Creating autonomous vehicle systems
Understanding AV technologies and how to integrate them.
AI & ML
Few technologies have the potential to change the nature of work and how we live as artificial intelligence (AI) and machine learning (ML).
The technology behind self-driving vehicles
The O’Reilly Data Show Podcast: Shaoshan Liu on perception, knowledge, reasoning, and planning for autonomous cars.
Real AI products arrive
The O’Reilly Bots Podcast: Hilary Mason, Jimi Smoot, and Roger Chen on what AI means now.
Highlights from Strata + Hadoop World in New York 2016
Watch highlights covering data science, big data, data in the enterprise, and more. From Strata + Hadoop World in New York 2016.
Inbox is the Trojan horse of AI
Alistair Croll looks at the sometimes surprising ways that machine learning is insinuating itself into our every day lives.
From big data to human-level artificial intelligence
What explains the gap between what machines do well and what people do well? And what needs to happen before machines can match the flexibility and power of human cognition?
Lili Cheng on bot personalities
The O’Reilly Bots Podcast: Group interaction through social computing.
Highlights from the O’Reilly AI Conference in New York 2016
Watch highlights covering artificial intelligence, machine learning, intelligence engineering, and more. From the O'Reilly AI Conference in New York 2016.
Obstacles to progress in AI
Significant progress in AI will require breakthroughs in unsupervised/predictive learning, as well as in reasoning, attention, and episodic memory.
Minds and brains, and the route to smarter machines
Gary Marcus discusses the machine-human connection.
Lessons on building data products at Google
Aparna Chennapragada discusses Google's process for developing data products.
Deep learning at scale and use cases
Naveen Rao outlines deep learning challenges and explores how changes to the organization of computation and communication can lead to advances in capabilities.
Why AI needs emotion
Rana El Kaliouby explores why emotion in AI is critical to accelerating adoption of AI systems.
Why we’ll never run out of jobs
Tim O’Reilly explains why we can’t just use technology to replace people; we must use it to augment them so they can do things that were previously impossible.
Software engineering of systems that learn in uncertain domains
Building reliable, robust software is hard. It is even harder when we move from deterministic domains, such as balancing a checkbook, to uncertain domains, such as recognizing speech or objects in an image.
Humanizing AI development: Lessons from China and Xiaoice at Microsoft
Lili Cheng discusses the human aspects of artificial intelligence.
How AI is propelling driverless cars, the future of surface transport
Shahin Farshchi examines role artificial intelligence will play in driverless cars.
Artificial intelligence: Making a human connection
Genevieve Bell explores the meaning of “intelligence” within the context of machines and its cultural impact on humans and their relationships.
Data architectures for streaming applications
The O’Reilly Data Show Podcast: Dean Wampler on streaming data applications, Scala and Spark, and cloud computing.
Andy Mauro on bot platforms and tools
The O’Reilly Bots Podcast: A look at some of the technologies behind the chatbot boom.
Data science for humans and data science for machines
The O’Reilly Data Show Podcast: Michael Li on the state of data engineering and data science training programs.
Joshua Browder on bots that fight bureaucracy
The O’Reilly Bots Podcast: Can bots replace lawyers?
Artificial intelligence and the future of design
How algorithms will optimize everything.
Cathy Pearl on voice user interfaces for bots
The O’Reilly Bots Podcast: Applying the principles of normal human interaction to chatbots.