Latest news with #LlamaStack
Mid East Info
22-05-2025
- Business
- Mid East Info
Red Hat Optimizes Red Hat AI to Speed Enterprise AI Deployments Across Models, AI Accelerators and Clouds - Middle East Business News and Information
Red Hat AI Inference Server, validated models and integration of Llama Stack and Model Context Protocol help users deliver higher-performing, more consistent AI applications and agents Red Hat, the world's leading provider of open source solutions, today continues to deliver customer choice in enterprise AI with the introduction of Red Hat AI Inference Server, Red Hat AI third-party validated models and the integration of Llama Stack and Model Context Protocol (MCP) APIs, along with significant updates across the Red Hat AI portfolio. With these developments, Red Hat intends to further advance the capabilities organizations need to accelerate AI adoption while providing greater customer choice and confidence in generative AI (gen AI) production deployments across the hybrid cloud. According to Forrester, open source software will be the spark for accelerating enterprise AI efforts.1 As the AI landscape grows more complex and dynamic, Red Hat AI Inference Server and third party validated models provide efficient model inference and a tested collection of AI models optimized for performance on the Red Hat AI platform. Coupled with the integration of new APIs for gen AI agent development, including Llama Stack and MCP, Red Hat is working to tackle deployment complexity, empowering IT leaders, data scientists and developers to accelerate AI initiatives with greater control and efficiency. Efficient inference across the hybrid cloud with Red Hat AI Inference Server: The Red Hat AI portfolio now includes the new Red Hat AI Inference Server, providing faster, more consistent and cost-effective inference at scale across hybrid cloud environments. This key addition is integrated into the latest releases of Red Hat OpenShift AI and Red Hat Enterprise Linux AI, and is also available as a standalone offering, enabling organizations to deploy intelligent applications with greater efficiency, flexibility and performance. Tested and optimized models with Red Hat AI third party validated models Red Hat AI third party validated models, available on Hugging Face, make it easier for enterprises to find the right models for their specific needs. Red Hat AI offers a collection of validated models, as well as deployment guidance to enhance customer confidence in model performance and outcome reproducibility. Select models are also optimized by Red Hat, leveraging model compression techniques to reduce size and increase inference speed, helping to minimize resource consumption and operating costs. Additionally, the ongoing model validation process helps Red Hat AI customers continue to stay at the forefront of optimized gen AI innovation. Standardized APIs for AI application and agent development with Llama Stack and MCP Red Hat AI is integrating Llama Stack, initially developed by Meta, along with Anthropic's MCP, to provide users with standardized APIs for building and deploying AI applications and agents. Currently available in developer preview in Red Hat AI, Llama Stack provides a unified API to access inference with vLLM, retrieval-augmented generation (RAG), model evaluation, guardrails and agents, across any gen AI model. MCP enables models to integrate with external tools by providing a standardized interface for connecting APIs, plugins and data sources in agent workflows. The latest release of Red Hat OpenShift AI (v2.20) delivers additional enhancements for building, training, deploying and monitoring both gen AI and predictive AI models at scale. These include: Optimized model catalog (technology preview) provides easy access to validated Red Hat and third party models, enables the deployment of these models on Red Hat OpenShift AI clusters through the web console interface and manages the lifecycle of those models leveraging Red Hat OpenShift AI's integrated registry. Distributed training through the KubeFlow Training Operator enables the scheduling and execution of InstructLab model tuning and other PyTorch-based training and tuning workloads, distributed across multiple Red Hat OpenShift nodes and GPUs and includes distributed RDMA networking–acceleration and optimized GPU utilization to reduce costs. Feature store (technology preview), based on the upstream Kubeflow Feast project, provides a centralized repository for