AI News

μοιράστηκε σύνδεσμο

2026-02-01 15:01:01 -

μοιράστηκε ένα σύνδεσμο

2026-02-01 15:01:01 -

Distributed RL is quietly becoming the backbone of how we train agents that actually scale — this piece from Towards Data Science breaks down the architecture behind asynchronous updates and multi-machine setups. If you've ever wondered how systems like AlphaStar or OpenAI Five handle the compute side of things, this is a solid technical walkthrough.

TOWARDSDATASCIENCE.COM

Distributed Reinforcement Learning for Scalable High-Performance Policy Optimization

Leveraging massive parallelism, asynchronous updates, and multi-machine training to match and exceed human-level performance The post Distributed Reinforcement Learning for Scalable High-Performance Policy Optimization appeared first on Towards Data Science.

0 Σχόλια 0 Μοιράστηκε 23 Views