AI Vision
AI Vision is a By the Bay technology conference.
Talks & recordings
11 connected sessions
AI VC Panel
The AI VC panel consists of experienced VCs investing in AI startups. They will distill, essentially, what works -- in the tech, in industry, in the marketplace.
Advances in Deep Learning for Mathematic...
We'll explore how Deep Learning can be used for proving mathematical theorems, and its wide-reaching implications.
Bots Panel
The Bots panel will tackle all the AI issues stemming from the rise of the intelligent bots.
Computer Vision for Coders
Nowadays computer vision is synonymous with deep learning - and deep learning is widely viewed as an exclusive world for a handful of genius PhD graduates. But need this really be the case? In this talk, Jeremy Howard will discuss his experiences in teaching cutting edge deep learning (with a focus on computer vision) to 100 coders with no specialist math background. He will provide concrete recommendations for those looking to enter the deep learning world, but aren't sure where to start.
Machine Learning Startups
Bradford reviews all 4 of the Machine Learning startups he started since 2008 and distills some themes for the future. It's technical but is pretty high level.
Measuring AI Capabilities with OpenAI Gy...
OpenAI recently launched Universe, a platform for evaluating and training intelligent agents across the world's supply of games, websites and other applications. In this talk, we explore Universe, and the types of questions that it allows us to answer.
Measuring Psychological Traits using Soc...
The words and impages people post on social media such as Twitter and Facebook provide a rich, if imperfect view of who they are and what they care about. We show how to analyze social media to predict people's age, gender, personality, and mental health. Such methods are increasingly used for applications ranging from job candidate screening to targeted marketing.
Rooftop Party Overlooking the Bay: Food,...
“Rooftop Party Overlooking the Bay: Food,...” is a recorded developer talk from By the Bay, preserved in the devreal community archive.
Tackling the Limits of Deep Learning
Deep learning has made great progress in a variety of language tasks. However, there are still many practical and theoretical problems and limitations. In this talk I will introduce solutions to some of these: How to predict previously unseen words at test time. How to have a single input and output encoding for words. How to grow a single model for many tasks. How to use a single end-to-end trainable architecture for question answering.
The Future of (Artificial) Intelligence
The news media in recent months have been full of dire warnings about the risk that AI poses to the human race, coming from well-known figures such as Stephen Hawking, Frank Wilczek, and Elon Musk. Should we be concerned? If so, what can we do about it? While some in the mainstream AI community dismiss these concerns, I will argue instead that a fundamental reorientation of the field is required.
The Real Future of AI Panel
Our conference is built by the full-stack AI people -- those who can both build it and define its future. Hear what it will be like, when built.
Connections
11 relationships