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The O’Reilly Data Show Podcast: Jacob Ward on the interplay between psychology, decision-making, and AI systems.
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Amy Heineike explains how Primer created a self-updating knowledge base that can track factual claims in unstructured text.
Yangqing Jia talks about what makes AI software unique and its connections to conventional computer science wisdom.
Jonathan Ballon explains why Intel’s AI and computer vision edge technology will drive advances in machine learning and natural language processing.
Ben Lorica and Roger Chen highlight recent trends in data, compute, and machine learning.
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Ashok Srivastava draws upon his cross-industry experience to paint an encouraging picture of how AI can solve big problems.
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Michael Bernstein offers an unflinching look at some of the fallacies that developers believe about marketing.
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Kavya Joshi says performance theory offers a rigorous and practical approach to performance tuning and capacity planning.
Dave Rensin explains why DevOps and SRE make each other better.
Kris Beevers examines the trade-offs between risk and velocity faced by any high-growth, critical path technology business.
Anil Dash asks: How could our processes and tools be designed to undo the biggest bugs and biases of today’s tech?
Laurent Gil shares the latest cybersecurity research findings based on real-world security operations.
Francesc Campoy Flores explores ways machine learning can help developers be more efficient.
Jessica McKellar draws parallels between the free and open source software movement and the work to end mass incarceration.
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The O’Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness.
The World Economic Forum’s 2018 jobs report limits research to a narrow range of the workforce.
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Chad Jennings explains how Geotab's smart city application helps city planners understand traffic and predict locations of unsafe driving.
Ziya Ma discusses how recent innovations from Intel in high-capacity persistent memory and open source software are accelerating production-scale deployments.
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We should invest at least as much time in understanding our customers as we do in optimizing our product development process.
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