McHugh said that GPUs give that time back to the employee for mental work. “You’re already on to your third or fourth exploration of the data, while the first guy is still waiting for it to return,” he said. The end result of this will be talent producing on a higher level than ever before possible.
“One of the most treasured people who work for you — a data scientist — we frustrate him,” McHugh said. “Where’s the gold in that? You’re trying to keep the guy there. Give him the tools that allow him to explore.”
AI: Artificial Imagination
McHugh also spoke about exciting uses for GPUs in self-driving cars. “We’re can now do augmented reality where we’re using that to train cars,” he said, adding that deep learning allows the cars to get smarter with every drive.
#BigDataNYC
#theCUBE
