Search Results for "ray"
Anyscale Enhances Ray Data with Joins and Hash-Shuffle for Improved Performance
Anyscale introduces a hash-based shuffle backend in Ray Data, enhancing joins and performance for repartitioning and aggregations. Discover the advancements in the Ray 2.46 release.
Anyscale Launches Ray Train and Ray Data Dashboards for Enhanced Observability
Anyscale introduces Ray Train and Ray Data Dashboards, offering new features for improved observability and performance optimization in distributed AI model training and data pipelines.
RayTurbo Data Enhancements Boost Processing Speed by Fivefold
Anyscale's RayTurbo Data introduces significant improvements, offering up to 5x faster data processing. Key features include job-level checkpointing, vectorized aggregations, and optimized pipeline rules.
Enhancing RAG Pipelines with Ray and Anyscale for Scalable AI Solutions
Explore how Ray and Anyscale empower developers to build scalable Retrieval-Augmented Generation (RAG) pipelines, reducing hallucinations and integrating new information without retraining models.
Exploring the Open Source AI Compute Tech Stack: Kubernetes, Ray, PyTorch, and vLLM
Discover the components of a modern open-source AI compute tech stack, including Kubernetes, Ray, PyTorch, and vLLM, as utilized by leading companies like Pinterest, Uber, and Roblox.
Ray and the Evolution of AI Compute Frameworks
Explore how Ray addresses compute bottlenecks in AI frameworks, as unstructured data and GPU demands challenge legacy systems, according to Anyscale.
Tencent's Weixin Integrates Ray for Large-Scale AI Deployment
Tencent's Weixin team has embraced Ray and Kubernetes to enhance their AI infrastructure, tackling challenges in resource utilization and deployment complexity.
NVIDIA Unveils DLSS 4 and Ray Tracing Advancements at Gamescom 2025
NVIDIA announces DLSS 4 support for over 175 games and introduces new ray tracing capabilities at Gamescom 2025, enhancing gaming experiences with AI-powered technologies.
Enhancing Text-to-SQL Models Using Tinker and Ray
Discover how Tinker and Ray are utilized to fine-tune text-to-SQL models, enhancing AI capabilities in generating efficient SQL queries.
Enhancing Ray Clusters with NVIDIA KAI Scheduler for Optimized Workload Management
NVIDIA's KAI Scheduler integrates with KubeRay, enabling advanced scheduling features for Ray clusters, optimizing resource allocation and workload prioritization.
Ray Enhances Scheduling with New Label Selectors
Ray introduces label selectors, enhancing scheduling capabilities for developers, allowing more precise workload placement on nodes. The feature is a collaboration with Google Kubernetes Engine.
Anyscale Showcases AI Innovations at AWS re:Invent 2025
Anyscale highlights AI solutions with Ray at AWS re:Invent 2025, featuring demos, talks, and executive events for enhanced machine learning operations.