InfoQ Homepage Robotics Content on InfoQ
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InfoQ AI, ML and Data Engineering Trends Report 2022
There have been a lot of innovations and developments in the AI and ML space since last year. In this podcast, InfoQ’s AI, ML, and Data Engineering editorial team discusses the latest trends that our readers should find interesting to learn about and apply in their own organizations when these trends become mainstream technologies.
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AI, ML and Data Engineering InfoQ Trends Report
How AI, ML and Data Engineering evolved in 2021 as seen by the InfoQ editorial team. Topics discussed include deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML.
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Joe, Florian and Sebastian on the Indy Autonomous Challenge
The Technical University of Munich has won the Indy Autonomous Challenge. A competition for self-racing vehicles. In this we discussies the the event itself, what makes it challenging, and the approach the TU Munich took. We discuss the importance of simulation, the limits of hardware, how Docker helps crossing this gap, and the role of open source software when taking on such a challenge.
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AI, ML and Data Engineering InfoQ Trends Report - August 2021
How AI, ML and Data Engineering are evolving in 2021 as seen by the InfoQ editorial team. Topics discussed include deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML.