New York City skyline - AI NY 2018
New York City skyline - AI NY 2018

Experts from across the AI world came together in New York for the Artificial Intelligence Conference. Below you'll find links to highlights from the event.

Hybrid bio-opto-electronics for AI

George Church discusses the IARPA MICrONS project, which aims to revolutionize machine learning by reverse-engineering the algorithms of the brain.

The frontiers of machine learning and AI

Zoubin Ghahramani discusses recent advances in artificial intelligence, highlighting research in deep learning, probabilistic programming, Bayesian optimization, and AI for data science.

Understanding automation

Ben Lorica and Roger Chen discuss the state of deep learning, reinforcement learning, and automation.

Neural interfaces: Connecting humans and artificial intelligence

Thomas Reardon offers an overview of brain-machine interface (BMI) technology and shares CTRL-Labs’s transformative and noninvasive neural interface approach.

Increasing business results through AI in the entertainment industry

Fiaz Mohammed and Justin Herz discuss how artificial intelligence can improve content discovery and monetization

Bringing AI into the wild

Mary Beth Ainsworth offers an overview of SAS deep learning and computer vision capabilities that help map wildlife and scale conservation efforts around the world.

Autonomy and human-AI interaction

Manuela Veloso looks at the role humans can play in autonomy-based AI interactions and the underlying challenges to AI.

Using machine learning, the IoT, drones, and networking to reduce world hunger

Food production needs to double by 2050 to feed the world’s growing population. Jennifer Marsman details a solution that uses sensors in the soil, aerial imagery from drones, and machine learning.

Intel AI for the enterprise ecosystem

Fiaz Mohamed explains how Intel AI solves today’s business problems.

Fireside chat with Peter Norvig and Kavya Kopparapu

Kavya Kopparapu shares her inspiration for starting GirlsComputingLeague.

Rapid AI experimentation and innovation on Amazon Web Services

Dan Mbanga explores how accelerating AI experimentation has influenced innovations such as Amazon Alexa, Prime Air, and Go.

Using machine learning in workload automation

Abhijit Deshpande explains how to use machine learning to identify root causes of problems in minutes instead of hours.

AI4ALL: AI will change the world, but who will change AI?

Olga Russakovsky explains how her organization, AI4ALL, aims to increase diversity and inclusion in AI development and research.

The physics of AI

Dario Gil explores state-of-the-art computing for AI as it exists today as well as an innovation that will lead us into the decades to come: quantum computing for AI.

Serving billions of personalized news feeds with AI

Meihong Wang explains how Facebook thinks about personalization and how the company uses machine learning to provide personalized experiences.

WTT: What the tensor?

Ron Bodkin explains what a tensor is and why you should care.

Article image: New York City skyline - AI NY 2018