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Revolutionizing the landscape of artificial intelligence (AI) and data analytics, Alluxio introduced Alluxio Enterprise AI. Designed to meet the rising demands of AI and machine learning workloads on an enterprise’s data infrastructure, the new high-performance data platform will help enterprises accelerate AI products’ time-to-value and maximize infrastructure ROI.

Alluxio, a company tracing its roots to 2014 open source project Tachyon at UC Berkeley’s AMPLab, has launched its Alluxio Enterprise AI (AEAI) platform, geared specifically to deep learning and generative AI applications. The new platform runs atop the established Alluxio Data Platform, adding optimizations for GPU resources and specific machine learning (ML) and deep learning libraries.

According to a new press release, Alluxio has unveiled a new high-performance data platform called Alluxio Enterprise AI, aimed at meeting the increasing demands of artificial intelligence (AI) and machine learning (ML) workloads within enterprise data infrastructure. This platform addresses challenges associated with AI infrastructure, such as low performance, data accessibility, GPU scarcity, and underutilized resources. Alluxio Enterprise AI offers significant speed improvements, achieving up to 20 times faster model training and up to 10 times accelerated model serving while utilizing GPUs efficiently.

Alluxio作为一家承载各类数据驱动型工作负载的数据平台公司，现推出全新的Alluxio Enterprise AI高性能数据平台, 旨在满足人工智能 (AI) 和机器学习 (ML) 负载对于企业数据基础设施不断增长的需求。 Alluxio Enterprise AI 平台可综合优化企业AI和分析基础设施的性能、数据可访问性、可扩展性和成本效益，助力生成式AI、计算机视觉、自然语言处理、大语言模型和高性能数据分析等下一代数据密集型应用的发展。

Alluxio 作为一家承载各类数据驱动型工作负载的数据平台公司，现推出全新的 Alluxio Enterprise AI 高性能数据平台, 旨在满足人工智能 (AI) 和机器学习 (ML) 负载对于企业数据基础设施不断增长的需求。 Alluxio Enterprise AI 平台可综合优化企业 AI 和分析基础设施的性能、数据可访问性、可扩展性和成本效益，助力生成式 AI、计算机视觉、自然语言处理、大语言模型和高性能数据分析等下一代数据密集型应用的发展。

Alluxio, the data platform company for all data-driven workloads, today introduced Alluxio Enterprise AI, a new high-performance data platform designed to meet the rising demands of Artificial Intelligence (AI) and machine learning (ML) workloads on an enterprise’s data infrastructure. Alluxio Enterprise AI brings together performance, data accessibility, scalability and cost-efficiency to enterprise AI and analytics infrastructure to fuel next-generation data-intensive applications like generative AI, computer vision, natural language processing, large language models and high-performance data analytics.

Alluxio, the data platform company for all data-driven workloads, has introduced a new high-performance data platform designed to meet the rising demands of AI/ML workloads on an enterprise’s data infrastructure. Alluxio Enterprise AI brings together performance, data accessibility, scalability and cost-efficiency to enterprise AI and analytics infrastructure to fuel next-generation data-intensive applications like generative AI, computer vision, natural language processing, large language models and high-performance data analytics.

Alluxio introduced Alluxio Enterprise AI, a high-performance data platform for making data available to AI. Alluxio has developed open source data store virtualization software, a virtual distributed file system with multi-tier caching. Alluxio Enterprise AI is a new product that builds on the previous Alluxio Enterprise Editions with a new architecture optimized for AI/ML workloads. It has has a distributed system architecture with decentralized metadata to eliminate bottlenecks when accessing massive numbers of small files, typical of AI workloads.

Alluxio, the data platform company for data-driven workloads, is unveiling Alluxio Enterprise AI, a high-performance data platform designed to unify performance, data accessibility, scalability, and cost efficiency in powering AI and machine learning (ML) workloads. Supporting a variety of use cases—from generative AI (GenAI) to computer vision, natural language processing (NLP), large language models (LLMs), high-performance data analytics, and more—Alluxio Enterprise AI reinvigorates enterprise infrastructure to handle the rising needs of AI and ML.