Highlights from the Artificial Intelligence Conference in London 2018
Watch highlights from expert talks covering artificial intelligence, machine learning, automation, and more.
People from across the AI world came together in London for the Artificial Intelligence Conference. Below you’ll find links to highlights from the event.
The state of automation technologies
Ben Lorica and Roger Chen highlight recent trends in data, compute, and machine learning.
- Watch “The state of automation technologies.”
AI in production: The droids you’re looking for
Jonathan Ballon explains why Intel’s AI and computer vision edge technology will drive advances in machine learning and natural language processing.
AI and machine learning at Amazon
Ian Massingham discusses the application of ML and AI within Amazon, from retail product recommendations to the latest in natural language understanding.
- Watch “AI and machine learning at Amazon.”
Why we built a self-writing Wikipedia
Amy Heineike explains how Primer created a self-updating knowledge base that can track factual claims in unstructured text.
Trust and transparency of AI for the enterprise
Ruchir Puri explains why trust and transparency are essential to AI adoption.
AI for a better world
Ashok Srivastava draws upon his cross-industry experience to paint an encouraging picture of how AI can solve big problems.
- Watch “AI for a better world.”
Rethinking software engineering in the AI era
Yangqing Jia talks about what makes AI software unique and its connections to conventional computer science wisdom.
Bringing AI into the enterprise: A functional approach to the technologies of intelligence
Kristian Hammond maps out simple rules, useful metrics, and where AI should live in the org chart.
Fireside chat with Marc Warner and Louis Barson
Marc Warner and Louis Barson discuss the internal and external uses of AI in the UK government.
Building artificial people: Endless possibilities and the dark side
Supasorn Suwajanakorn discusses the possibilities and the dark side of building artificial people.
Deep learning at scale: A field manual
Jason Knight offers an overview of the state of the field for scaling training and inference across distributed systems.
The missing piece
Cassie Kozyrkov shares machine learning lessons learned at Google and explains what they mean for applied data science.
- Watch “The missing piece.”
Notes from the frontier: Making AI work
Drawing on the McKinsey Global Institute’s research, Michael Chui explores commonly asked questions about AI and its impact on work.