InfoQ Homepage Presentations
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Reinventing Credit Insurance with APIs
Christophe Spoerry discusses embedding insurance in B2B innovations.
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Elm and Phoenix: Two FP Flavors That Taste Great Together
Josh Adams discusses the basics of creating apps in Elm with a Phoenix back-end, using real-world examples of how the two work together in Firestorm, an open-source forum engine.
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Serverless Platform: Scientific Computation @Scale
Diptanu Choudhury talks about the platform they are developing at NASA for running computations as functions which would make it easier for researchers to program their applications & algorithms.
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What Does Speed Mean in Software Product Delivery?
Jason Yip explores the way of thinking about "high velocity" and gives specific examples of concepts and practices to try from his experiences at ThoughtWorks and Spotify.
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More Reliable Delivery with Monte Carlo & Mapping
Conal Scanlon talks about how to use Monte Carlo simulations to remove the guesswork from planning, story mapping to discover the story up front, and reviews an example of how to automate a forecast.
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Development Metrics You Should Use But Don't
Cat Swetel discusses new ways and tools to visualize a team’s reliability and variability of delivery using the data already collected.
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Stop Managing Tech People! Empower Them to Build What You Need
Benjamin Brial suggests reorganizing a company by trusting employees, letting them work on something they enjoy, and sharing the benefits with them.
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How to Survive the API Copyright Apocalypse
Steven Willmott recommends avoiding the possible API copyright troubles by sharing API definitions rather than copyrighting them.
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Avoiding React Performance Pitfalls
Alex Grigoryan discusses the performance problems found and their solutions moving from Backbone/Java to React/Node.js at @WalmartLabs.
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IoT for Big Machines
Jayant Thomas discusses Predix, GE’s IoT Cloud, and how one can use anomaly detection on an IoT cloud and scale it up for multiple industrial assets to provide insights about the big machines.
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When Models Go Rogue: Hard Earned Lessons on Using Machine Learning in Production
David Talby summarizes best practices & lessons learned in ML, based on nearly a decade of experience building & operating ML systems at Fortune 500 companies across several industries.
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What Makes an Agile Manager?
Roisi Proven discusses what an agile project looks like to different people, what common misconceptions are attached to some of these titles, and all the ways in which they intersect.
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