managing and serving data for both model training and inference, streamlining data workflows to improve model accuracy and reusability. Red Hat Enterprise Linux AI 1.5 brings new updates to Red Hat's foundation model platform for developing, testing and running large language models (LLMs). Key features in version 1.5 include: Google Cloud Marketplace availability, expanding the customer choice for running Red Hat Enterprise Linux AI in public cloud environments–along with AWS and Azure–to help simplify the deployment and management of AI workloads on Google Cloud. Enhanced multi-language capabilities for Spanish, German, French and Italian via InstructLab, allowing for model customization using native scripts and unlocking new possibilities for multilingual AI applications. Users can also bring their own teacher models for greater control over model customization and testing for specific use cases and languages, with future support planned for Japanese, Hindi and Korean. The Red Hat AI InstructLab on IBM Cloud service is also now generally available. This new cloud service further streamlines the model customization process, improving scalability and user experience, empowering enterprises to make use of their unique data with greater ease and control. Red Hat's vision: Any model, any accelerator, any cloud. The future of AI must be defined by limitless opportunity, not constrained by infrastructure silos. Red Hat sees a horizon where organizations can deploy any model, on any accelerator, across any cloud, delivering an exceptional, more consistent user experience without exorbitant costs. To unlock the true potential of gen AI investments, enterprises require a universal inference platform–a standard for more seamless, high-performance AI innovation, both today and in the years to come. Red Hat Summit: Join the Red Hat Summit keynotes to hear the latest from Red Hat executives, customers and partners: Modernized infrastructure meets enterprise-ready AI — Tuesday, May 20, 8-10 a.m. EDT (YouTube) Hybrid cloud evolves to deliver enterprise innovation — Wednesday, May 21, 8-9:30 a.m. EDT (YouTube) Supporting Quotes: Joe Fernandes, vice president and general manager, AI Business Unit, Red Hat 'Faster, more efficient inference is emerging as the newest decision point for gen AI innovation. Red Hat AI, with enhanced inference capabilities through Red Hat AI Inference Server and a new collection of validated third-party models, helps equip organizations to deploy intelligent applications where they need to, how they need to and with the components that best meet their unique needs.' Michele Rosen, research manager, IDC 'Organizations are moving beyond initial AI explorations and are focused on practical deployments. The key to their continued success lies in the ability to be adaptable with their AI strategies to fit various environments and needs. The future of AI not only demands powerful models, but models that can be deployed with ability and cost-effectiveness. Enterprises seeking to scale their AI initiatives and deliver business value will find this flexibility absolutely essential.' About Red Hat: Red Hat is the open hybrid cloud technology leader, delivering a trusted, consistent and comprehensive foundation for transformative IT innovation and AI applications. Its portfolio of cloud, developer, AI, Linux, automation and application platform technologies enables any application, anywhere—from the datacenter to the edge. As the world's leading provider of enterprise open source software solutions, Red Hat invests in open ecosystems and communities to solve tomorrow's IT challenges. Collaborating with partners and customers, Red Hat helps them build, connect, automate, secure and manage their IT environments, supported by consulting services and award-winning training and certification offerings. Forward-Looking Statements: Except for the historical information and discussions contained herein, statements contained in this press release may constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements are based on the company's current assumptions regarding future business and financial performance. These statements involve a number of risks, uncertainties and other factors that could cause actual results to differ materially. Any forward-looking statement in this press release speaks only as of the date on which it is made. Except as required by law, the company assumes no obligation to update or revise any forward-looking statements.
