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AI everywhere

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"We invented a computing model called GPU accelerated computing and we introduced it almost slightly over 10 years ago," Huang said, noting that while AI is only recently dominating tech news headlines, the company was working on the foundation long before that. Nvidia's tech now resides in many of the world's most powerful supercomputers, and the applications include fields that were once considered beyond the realm of modern computing capabilities. Now, Nvidia's graphics hardware occupies a more pivotal role, according to Huang – and the company's long list of high-profile partners, including Microsoft, Facebook and others, bears him out. GTC, in other words, has evolved into arguably the biggest developer event focused on artificial intelligence in the world.


Tesla P100 by Nvidia is the biggest chip with 15 billion transistors

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Every technological gadget and machines rely on chips to perform its operations and activities. One of the leading company, Nvidia has recently announced the launch of Tesla P100, a data centre accelerator of 15 billion transistor chip. It is specifically designed for deep learning AI technology. Nvidia has made the announcement regarding Tesla P100 at the GPU conference held in San Jose, California. Jen-Hsun Huang, the CEO has asserted that Tesla P100 is the world's largest chip till date with 15 billion transistors on a single chip.


The New Intel: How Nvidia Went From Powering Video Games To Revolutionizing Artificial Intelligence

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Nvidia cofounder Chris Malachowsky is eating a sausage omelet and sipping burnt coffee in a Denny's off the Berryessa overpass in San Jose. It was in this same dingy diner in April 1993 that three young electrical engineers--Malachowsky, Curtis Priem and Nvidia's current CEO, Jen-Hsun Huang--started a company devoted to making specialized chips that would generate faster and more realistic graphics for video games. East San Jose was a rough part of town back then--the front of the restaurant was pocked with bullet holes from people shooting at parked cop cars--and no one could have guessed that the three men drinking endless cups of coffee were laying the foundation for a company that would define computing in the early 21st century in the same way that Intel did in the 1990s. "There was no market in 1993, but we saw a wave coming," Malachowsky says. "There's a California surfing competition that happens in a five-month window every year.


The New Intel: How Nvidia Went From Powering Video Games To Revolutionizing Artificial Intelligence

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Nvidia cofounder Chris Malachowsky is eating a sausage omelet and sipping burnt coffee in a Denny's off the Berryessa overpass in San Jose. It was in this same dingy diner in April 1993 that three young electrical engineers--Malachowsky, Curtis Priem and Nvidia's current CEO, Jen-Hsun Huang--started a company devoted to making specialized chips that would generate faster and more realistic graphics for video games. East San Jose was a rough part of town back then--the front of the restaurant was pocked with bullet holes from people shooting at parked cop cars--and no one could have guessed that the three men drinking endless cups of coffee were laying the foundation for a company that would define computing in the early 21st century in the same way that Intel did in the 1990s. "There was no market in 1993, but we saw a wave coming," Malachowsky says. "There's a California surfing competition that happens in a five-month window every year.


The New Intel: How Nvidia Went From Powering Video Games To Revolutionizing Artificial Intelligence

#artificialintelligence

It was in this same dingy diner in April 1993 that three young electrical engineers--Malachowsky, Curtis Priem and Nvidia's current CEO, Jen-Hsun Huang--started a company devoted to making specialized chips that would generate faster and more realistic graphics for video games. "We've been investing in a lot of startups applying deep learning to many areas, and every single one effectively comes in building on Nvidia's platform," says Marc Andreessen of venture capital firm Andreessen Horowitz. Starting in 2006, Nvidia released a programming tool kit called CUDA that allowed coders to easily program each individual pixel on a screen. From his bedroom, Krizhevsky had plugged 1.2 million images into a deep learning neural network powered by two Nvidia GeForce gaming cards.


