Building a natural language processing library for Apache Spark
The O’Reilly Data Show Podcast: David Talby on a new NLP library for Spark, and why model development starts after a model gets deployed to production.
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).
Machine intelligence for content distribution, logistics, smarter cities, and more
The O’Reilly Data Show Podcast: Rhea Liu on technology trends in China.
How companies can navigate the age of machine learning
To become a “machine learning company,” you need tools and processes to overcome challenges in data, engineering, and models.
Planning for AI
What you need know before committing to AI.
Vehicle-to-vehicle communication networks can help fuel smart cities
The O’Reilly Data Show Podcast: Bruno Fernandez-Ruiz on the importance of building the ground control center of the future.
How IoT and machine learning keep America truckin’
Terry Kline and Mike Olson look at how machine learning and predictive analytics keep more than 300,000+ connected vehicles rolling
The real project of AI ethics
Joanna Bryson says AI's main threat is not that it will do anything to us, but that we'll use it to predict and manipulate our behaviors.
Human-AI interaction: Autonomous service robots
Manuela Veloso provides an overview of the CoBot mobile service robots and their symbiotic autonomy, which lets the robots ask for help to overcome their limitations.
WTF? What’s the future and why it’s up to us
Tim O'Reilly says entrepreneurs need to set their sights on how we can use big data, sensors, and AI to create amazing human experiences and the economy of the future.
Transforming organizations through analytics centers of excellence
The O’Reilly Data Show Podcast: Carme Artigas on helping enterprises transform themselves with big data tools and technologies.
The age of machine learning
Ben Lorica discusses the state of machine learning.
Highlights from Strata Data Conference in New York 2017
Watch highlights covering data science, data engineering, data-driven business, and more. From Strata Data Conference in New York 2017.
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.
Accelerating AI
Steve Jurvetson examines the state of artificial intelligence.
Fireside chat with Naveen Rao and Steve Jurvetson
A discussion on the impact and opportunities of artificial intelligence.
Our Skynet moment
Tim O'Reilly says the algorithms that shape our economy must be rewritten if we want to create a more human-centered future.
The inevitable merger of IQ and EQ in technology
Rana el Kaliouby lays out a vision for an emotion-enabled world of technology.
The state of AI adoption
AI Conference chairs Ben Lorica and Roger Chen reveal the current AI trends they've observed in industry.
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.
AI is the new electricity
Andrew Ng shares his thoughts on where the biggest opportunities in AI may lie.
Highlights from the Artificial Intelligence Conference in San Francisco 2017
Watch highlights covering artificial intelligence, machine learning, applied deep learning, and more. From the Artificial Intelligence Conference in San Francisco 2017.
Visualizing convolutional neural networks
Building convnets from scratch with TensorFlow and TensorBoard.
Visualizing convolutional neural networks
Building convnets from scratch with TensorFlow and TensorBoard.