Zawya
22-05-2025
- Business
- Zawya
Red Hat optimizes Red Hat AI to speed enterprise AI deployments across models, AI accelerators and clouds
Red Hat, the world's leading provider of open source solutions, today continues to deliver customer choice in enterprise AI with the introduction of Red Hat AI Inference Server, Red Hat AI third-party validated models and the integration of Llama Stack and Model Context Protocol (MCP) APIs, along with significant updates across the Red Hat AI portfolio. With these developments, Red Hat intends to further advance the capabilities organizations need to accelerate AI adoption while providing greater customer choice and confidence in generative AI (gen AI) production deployments across the hybrid cloud. According to Forrester, open source software will be the spark for accelerating enterprise AI efforts.1 As the AI landscape grows more complex and dynamic, Red Hat AI Inference Server and third party validated models provide efficient model inference and a tested collection of AI models optimized for performance on the Red Hat AI platform. Coupled with the integration of new APIs for gen AI agent development, including Llama Stack and MCP, Red Hat is working to tackle deployment complexity, empowering IT leaders, data scientists and developers to accelerate AI initiatives with greater control and efficiency. Efficient inference across the hybrid cloud with Red Hat AI Inference Server The Red Hat AI portfolio now includes the new Red Hat AI Inference Server, providing faster, more consistent and cost-effective inference at scale across hybrid cloud environments. This key addition is integrated into the latest releases of Red Hat OpenShift AI and Red Hat Enterprise Linux AI, and is also available as a standalone offering, enabling organizations to deploy intelligent applications with greater efficiency, flexibility and performance. Tested and optimized models with Red Hat AI third party validated models Red Hat AI third party validated models, available on Hugging Face, make it easier for enterprises to find the right models for their specific needs. Red Hat AI offers a collection of validated models, as well as deployment guidance to enhance customer confidence in model performance and outcome reproducibility. Select models are also optimized by Red Hat, leveraging model compression techniques to reduce size and increase inference speed, helping to minimize resource consumption and operating costs. Additionally, the ongoing model validation process helps Red Hat AI customers continue to stay at the forefront of optimized gen AI innovation. Standardized APIs for AI application and agent development with Llama Stack and MCP Red Hat AI is integrating Llama Stack, initially developed by Meta, along with Anthropic's MCP, to provide users with standardized APIs for building and deploying AI applications and agents. Currently available in developer preview in Red Hat AI, Llama Stack provides a unified API to access inference with vLLM, retrieval-augmented generation (RAG), model evaluation, guardrails and agents, across any gen AI model. MCP enables models to integrate with external tools by providing a standardized interface for connecting APIs, plugins and data sources in agent workflows. The latest release of Red Hat OpenShift AI (v2.20) delivers additional enhancements for building, training, deploying and monitoring both gen AI and predictive AI models at scale. These include: Optimized model catalog (technology preview) provides easy access to validated Red Hat and third party models, enables the deployment of these models on Red Hat OpenShift AI clusters through the web console interface and manages the lifecycle of those models leveraging Red Hat OpenShift AI's integrated registry. Distributed training through the KubeFlow Training Operator enables the scheduling and execution of InstructLab model tuning and other PyTorch-based training and tuning workloads, distributed across multiple Red Hat OpenShift nodes and GPUs and includes distributed RDMA networking–acceleration and optimized GPU utilization to reduce costs. Feature store (technology preview), based on the upstream Kubeflow Feast project, provides a centralized repository for managing and serving data for both model training and inference, streamlining data workflows to improve model accuracy and reusability. Red Hat Enterprise Linux AI 1.5 brings new updates to Red Hat's foundation model platform for developing, testing and running large language models (LLMs). Key features in version 1.5 include: Google Cloud Marketplace availability, expanding the customer choice for running Red Hat Enterprise Linux AI in public cloud environments–along with AWS and Azure–to help simplify the deployment and management of AI workloads on Google Cloud. Enhanced multi-language capabilities for Spanish, German, French and Italian via InstructLab, allowing for model customization using native scripts and unlocking new possibilities for multilingual AI applications. Users can also bring their own teacher models for greater control over