InfoQ Homepage Keynote Content on InfoQ
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Artificial Pancreas System: #WeAreNotWaiting in Healthcare
Dana Lewis discusses open source innovation in unexpected places and how we can democratize data (and innovation processes) to enable more people to solve the most pressing problems in their lives.
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Ignite the Fire - How Managers Can Spark New Leaders
Nick Caldwell discusses the three ingredients for inspiring non-manager leaders to emerge and provides simple techniques any team member can apply.
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No Moore Left to Give: Enterprise Computing after Moore's Law
Bryan Cantrill talks about Moore's Law, which after years of defying predictions of its demise, is now dying. But what does the end of Moore's Law mean for practitioners of enterprise computing?
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Learning from Machines
Ashi Krishnan discusses biological and artificial minds, exploring how models of cognition informed by ML and computation can help reconfigure processes of being.
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How to Create a Data Science Product from Scratch?
Dmytro Bilash discusses the top five biggest challenges in creating a data science product, compares a product for one client and a scalable one for the whole market, and how to be successful.
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Quality Engineering in DevOps
Geoffrey van der Tas keynotes on testing in the DevOps world, covering practices to keep, habits to forget, new things to learn, and the need for manual testing.
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Privacy: The Last Stand for Fair Algorithms
Katharine Jarmul discusses research related to fair-and-private ML algorithms and privacy-preserving models, showing that caring about privacy can help ensure a better model overall and support ethics
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The Future of Transportation
Anita Sengupta discusses the future of transportation with an eye towards how machine learning and AI will help shape the future.
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Modern NLP for Pre-Modern Practitioners
Joel Grus discusses the latest in NLP research breakthrough, and how to incorporate NLP concepts and models into a project.
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Right to Left
Mike Burrows advocates for a Lean-Agile delivery process starting “from the right” with needs met by working software.
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Blunders in Test Automation
Dorothy Graham discusses several testing blunders, including: Testing-Tools-Test, Silver Bullet, Automating the Wrong Thing, Who Needs GPS, How Hard Can It Be, and the Stable-Application Myth.
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Data Science for Lazy People, Automated Machine Learning
Diego Hueltes discusses using Automated Machine Learning as a personal assistant in Data Science.
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