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.
Few technologies have the potential to change the nature of work and how we live as artificial intelligence (AI) and machine learning (ML).
Olga Russakovsky explains how her organization, AI4ALL, aims to increase diversity and inclusion in AI development and research.
Meihong Wang explains how Facebook thinks about personalization and how the company uses machine learning to provide personalized experiences.
Thomas Reardon offers an overview of brain-machine interface (BMI) technology and shares CTRL-Labs’s transformative and noninvasive neural interface approach.
George Church discusses the IARPA MICrONS project, which aims to revolutionize machine learning by reverse-engineering the algorithms of the brain.
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.
Fiaz Mohamed explains how Intel AI solves today’s business problems.
Kavya Kopparapu shares her inspiration for starting GirlsComputingLeague.
Zoubin Ghahramani discusses recent advances in artificial intelligence, highlighting research in deep learning, probabilistic programming, Bayesian optimization, and AI for data science.
Watch highlights covering artificial intelligence, machine learning, automation, and more. From the Artificial Intelligence Conference in New York 2018.
Fiaz Mohammed and Justin Herz discuss how artificial intelligence can improve content discovery and monetization
Ben Lorica and Roger Chen discuss the state of reinforcement learning and automation.
Manuela Veloso looks at the role humans can play in autonomy-based AI interactions and the underlying challenges to AI.
The O’Reilly Data Show Podcast: Jerry Overton on organizing data teams, agile experimentation, and the importance of ethics in data science.
The O’Reilly Data Show Podcast: Guillaume Chaslot on bias and extremism in content recommendations.
The two positions are not interchangeable—and misperceptions of their roles can hurt teams and compromise productivity.
Our survey reveals how organizations are using tools, techniques, and training to apply AI through deep learning.
The O’Reilly Data Show Podcast: Jesse Anderson and Paco Nathan on organizing data teams and next-generation messaging with Apache Pulsar.
The O’Reilly Data Show Podcast: Ameet Talwalkar on large-scale machine learning.
Using silly data sets as examples, Janelle Shane talks about ways that algorithms fail.
Ben Lorica explores emerging security best practices for business intelligence, machine learning, and mobile computing products.
Watch highlights covering machine learning, business intelligence, data privacy, and more. From the Strata Data Conference in San Jose 2018.
Li Fan shows how Pinterest is using AI to predict what’s in an image, what a user wants, and what they’ll want next.
The O’Reilly Data Show Podcast: Ofer Ronen on the current state of chatbots.
The O’Reilly Data Show Podcast: Danny Lange on how reinforcement learning can accelerate software development and how it can be democratized.