model customization and testing for specific use cases and languages, with future support planned for Japanese, Hindi and Korean. The Red Hat AI InstructLab on IBM Cloud service is also now generally available. This new cloud service further streamlines the model customization process, improving scalability and user experience, empowering enterprises to make use of their unique data with greater ease and control. Red Hat's vision: Any model, any accelerator, any cloud. The future of AI must be defined by limitless opportunity, not constrained by infrastructure silos. Red Hat sees a horizon where organizations can deploy any model, on any accelerator, across any cloud, delivering an exceptional, more consistent user experience without exorbitant costs. To unlock the true potential of gen AI investments, enterprises require a universal inference platform–a standard for more seamless, high-performance AI innovation, both today and in the years to come. Red Hat Summit Join the Red Hat Summit keynotes to hear the latest from Red Hat executives, customers and partners: Modernized infrastructure meets enterprise-ready AI — Tuesday, May 20, 8-10 a.m. EDT (YouTube) Hybrid cloud evolves to deliver enterprise innovation — Wednesday, May 21, 8-9:30 a.m. EDT (YouTube) Supporting Quotes Joe Fernandes, vice president and general manager, AI Business Unit, Red Hat 'Faster, more efficient inference is emerging as the newest decision point for gen AI innovation. Red Hat AI, with enhanced inference capabilities through Red Hat AI Inference Server and a new collection of validated third-party models, helps equip organizations to deploy intelligent applications where they need to, how they need to and with the components that best meet their unique needs.' Michele Rosen, research manager, IDC 'Organizations are moving beyond initial AI explorations and are focused on practical deployments. The key to their continued success lies in the ability to be adaptable with their AI strategies to fit various environments and needs. The future of AI not only demands powerful models, but models that can be deployed with ability and cost-effectiveness. Enterprises seeking to scale their AI initiatives and deliver business value will find this flexibility absolutely essential.' 1Source: Navigate The Open-Source AI Ecosystem In The Cloud, Forrester Research, Inc., February 2025 Additional Resources Learn more about Red Hat AI Learn more about Red Hat AI Inference Server Learn more about Red Hat OpenShift AI Learn more about Red Hat Enterprise Linux AI Learn more about Red Hat AI validated models Hear more about Red Hat AI Inference Server from Red Hat executives Read about the llm-d community project Learn about Red Hat's work with Meta Learn about Red Hat's work with NVIDIA Learn about Red Hat's work with AMD Learn about Red Hat's success with Hitachi Learn about Red Hat's success with DenizBank Read more about Llama Stack and MCP Read more about model validation Read more about LLM model compression Read more about feature store Read about AI at the edge Learn more about Red Hat Summit See all of Red Hat's announcements this week in the Red Hat Summit newsroom Follow @RedHatSummit or #RHSummit on X for event-specific updates Connect with Red Hat Learn more about Red Hat Get more news in the Red Hat newsroom Read the Red Hat blog Follow Red Hat on X Follow Red Hat on Instagram Follow Red Hat on LinkedIn Watch Red Hat videos on YouTube About Red Hat Red Hat is the open hybrid cloud technology leader, delivering a trusted, consistent and comprehensive foundation for transformative IT innovation and AI applications. Its portfolio of cloud, developer, AI, Linux, automation and application platform technologies enables any application, anywhere—from the datacenter to the edge. As the world's leading provider of enterprise open source software solutions, Red Hat invests in open ecosystems and communities to solve tomorrow's IT challenges. Collaborating with partners and customers, Red Hat helps them build, connect, automate, secure and manage their IT environments, supported by consulting services and award-winning training and certification offerings. Forward-Looking Statements Except for the historical information and discussions contained herein, statements contained in this press release may constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements are based on the company's current assumptions regarding future business and financial performance. These statements involve a number of risks, uncertainties and other factors that could cause actual results to differ materially. Any forward-looking statement in this press release speaks only as of the date on which it is made. Except as required by law, the company assumes no obligation to update or revise any forward-looking statements. ### Red Hat, Red Hat Enterprise Linux, the Red Hat logo and OpenShift are trademarks or registered trademarks of Red Hat, Inc. or its subsidiaries in the U.S. and other countries. Linux® is the registered trademark of Linus Torvalds in the U.S. and other countries.
