The journey to the data-driven enterprise from the edge to AI
Amy O'Connor explains how Cloudera applies an "edge to AI" approach to collect, process, and analyze data.
Data
Our take on the ideas, information, and tools that make data work.
Algorithms are shaping our lives—here’s how we wrest back control
The O’Reilly Data Show Podcast: Kartik Hosanagar on the growing power and sophistication of algorithms.
Why your attention is like a piece of contested territory
The O’Reilly Data Show Podcast: P.W. Singer on how social media has changed, war, politics, and business.
The technical, societal, and cultural challenges that come with the rise of fake media
The O’Reilly Data Show Podcast: Siwei Lyu on machine learning for digital media forensics and image synthesis.
Artificial intelligence and machine learning adoption in European enterprise
How companies in Europe are preparing for and adopting AI and ML technologies.
Using machine learning and analytics to attract and retain employees
The O’Reilly Data Show Podcast: Maryam Jahanshahi on building tools to help improve efficiency and fairness in how companies recruit.
How companies are building sustainable AI and ML initiatives
A recent survey investigated how companies are approaching their AI and ML practices, and measured the sophistication of their efforts.
Rethinking informed consent
Consent is the first step toward the ethical use of data, but it's not the last.
How machine learning impacts information security
The O’Reilly Data Show Podcast: Andrew Burt on the need to modernize data protection tools and strategies.
7 data trends on our radar
From infrastructure to tools to training, Ben Lorica looks at what’s ahead for data.
In the age of AI, fundamental value resides in data
The O’Reilly Data Show Podcast: Haoyuan Li on accelerating analytic workloads, and innovation in data and AI in China.
Trends in data, machine learning, and AI
The O’Reilly Data Show Podcast: Ben Lorica looks ahead at what we can expect in 2019 in the big data landscape.
Tools for generating deep neural networks with efficient network architectures
The O’Reilly Data Show Podcast: Alex Wong on building human-in-the-loop automation solutions for enterprise machine learning.
Building tools for enterprise data science
The O’Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science.
Managing risk in machine learning
Considerations for a world where ML models are becoming mission critical.
Lessons learned while helping enterprises adopt machine learning
The O’Reilly Data Show Podcast: Francesca Lazzeri and Jaya Mathew on digital transformation, culture and organization, and the team data science process.
Machine learning on encrypted data
The O’Reilly Data Show Podcast: Alon Kaufman on the interplay between machine learning, encryption, and security.
How social science research can inform the design of AI systems
The O’Reilly Data Show Podcast: Jacob Ward on the interplay between psychology, decision-making, and AI systems.
Why it’s hard to design fair machine learning models
The O’Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness.
Sound design and the future of experience
Amber Case covers methods product designers and managers can use to improve interactions through an understanding of sound design.
Practical ML today and tomorrow
Hilary Mason explores the current state of AI and ML and what’s coming next in applied ML.
Quantifying forgiveness
Julia Angwin discusses what she's learned about forgiveness from her series of articles on algorithmic accountability and the lessons we all need to learn for the coming AI future.
Brain-based human-machine interfaces
Amanda Pustilnik highlights potential applications of data from new technologies that capture brain-based processes.
Black box: How AI will amplify the best and worst of humanity
Jacob Ward reveals the relationship between the unconscious habits of our minds and the way that AI is poised to amplify them, alter them, maybe even reprogram them.