According to @gensynai, RL Swarm has integrated with Weights & Biases, enabling direct terminal log uploads and real-time monitoring of key training metrics such as loss, learning rate, rewards, and GPU utilization (source: https://twitter.com/gensynai/status/1927789712938602649). This upgrade streamlines AI model optimization for algorithmic trading, giving crypto traders faster feedback loops and improved transparency for developing high-frequency trading bots.

According to gensyn (@gensynai), RL Swarm has expanded its decentralized network by adding Metal support, enabling Mac users with Apple silicon (M2, M3, M4) to train AI models significantly faster (source: @gensynai, May 28, 2025). This upgrade increases the network's computational capacity, potentially making decentralized AI training more efficient and accessible. For crypto traders, this enhancement may boost interest in RL Swarm-related tokens and decentralized AI infrastructure projects, as faster training could drive adoption and ecosystem growth.