Techday NZ
21-05-2025
- Business
- Techday NZ
Red Hat & Meta unite to drive open source AI for business
Red Hat and Meta have announced a collaboration aimed at advancing open source generative artificial intelligence (AI) for enterprise use. The collaboration began with Red Hat enabling the Llama 4 model family from Meta on Red Hat AI and the vLLM inference server. This initial integration enables businesses to deploy generative AI applications and agents with a simplified process. Both companies plan to continue this effort by promoting the alignment of the Llama Stack and the vLLM community projects, with the goal of creating unified frameworks for open generative AI workloads. Red Hat and Meta indicated that they are championing open standards to ensure that generative AI applications operate efficiently across hybrid cloud environments, independent of specific hardware accelerators or computing environments. This direction is aimed at creating consistency and reducing costs in enterprise AI deployments. Mike Ferris, Senior Vice President and Chief Strategy Officer at Red Hat, stated: "Red Hat and Meta both recognize that AI's future success demands not only model advancements but also inference capabilities that let users maximize the breakthrough capabilities of next-generation models. Our joint commitment to Llama Stack and vLLM are intended to help realize a vision of faster, more consistent and more cost-effective gen AI applications running wherever needed across the hybrid cloud, regardless of accelerator or environment. This is the open future of AI, and one that Red Hat and Meta are ready to meet." According to Gartner, by 2026, over 80% of independent software vendors are expected to have embedded generative AI capabilities in their enterprise applications, compared to the less than 1% observed currently. Red Hat and Meta's collaboration addresses the need for open and interoperable foundations, particularly at the application programming interface (API) layer and within inference serving, which handles real-time operational AI workloads. Llama Stack, developed and released as open source by Meta, provides standardized building blocks and APIs for the full lifecycle of generative AI applications. Red Hat is actively contributing to the Llama Stack project, which the company expects will improve options for developers who are building agentic AI applications on Red Hat AI. Red Hat has committed to supporting a range of agentic frameworks, including Llama Stack, in order to offer customers flexibility in their tooling and development approaches. With these developments, Red Hat aims to create an environment that accelerates the development and deployment of next-generation AI solutions, which align with emerging technologies and methods in the sector. On the inference side, the vLLM project acts as an open source platform supporting efficient inference for large language models such as the Llama series. Red Hat has made leading contributions to vLLM, ensuring immediate support for Llama 4 models. Meta has pledged to increase its engagement with the vLLM community project, aiming to enhance its capabilities for cost-effective and scalable AI inference. The project is also part of the PyTorch ecosystem, which Meta and others support, contributing to an inclusive AI tools environment. Ash Jhaveri, Vice President of AI and Reality Labs Partnerships at Meta, said: "We are excited to partner with Red Hat as we work towards establishing Llama Stack as the industry standard for seamlessly building and deploying generative AI applications. This collaboration underscores our commitment to open innovation and the development of robust, scalable AI solutions that empower businesses to harness the full potential of AI technology. Together with Red Hat, we are paving the way for a future where Llama models and tools become the backbone of enterprise AI, driving efficiency and innovation across industries." The collaboration formalises the intent of both companies to bolster open source AI foundations, facilitate interoperability, and expand choice for enterprise customers in building and deploying generative AI solutions across various computing environments.
Techday NZ
21-05-2025
- Business
- Techday NZ
Red Hat unveils enhanced AI tools for hybrid cloud deployments
Red Hat has expanded its AI portfolio, introducing Red Hat AI Inference Server along with validated models and new API integrations, aimed at enabling more efficient enterprise AI deployments across diverse environments. Red Hat AI Inference Server, now included in the Red Hat AI suite, provides scalable, consistent, and cost-effective inference for hybrid cloud setups. This server is integrated into the newest releases of both Red Hat OpenShift AI and Red Hat Enterprise Linux AI, while also being available as a standalone product. The offering is designed to optimise performance, flexibility, and resource usage for organisations deploying AI-driven applications. To address the challenge many enterprises face in model selection and deployment, Red Hat has announced availability of third party validated AI models, accessible on Hugging Face. These models are tested to ensure optimal performance on the Red Hat AI platform. Red Hat also