In this episode I’m joined by Jeff Dean, Google Senior Fellow and head of the company’s deep learning research team Google Brain, who I had a chance to sit down with last week at the Googleplex in Mountain View.
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As you’ll hear, I was very excited for this interview, because so many of Jeff’s contributions since he started at Google in ‘99 have touched my life and work. In our conversation, Jeff and I dig into a bunch of the core machine learning innovations we’ve seen from Google. Of course we discuss TensorFlow, and its origins and evolution at Google. We also explore AI acceleration hardware, including TPU v1, v2 and future directions from Google and the broader market in this area. We talk through the machine learning toolchain, including some things that Googlers might take for granted, and where the recently announced Cloud AutoML fits in. We also discuss Google’s process for mapping problems across a variety of domains to deep learning, and much, much more. This was definitely one of my favorite conversations, and I’m pumped to be able to share it with you.
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Are you an IT, technology or business leader who needs to get smart on the broad spectrum of machine learning and AI opportunities in the enterprise? Or, perhaps someone in your organization could benefit from a level-up in this area? (Or, maybe you would benefit from them leveling up!) If this sounds like you, or someone you know, you’ll probably be interested in my upcoming AI Summit event.
Think of the event as a two-day, no-fluff, Technical MBA in machine learning & AI. You’ll leave with a clear understanding of:
How machine learning and deep learning work (no math required)
How to identify machine learning and deep learning opportunities in your organization
How to understand and take advantage of technologies like computer vision and natural language processing
How to manage and label data to take advantage of ML and AI
And how to build an AI-first culture, and operationalize AI in your business.
You’ll have an informed perspective on what’s going on across the ML and AI landscape, and will be able to engage confidently in discussions about machine learning and AI with your colleagues, customers and partners. I’m super excited about this event and the speakers you’ll get a chance to learn from. For more information visit twimlai.com/aisummit, and feel free to contact me with your questions.
Mentioned in the Interview
- Sanjay Ghemawat
- ISCA Paper – In-Datacenter Performance Analysis of a Tensor
- Cloud AutoML
- Optimization and other update rules – Deep Learning with Theano
- Advanced Guide to Inception v3 on Cloud TPU
- National Academy of Engineers – 14 Grand Challenges for Engineering in the 21st Century
- Ryan Poplin – Predicting Cardiovascular Risk Factors from Eye Images
- Register for the AI Summit
- Check out @ShirinGlander’s Great TWIML Sketches!
- TWIML Presents: Series page
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- TWIML Meetup
- TWIML Newsletter
“More On That Later” by Lee Rosevere licensed under CC By 4.0