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Breakthrough Theory, AI in Action

Gadi Singer Vice President, Architecture General Manager, AI Products Group, Intel Corporation and Prakash Mallya, Managing Director, Sales & Marketing Group, Intel India explore how Intel build the best tools, understand the different types of compute that AI requires, and display the exciting results from our partnerships and community. The keynote address also saw insights sharing by Amazon, Arya.ai, Microsoft, Philips, Wipro, and more.

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1:31:09
Breakthrough Theory, AI in Action
Breakthrough Theory, AI in Action
20:08
Real-Life Machine Learning on AWS
Real-Life Machine Learning on AWS
17:30
How to Operationalize AI for Instant Business Impact with Intel BigDL
How to Operationalize AI for Instant Business Impact with Intel BigDL
24:52
Fast Simulation with Generative Adversarial Networks Towards Convergence of HPC and AI in High Energy Physics
Fast Simulation with Generative Adversarial Networks Towards Convergence of HPC and AI in High Energy Physics
27:20
More than Colorful Pixels: AI in Medical Imaging
More than Colorful Pixels: AI in Medical Imaging
46:44
Look Inside the Black Box: Validation of AI Models
Look Inside the Black Box: Validation of AI Models
10:02
Artificial Intelligence Solutions for the Enterprise
Artificial Intelligence Solutions for the Enterprise
1:19:33
Breakthrough Theory, AI in Action
Breakthrough Theory, AI in Action
37:40
Revolutionizing AI and Big Data
Revolutionizing AI and Big Data
32:50
Compute in the AI Era
Compute in the AI Era
16:56
The Tools Brought to Life through Data Science
The Tools Brought to Life through Data Science
23:29
AI Research: Physics, Privacy, and the Brain
AI Research: Physics, Privacy, and the Brain
30:45
Large Scale Deep Learning Applications at Baidu and Open-source AI framework PaddlePaddle
Large Scale Deep Learning Applications at Baidu and Open-source AI framework PaddlePaddle
21:27
The Evolution Path of Artificial Intelligence
The Evolution Path of Artificial Intelligence
30:20
Some Humble Thoughts about Deep Learning
Some Humble Thoughts about Deep Learning

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