offers deployment guidance to assist customers, with select models benefiting from model compression techniques to reduce their size and increase inference speed. This approach is intended to minimise computational resources and operating costs, while the validation process helps customers remain current with the latest in generative AI innovation. The company has begun integrating the Llama Stack, developed by Meta, alongside Anthropic's Model Context Protocol (MCP), offering standardised APIs for building and deploying AI applications and agents. Currently available in developer preview in Red Hat AI, Llama Stack delivers a unified API that includes support for inference with vLLM, retrieval-augmented generation, model evaluation, guardrails, and agent functionality. MCP, meanwhile, enables AI models to connect with external tools using a standardised interface, facilitating API and plugin integrations during agent workflows. The new version of Red Hat OpenShift AI (v2.20) introduces enhancements that support the development, training, deployment, and monitoring of both generative and predictive AI models at scale. A technology preview model catalogue offers access to validated Red Hat and third party models, while distributed training capabilities via the KubeFlow Training Operator enable efficient scheduling and execution of AI model tuning across multiple nodes and GPUs. This includes support for remote direct memory access (RDMA) networking and optimised GPU utilisation, reducing operational costs. A feature store based on the Kubeflow Feast project is also available in technology preview, providing a central repository for managing and serving data, intended to improve accuracy and reusability of models. Red Hat Enterprise Linux AI 1.5 introduces updates that extend the platform's reach and its multi-language support. The system is now available on Google Cloud Marketplace, which expands customer options for running AI workloads in public cloud platforms including AWS and Azure. Enhanced language capabilities for Spanish, German, French, and Italian have been added through InstructLab, enabling model customisation in these languages. Customers are also able to bring their own teacher models for detailed tuning, with support for Japanese, Hindi, and Korean planned for the future. Additionally, the Red Hat AI InstructLab on IBM Cloud service is now generally available, aimed at simplifying model customisation and improving scalability for customers wishing to use unique data sets for AI development. Red Hat states its long-term aim is to provide a universal inference platform that allows organisations to deploy any AI model on any accelerator and across any cloud provider. The company's approach seeks to help enterprises avoid infrastructure silos and better realise the value of their investments in generative AI. Joe Fernandes, Vice President and General Manager of the AI Business Unit at Red Hat, said, "Faster, more efficient inference is emerging as the newest decision point for gen AI innovation. Red Hat AI, with enhanced inference capabilities through Red Hat AI Inference Server and a new collection of validated third-party models, helps equip organisations to deploy intelligent applications where they need to, how they need to and with the components that best meet their unique needs." Michele Rosen, Research Manager at IDC, commented on shifting enterprise AI needs: "Organisations are moving beyond initial AI explorations and are focused on practical deployments. The key to their continued success lies in the ability to be adaptable with their AI strategies to fit various environments and needs. The future of AI not only demands powerful models, but models that can be deployed with ability and cost-effectiveness. Enterprises seeking to scale their AI initiatives and deliver business value will find this flexibility absolutely essential." Red Hat's recent portfolio enhancements are in line with the views outlined by Forrester, which stated open source software will be instrumental in accelerating enterprise AI programmes.
Business Wire
20-05-2025
- Business
- Business Wire
Red Hat and Meta Collaborate to Advance Open Source AI for Enterprise
BOSTON – RED HAT SUMMIT--(BUSINESS WIRE)--Red Hat, the world's leading provider of open source solutions, and Meta today announced a new collaboration to spur the evolution of generative AI (gen AI) for the enterprise. This collaboration started with Red Hat's day 0 enablement of the groundbreaking Llama 4 model family on Red Hat AI and the high-performing vLLM inference server. Building on this momentum, Red Hat and Meta will also champion the alignment of the Llama Stack and the vLLM community projects, helping to drive unified frameworks for the democratization and simplification of open gen AI workloads. Red Hat and Meta collaborate around open source enterprise AI with vLLM and Llama Stack Share According to Gartner 1, 'by 2026, more than 80% of independent software vendors (ISVs) will have embedded generative AI capabilities in their enterprise applications, up from less than 1% today.' This underscores the urgent need for the open, interoperable foundations that Red Hat and Meta are pioneering. The companies' collaboration directly addresses