Silicon Valley Deep Learning Group
Our Goals and Philosophy
The Silicon Valley Deep Learning Group (SVDLG) is a not-for-profit community initiative with over 5,000 members in the San Fransisco Bay Area. SVDLG’s goal is to provide a universal point of entry and avenue of advancement for members of the Silicon Valley community interested in the evolution of the technology of Deep Neural Networks, also called Deep Learning.
SVDLG was founded in the spirit of organizations such as the Homebrew Computer Club of the 70s and 80s. We would like to facilitate the sharing of information between scientists developing the technology, engineer practitioners, investors, founders, entrepreneurs, the media, and other interested parties. Working together everyone can find a way to succeed and take part in what we believe is the next great revolution in computer technology.
You are welcome to come join us. Please take the time to sign up on meetup.com as seating can be limited. We are excited to meet you and to learn from what you have to contribute to the SVDLG community. We are also on Facebook and Twitterand we are looking forward to having you join us, even if you live and work outside Silicon Valley.Join Us on the Meetup
- Date: 19 Mar, 2018Topic:How to become a Full-Stack Deep Learning EngineerSpeaker:Forrest Iandola (CEO, DeepScale)Abstract:
Historically, AI has been an algorithm-centric field. However, with the rise of Deep Neural Networks (DNNs), it is now the case that (1) large-scale data, (2) novel DNN models, and (3) efficient software and hardware infrastructure, are all key to success. The best outcomes often come from teams who understand the "full stack" from low-level hardware for DNNs to high-level applications of DNNs. Full-stack DNN teams are able to make big-picture tradeoffs in the development of data, models, and infrastructure, leading to practical solutions that exhibit unprecedented levels of accuracy, speed, energy-efficiency.
In this talk, Forrest Iandola will focus on three main topics. First, he will inclusively define the "full stack" of skills and technologies that go into DNN engineering. Second, he will describe a playbook for managers who want to build, coach, and grow a full-stack DNN engineering team. This playbook draws on lessons that Forrest have learned first-hand at UC Berkeley, Microsoft Research, and DeepScale. Finally, he will provide advice on how a generalist or specialist engineer can engage with a full-stack DNN engineering team, and describe a path for how to ultimately become a full-stack DNN engineer.
Forrest Iandola completed a PhD in Electrical Engineering and Computer Science at UC Berkeley, where his research focused on deep neural networks. His advances in scalable training and efficient implementation of deep neural networks led to the founding of DeepScale, where he is CEO. DeepScale is focused entirely on building perception systems for automated vehicles, and DeepScale has a number of engagements with automakers and automotive suppliers.
We record the videos of talks given to our Silicon Valley Deep Learning Group. Enjoy watching the past talks on our Youtube chanel if you are not in the Bay Area or if you are, but missed a few talks.Our Youtube chanel
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