This post is a tour around the PyTorch codebase, it is meant to be a guide for the architectural design of PyTorch and its internals. My main goal is to provide something useful for those who are interested in understanding what happens beyond the user-facing API and show something new beyond what was already covered in other tutorials.
Source: christianperone.com
A report from Gizmodo says that Google is partnering with the United States Department of Defense and building drone software. The project will reportedly apply Google’s usual machine learning prowess to identify objects in drone footage. Google’s involvement in the project wasn’t public, but it was apparently discussed internally at Google last week and leaked.
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Simulink provides a great training environment for DRL as it allows 3rd parties like Bonsai to integrate and control simulation models from the outside. This ability is one of the basic requirements for simulation platforms to be feasible for Deep Reinforcement Learning using Bonsai AI. More requirements can be found here.
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Interpretability techniques are normally studied in isolation. We explore the powerful interfaces that arise when you combine them — and the rich structure of this combinatorial space.
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