Five Hot AI Startups Step into Spotlight at GTC Europe Inception Awards

Five hot #AI startups step into the spotlight at the #GTC17EU Inception Awards:

  • Then we gave one of them — Gamaya, a 20-person startup harnessing deep learning to help farms improve their productivity and sustainability — a new DGX Station in front of a room packed with more than 160 investors, entrepreneurs and industry observers.
  • The event’s contenders were selected from among the 700 European startups participating in our Inception program, which accelerates the development of startups involved in AI and deep learning.
  • After looking at an initial round of 25 startups, our judges chose companies we believe to be the five hottest in Europe to tell their stories.
  • Besides our winner Gamaya, the startups included presentations from: – – The Inception Awards continue the series of events we’ve held in Silicon Valley and China in conjunction with our GPU Technology Conference world tour.
  • Our Inception virtual accelerator program supports more than 1,900 AI startups with GPUs, deep learning expertise and other resources to help them be successful.

We brought five of the hottest startups in Europe and put them in front of a panel of some of tech’s savviest players at GTC Europe in Munich Tuesday.
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Data Mining History: The Invention of Support Vector Machines

#DataMining History: The Invention of Support Vector Machines  #MachineLearning

  • The invention of Support Vector Machines using the kernel trick in 1991 is my most important contribution.
  • Gregory Piatetsky: I sent Isabelle the link to History of Data Mining , which mentions her and Vapnik historic invention of Support Vector Machines, and asked if she had a description of that discovery.
  • The story starts in Paris in 1989, when I benchmarked neural networks against kernel methods, but the real invention of SVMs happened when Bernhard decided to implement Vladimir Vapnik algorithm.
  • The invention of SVMs happened when Bernhard decided to implement Vladimir’s algorithm in the three months we had left before we moved to Berkeley.
  • I had heated discussions with Vladimir Vapnik, who shared my office and was pushing another optimal margin algorithm that he invented in the 1960’s.

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@kdnuggets: “#DataMining History: The Invention of Support Vector Machines #MachineLearning”


The story starts in Paris in 1989, when I benchmarked neural networks against kernel methods, but the real invention of SVMs happened when Bernhard decided to implement Vladimir Vapnik algorithm.


Data Mining History: The Invention of Support Vector Machines