O'Reilly Artificial Intelligence Conference 2017 - San Francisco, CA

"Putting AI to Work" was the theme of AI San Francisco 2017 and this sold out conference delivered on that theme with more than 100 of the world's top AI researchers, engineers, data scientists, and venture capitalists presenting real-world implementations of AI in medicine, autonomou...

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Detalles Bibliográficos
Autor Corporativo: O'Reilly Artificial Intelligence Conference (-)
Otros Autores: O'Reilly Media, Inc., author (author)
Formato: Video
Idioma:Inglés
Publicado: O'Reilly Media, Inc 2017.
Edición:1st edition
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631252506719
Descripción
Sumario:"Putting AI to Work" was the theme of AI San Francisco 2017 and this sold out conference delivered on that theme with more than 100 of the world's top AI researchers, engineers, data scientists, and venture capitalists presenting real-world implementations of AI in medicine, autonomous vehicles, smart phones, voice-based personal assistants, in-store shopping, financial services, media, IoT, and more. This video compilation gives you complete access to all of the conference's 14 keynotes, 10 tutorials, and 70 plus sessions. You'll hear keynotes from Andrew Ng (Coursera) on how AI will revolutionize the world just as electricity did 100 years ago; Jia Li (Google Cloud) on why a democratized approach to AI will bestow AI's benefits to the widest audience possible; Tim O'Reilly (O'Reilly Media) on the AI design choices we must make to avoid a world ruled by hostile AI machines; and you'll get to listen to what the VC's think about AI in a keynote by Vijay Pande (Andreessen Horowitz), and a fireside chat between Steve Jurvetson (DFJ Venture Capital) and Naveen Rao (Intel). Revealing AI's important new tools and frameworks was a primary objective of AI SF 2017. You'll be able to learn about all of these advances in sessions, such as Jason Knight (Intel) on Intel's Nervana Graph project (a universal deep learning compiler); Ion Stoica's (UC Berkeley) on Ray, a new distributed execution framework for reinforcement learning applications; Mary Wahl (Microsoft) on scalable operationalization of trained CNTK and TensorFlow DNNs; and Jeremy Howard (fast.ai) on using GPU acceleration with PyTorch to make your algorithms 2,000% faster. But the real foci of the conference were the AI implementation sessions and this compilation lets you listen in on all of them. You'll learn how AI is working in medicine, with presentations on how AI uses cellular images to discover new drugs; how AI applies to healthcare's biggest opportunity—clinical variation; and how AI is helping cure cancer. From AI researchers in the transportation sector, you'll hear how affordable and reliable sensors enable computer-vision-based autonomous driving and how to train vision models for object detection. And in the world of consumer products, you'll get an overview of how Instacart uses deep learning to optimize the in-store shopping experience; an update on conversational AI in Amazon's Alexa; a preview of Intuit's AI driven self-filing tax system; a look at how deep learning is produ...
Notas:Title and publication information from resource description page (Safari, viewed October 24, 2017).
Descripción Física:1 online resource (1 video file, approximately 64 hr., 28 min.)