Tag: Reinforcement Learning
Ray 1.9 makes Train beta, launches Ray Job Submission server
The team behind the Ray framework for building distributed applications has pushed version 1.9 of its project into […]
Break point: Epsagon, Artifact Hub, Tesseract, Cloudera, OpenSpiel, Keda, and GitHub
Cisco has announced plans to acquire distributed tracing company Epsagon, in a bid to accelerate its comprehensive observability […]
What’s the point: Google AI advances, Git security updates, and API gateway Gloo
Google’s AI teams used the comparatively quiet post-easter days to get ML practitioners up to speed with their […]
Google AI plants SEED for better scalable reinforcement learning
Google AI researchers have looked into ways of making reinforcement learning scale better and improve computational efficiency. The […]
DeepMind says RLax..or try Haiku(s)
Artificial intelligence company DeepMind has open-sourced new libraries for neural networks and reinforcement learning, making the most of […]
Huskarl aims at becoming the TensorFlow for Reinforcement Learning
TensorFlow users interested in Reinforcement Learning (better known as the thing that made AlphaGo win at Go) might […]
Reinforcement Learning framework Dopamine opens up to new environments
Dopamine, a framework for experimenting with reinforcement learning (RL), has reached the 2.0 mark, now allowing the use […]