The New Intel: How Nvidia Went From Powering Video Games To Revolutionizing Artificial Intelligence

#artificialintelligence

Nvidia cofounder Chris Malachowsky is eating a sausage omelet and sipping burnt coffee in a Denny's off the Berryessa overpass in San Jose. It was in this same dingy diner in April 1993 that three young electrical engineers–Malachowsky, Curtis Priem and Nvidia's current CEO, Jen-Hsun Huang–started a company devoted to making specialized chips that would generate faster and more realistic graphics for video games. East San Jose was a rough part of town back then–the front of the restaurant was pocked with bullet holes from people shooting at parked cop cars–and no one could have guessed that the three men drinking endless cups of coffee were laying the foundation for a company that would define computing in the early 21st century in the same way that Intel did in the 1990s. "There was no market in 1993, but we saw a wave coming," Malachowsky says. "There's a California surfing competition that happens in a five-month window every year.


Nvidia CEO's "Hyper-Moore's Law" Vision for Future Supercomputers

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Over the last year in particular, we have documented the merger between high performance computing and deep learning and its various shared hardware and software ties. This next year promises far more on both horizons and while GPU maker Nvidia might not have seen it coming to this extent when it was outfitting its first GPUs on the former top "Titan" supercomputer, the company sensed a mesh on the horizon when the first hyperscale deep learning shops were deploying CUDA and GPUs to train neural networks. All of this portends an exciting year ahead and for once, the mighty CPU is not the subject of the keenest interest. Instead, the action is unfolding around the CPU's role alongside accelerators; everything from Intel's approach to integrating the Nervana deep learning chips with Xeons, to Pascal and future Volta GPUs, and other novel architectures that have made waves. While Moore's Law for traditional CPU-based computing is on the decline, Jen-Hsun Huang, CEO of GPU maker, Nvidia told The Next Platform at SC16 that we are just on the precipice of a new Moore's Law-like curve of innovation--one that is driven by traditional CPUs with accelerator kickers, mixed precision capabilities, new distributed frameworks for managing both AI and supercomputing applications, and an unprecedented level of data for training.


Nvidia is GPU accelerator king

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Shah, who works Japanese financial holding company Nomura, seemed to be rather enthusiast about Nvidia's data centre business after his chat. Huang apparently was animate about the prospects for the data centre business, as hyperscale companies quickly adopt throughput computing in an effort to accelerate workload performance. Nvidia's year-on-year data center revenues grew by 63 percent last quarter, mostly due to the "broad adoption" of Tesla M40 GPU accelerator. One product name dropped included the Tesla M40 GPU was designed for machine learning, and features 3,072 CUDA cores and 12GB of GDDR5 memory, with up to seven Teraflops of single-precision performance.


Nvidia CEO "enthusiastic" about data center business, revenues grow 63% YoY

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Romit Shah, of Japanese financial holding company Nomura, has raised his rating on the shares in silicon specialist Nvidia, after spending time with CEO Jen-Hsun Huang and hearing about the company's plans for the future. Nvidia's year-on-year data center revenues grew by 63 percent last quarter, mostly due to the "broad adoption" of Tesla M40 GPU accelerator. Nvidia claims that for machine learning workloads, the accelerator can deliver eight times more compute than a traditional CPU. Speaking to analysts earlier this year, Nvidia's CEO shared his views on the importance of machine learning: "In terms of how big that is going be, my sense is at almost no transaction with the Internet will be without deep learning or some machine learning inference in the future.


Computex 2016 verdict: Behold the new brains of the computer

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When we were planning our approach this year to covering Computex, the largest IT trade show in Asia, there was some confusion about where exactly Intel had gone. At that point there was a sense that maybe this year would be a little flat. The Taipei show has always been a big song and dance around the latest CPUs (central processing units) from Intel and the changes they'll bring to computing in the years ahead. As it turned out, Computex was fascinating. On day zero, Nvidia and Asus put on a great show that quickly reminded us that the future is moving beyond the CPU, the chip that traditionally has been the brains of the computer.