Ray
KubeRay v1.7 Launches With Upgraded Features for Ray on Kubernetes
KubeRay v1.7 introduces major upgrades like History Server beta, enhanced RayJob management, and stronger security for Ray workloads on Kubernetes.
Anyscale Debuts GPU Health Observability for AI Workloads
Anyscale introduces GPU Health Observability, bridging hardware and ML workloads with real-time monitoring to reduce failures.
Ray 2.58 Unveils Native gVisor Sandboxing for Scalable AI Workloads
Ray 2.58 introduces native gVisor sandboxing, enabling scalable, isolated environments for reinforcement learning and agentic AI workloads.
NVIDIA GB300 NVL72 Enhances AI with Ray Placement Groups
NVIDIA GB300 NVL72 leverages Ray's NVLink Domain-Aware Placement Groups for optimized multi-node GPU scheduling, boosting AI performance.
Anyscale to Merge with Nscale, Boosting AI Infrastructure
Anyscale and Nscale unite to advance AI infrastructure, focusing on open-source Ray, GPU capacity, and multi-cloud flexibility.
Ray's Resource Isolation Enhances Cluster Stability with cgroup v2
Ray's new Resource Isolation feature leverages Linux's cgroup v2 to improve stability under heavy workloads, cutting node failures to zero.
FSDP and PyTorch Enable Large-Scale Model Training
Fully Sharded Data Parallel (FSDP) in PyTorch, integrated with Ray, optimizes GPU memory usage for scalable training of models like Qwen3-TTS with 1.7B parameters.
Adyen (ADYEN) Trains AI Model on 51 Trillion Tokens, Tackling Fraud
Adyen unveils its Transaction Foundation Model, trained on 51 trillion tokens, aiming to enhance fraud detection and payment optimization.
Anyscale Launches Debugging Skills to Streamline Ray and vLLM Fixes
Anyscale's new debugging tools simplify fixing Ray and vLLM workloads, saving hours of manual effort for developers.
Ray Day NYC Spotlights AI Scaling from Coinbase, Discord, Torc
Ray Day NYC featured Coinbase, Discord, and Torc Robotics sharing how Ray boosted AI workloads. Highlights include Torc's 90% GPU utilization.