{"id":340195,"date":"2017-05-06T02:00:18","date_gmt":"2017-05-05T18:00:18","guid":{"rendered":"http:\/\/techcrunch.com\/?p=1485663"},"modified":"2017-05-06T02:00:18","modified_gmt":"2017-05-05T18:00:18","slug":"ai-everywhere","status":"publish","type":"post","link":"https:\/\/people.utm.my\/asmawisham\/ai-everywhere\/","title":{"rendered":"AI everywhere"},"content":{"rendered":"

I asked Huang to compare the GTC of eight years ago to the GTC of today, given how much of Nvidia\u2019s focus has changed.<\/p>\n

\u201cWe invented a computing model called GPU accelerated computing and we introduced it almost slightly over 10 years ago,\u201d Huang said, noting that while AI is only recently dominating tech news headlines, the company was working on the foundation long before that. \u201cAnd so we started evangelizing all over the world. GTC is our developers conference for that. The first year, with just a few hundred people, we were mostly focused in two areas: They were focused in computer graphics, of course, and physics simulation, whether it\u2019s finite element analysis or fluid simulations or molecular dynamics. It\u2019s basically Newtonian physics.\u201d<\/p>\n

A lot can change in a decade, however, and Huang points to a few things that have changed in the past 10\u00a0years that have shifted the landscape in which Nvidia operates.<\/p>\n

\u201cThe first thing is that Moore\u2019s Law has really slowed,\u201d he said. \u201cSo as a result GPU-accelerated computing gave us life after Moore\u2019s Law, and it extended the capability of computing so that these applications that desperately need more computing can continue to advance. Meanwhile, the reach of GPUs has\u00a0gone far and wide, and it\u2019s much more than computer graphics today. We\u2019ve reached out into all fields \u2014 of course computer graphics, virtual reality, augmented reality \u2014 to all kinds of interesting and challenging physics simulations.\u201d<\/p>\n

But it doesn\u2019t end there. Nvidia\u2019s tech now resides in many of the world\u2019s most powerful supercomputers, and the applications include fields that were once considered beyond the realm of modern computing capabilities. However,\u00a0the train that Nvidia has been riding to great success recently, AI, was a later development still.<\/p>\n

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“AI is just the modern way of doing software.”<\/p>\n<\/blockquote>\n<\/div>\n

\u201cAlmost every supercomputer in the world today has some form of acceleration, much of it from Nvidia,\u201d Huang told me. \u201cAnd then there was quantum mechanics. The field of quantum chemistry is going quite well and there\u2019s a great deal of research in quantum chemistry, in quantum mechanics. And then several years ago \u2013 I would say about five years ago \u2013 we saw an emergence of a new field in computer science called deep learning. And deep learning, combined with the rich amount of data that\u2019s available, and the processing capability came together to become what people call the Big Bang of modern AI.\u201d<\/p>\n

This was a landscape shift that moved Nvidia from the periphery. Now, Nvidia\u2019s graphics hardware occupies a more pivotal role, according to Huang \u2013 and the company\u2019s long list of high-profile partners, including Microsoft, Facebook and others, bears him out.<\/p>\n

GPUs really have become the center of the AI universe, though some alternatives like FPGAs are starting to appear, as well. At GTC, Nvidia has had many industry-leading partners onstage and off, and this year will be no exception: Microsoft, Facebook, Google and Amazon will all be present. It\u2019s also a hub for researchers, and representatives from\u00a0the University of Toronto, Berkeley, Stanford, MIT, Tsinghua University, the Max Plank Institutes and many more will also be in attendance.<\/p>\n

GTC, in other words, has evolved into arguably the biggest developer event focused on artificial intelligence in the world. Nowhere else can you find most of the major tech companies in the world, along with academic and research organizations under one roof. And Nvidia is also focusing on bringing a third group more into the mix: startups.<\/p>\n

Nvidia has an accelerator program called Inception<\/a> that Huang says is its AI platform for startups. About 2,000 startups participate,\u00a0getting support from Nvidia in one form or another, including\u00a0financing, platform access, exposure to experts and more.<\/p>\n

Huang also notes that GTC is an event for different industry partners, including GlaxoSmithKline, Procter &\u00a0Gamble and GE Healthcare. Some of these industry-side partners would previously have been out of place even at very general computing events. That\u2019s because, unlike with the onset of smartphones, AI isn\u2019t just changing how you present computing products to a user, but also what areas actually represent opportunities for computing innovation, according to Huang.<\/p>\n

\u201cAI is eating software,\u201d Huang continued. \u201cThe way to think about it is that\u00a0AI is just the modern way of doing software. In the future, we\u2019re not going to see software that is not going to continue to learn over time, and be able to perceive and reason, and plan actions and that continues to improve as we use it. These machine-learning approaches, these artificial intelligence-based approaches, will define how software is developed in the future. Just about every startup company does software these days,\u00a0and even non-startup companies do their own software. Similarly, every startup in the future will have AI.\u201d<\/p>\n

Nor will this be limited to cloud-based intelligence, resident in powerful, gigantic data centers. Huang notes that we\u2019re now able to apply computing to things where before it made no sense to do so, including to air conditioners and other relatively \u2018dumb\u2019 objects.<\/p>\n

\u201cYou\u2019ve got cars, you\u2019ve got drones, you\u2019ve got microphones; in the future, almost every electronic device will have some form of deep learning inferencing within it.\u00a0We call that AI at the edge,\u201d he said. \u201cAnd eventually there\u2019ll be a trillion devices out there: Vending machines; every microphone; every camera; every house will have deep learning capability. And some of it needs a lot of performance; some of it doesn\u2019t need a lot of performance. Some of it needs a lot of flexibility because it continues to evolve and get smarter. Some of it doesn\u2019t have to get smarter.\u00a0And we\u2019ll have custom solutions for it all.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

\"\" Nvidia’s Jensen Huang is one of those rare CEOs who has, for a remarkably long and storied period, been at the helm of a company he helped create. What began as a provider of relatively niche graphics processing units (GPUs) with a narrow field of general computing uses has evolved to become, arguably, the bedrock underlying the current AI market explosion. Read More<\/a><\/p>\n

\n<\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a> <\/img><\/a>\n<\/div>\n

\"\"\/ <\/p>\n","protected":false},"author":5817,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[25],"tags":[59,66,26],"class_list":["post-340195","post","type-post","status-publish","format-standard","hentry","category-technology","tag-media","tag-techcrunch","tag-technology"],"_links":{"self":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts\/340195","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/users\/5817"}],"replies":[{"embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/comments?post=340195"}],"version-history":[{"count":0,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts\/340195\/revisions"}],"wp:attachment":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/media?parent=340195"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/categories?post=340195"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/tags?post=340195"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}