the critical requirement for more seamless gen AI workload functionality across diverse platforms, clouds and AI accelerators, particularly at the crucial application programming interface (API) layer and within the 'doing' phase of AI — inference serving. Red Hat and Meta's deep commitment to open innovation is evident in their roles as primary commercial contributors to foundational projects: Llama Stack, developed and open-sourced by Meta, delivers standardized building blocks and APIs to revolutionize the entire gen AI application lifecycle; and vLLM, where Red Hat's leading contributions are powering an open source platform that enables highly efficient and optimized inference for large language models (LLMs), including Day 0 support for Llama 4. Creating common foundations and open choice for gen AI apps As part of this collaboration, Red Hat is actively contributing to the Llama Stack project, helping further enhance its capabilities as a compelling choice for developers building innovative, agentic AI applications on Red Hat AI. With Red Hat AI, Red Hat maintains a commitment to supporting a diverse range of agentic frameworks, including Llama Stack, fostering customer choice in tooling and innovation. This enablement aims to provide a robust and adaptable environment to accelerate the development and deployment of next-generation AI solutions, a wave that embraces the evolving landscape of agentic technologies. Trailblazing the future of AI inference with vLLM The vLLM project, already pushing the boundaries of efficient and cost-effective open gen AI, gains further momentum with Meta's commitment to deepen community contributions. This collaboration gives vLLM the capacity to provide Day 0 support for the latest generations of the Llama model family, starting with Llama 4. vLLM is also part of the PyTorch Ecosystem where Meta and others collaborate to foster an open and inclusive tools ecosystem. This validation positions vLLM at the forefront of unlocking gen AI value in the enterprise. Red Hat Summit Join the Red Hat Summit keynotes to hear the latest from Red Hat executives, customers and partners: Modernized infrastructure meets enterprise-ready AI — Tuesday, May 20, 8-10 a.m. EDT (YouTube) Hybrid cloud evolves to deliver enterprise innovation — Wednesday, May 21, 8-9:30 a.m. EDT (YouTube) Supporting Quotes Mike Ferris, senior vice president and chief strategy officer, Red Hat 'Red Hat and Meta both recognize that AI's future success demands not only model advancements but also inference capabilities that let users maximize the breakthrough capabilities of next-generation models. Our joint commitment to Llama Stack and vLLM are intended to help realize a vision of faster, more consistent and more cost-effective gen AI applications running wherever needed across the hybrid cloud, regardless of accelerator or environment. This is the open future of AI, and one that Red Hat and Meta are ready to meet.' Ash Jhaveri, vice president, AI and Reality Labs Partnerships, Meta "We are excited to partner with Red Hat as we work towards establishing Llama Stack as the industry standard for seamlessly building and deploying generative AI applications. This collaboration underscores our commitment to open innovation and the development of robust, scalable AI solutions that empower businesses to harness the full potential of AI technology. Together with Red Hat, we are paving the way for a future where Llama models and tools become the backbone of enterprise AI, driving efficiency and innovation across industries." Additional Resources Connect with Red Hat About Red Hat Red Hat is the world's leading provider of enterprise open source software solutions, using a community-powered approach to deliver reliable and high-performing Linux, hybrid cloud, container, and Kubernetes technologies. Red Hat helps customers integrate new and existing IT applications, develop cloud-native applications, standardize on our industry-leading operating system, and automate, secure, and manage complex environments. Award-winning support, training, and consulting services make Red Hat a trusted adviser to the Fortune 500. As a strategic partner to cloud providers, system integrators, application vendors, customers, and open source communities, Red Hat can help organizations prepare for the digital future. Forward-Looking Statements Except for the historical information and discussions contained herein, statements contained in this press release may constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements are based on the company's current assumptions regarding future business and financial performance. These statements involve a number of risks, uncertainties and other factors that could cause actual results to differ materially. Any forward-looking statement in this press release speaks only as of the date on which it is made. Except as required by law, the company assumes no obligation to update or revise any forward-looking statements. Red Hat and the Red Hat logo are trademarks or registered trademarks of Red Hat, Inc. or its subsidiaries in the U.S. and other countries. 1 Gartner, 2025 TSP Planning Trends: Managing the GenAI Inference 'Tax,' 2 September 2024, ID G00818892, John Lovelock and Mark McDonald
