InfoQ Homepage Artificial Intelligence Content on InfoQ
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Panel: Sequential Data
The panelists discuss how the different fields within sequential data processing can benefit from each other, what the future trends are that we expect and take questions.
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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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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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Creating a Trusted Narrative for Data-Driven Technology
Indra Joshi talks about the hype and promise surrounding AI-based technology within health and care, and how to ensure that what gets developed or commissioned is ethically developed.
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DeepRacer and DeepLens, Machine Learning for Fun! (and Profit?)
Jeremy Edberg shares his work with DeepRacer and DeepLens, talking about some of the basics of ML used in these projects and showing a DeepRacer in action.
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Improving Developer Productivity with Visual Studio Intellisense
Allison Buchholtz-Au and Shengyu Fu discuss how PM, engineering, and data science came together to build Visual Studio IntelliCode, which delivers context-aware code completion suggestions.
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From Robot Simulation to the Real World
Louise Poubel overviews Gazebo's architecture with examples of projects using Gazebo, describing how to bridge virtual robots to their physical counterparts.
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The Road to Artificial Intelligence: An Ethical Minefield
Lloyd Danzig offers a look into the complex ethical issues faced by today's top engineers and poses open-ended questions for the consideration of attendees.
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The Evolution of Spotify Home Architecture
Emily Samuels and Anil Muppalla discuss the evolution of Spotify's architecture that serves recommendations (playlist, albums, etc) on the Home Tab.
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Scaling Emerging AI Applications with Ray
Peter Schafhalter discusses about his work with Ray, a distributed execution framework for emerging AI applications, Tune, and Modin.
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Practical NLP for the Real World
Emmanuel Ameisen discusses examples of how to build practical applications using NLP, diving into data visualization and labelling, as well as model validation.
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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.