Experts from across the AI world came together for the Artificial Intelligence Conference in San Francisco. Below you’ll find links to highlights from the event.
Our Skynet moment
Tim neveropen says the algorithms that shape our economy must be rewritten if we want to create a more human-centered future.
Learn faster. Dig deeper. See farther.
- Watch “Our Skynet moment.”
The inevitable merger of IQ and EQ in technology
Rana el Kaliouby lays out a vision for an emotion-enabled world of technology.
AI is the new electricity
Andrew Ng shares his thoughts on where the biggest opportunities in AI may lie.
- Watch “AI is the new electricity.”
Engineering the future of AI for businesses
Ruchir Puri addresses the opportunities and challenges of AI for business and focuses on what’s needed to scale AI across the breadth of enterprises.
The state of AI adoption
AI Conference chairs Ben Lorica and Roger Chen reveal the current AI trends they’ve observed in industry.
- Watch “The state of AI adoption.”
Deep learning to fight cancer: Fireside chat with Peter Norvig and Abu Qader
Peter Norvig speaks with Abu Qader, the 18-year-old CTO of GliaLab who taught himself machine learning and launched an AI company for breast cancer diagnostics.
How to escape saddlepoints efficiently
Michael Jordan discusses recent results in gradient-based optimization for large-scale data analysis.
Why democratizing AI matters: Computing, data, algorithms, and talent
Jia Li explains why a democratized approach to AI ensures that the components behind these technologies reach the widest possible audience.
AI mimicking nature: Flying and talking
Lili Cheng shares two examples of AI that were inspired by nature.
Accelerating AI
Steve Jurvetson examines the state of artificial intelligence.
- Watch “Accelerating AI.”
Fireside chat with Naveen Rao and Steve Jurvetson
A discussion on the impact and opportunities of artificial intelligence.
Build smart applications with your new super power: Cloud AI
Philippe Poutonnet discusses how you can harness the power of machine learning, whether you have a machine learning team of your own or you just want to use machine learning as a service.
