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Anyscale launches Replica Compaction to address resource fragmentation, enhancing resource utilization and reducing costs for Ray Serve deployments. (Read More)
Anyscale unveils multi-tenant serve applications using runtime environments as containers, enhancing efficiency and reducing operational complexity. (Read More)
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. (Read More)
Anyscale introduces enhanced AI compute solutions with support for Azure Kubernetes Service, Global Resource Scheduler, and upcoming multi-deployment management, optimizing resource utilization and scaling across cloud platforms. (Read More)
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. (Read More)
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. (Read More)
Google Cloud and Anyscale have partnered to integrate RayTurbo with Google Kubernetes Engine, enhancing AI application development and scaling. This collaboration aims to simplify and optimize AI workloads. (Read More)
Anyscale launches new training options for Ray, including free eLearning and instructor-led courses, catering to AI/ML engineers seeking to scale AI applications effectively. (Read More)
Anyscale introduces the deployment of DeepSeek R1, offering enhanced control, scalability, and transparency for AI models across various infrastructures without vendor constraints. (Read More)
Anyscale has been named a 2024 Cool Vendor in AI Engineering by Gartner, highlighting its role as a leading AI platform overcoming AI complexity challenges. (Read More)
Anyscale partners with Astronomer to streamline machine learning workflows using Apache Airflow and Ray, enhancing scalability and efficiency for data teams. (Read More)
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