Artificial intelligence (AI) continues to reshape industries and enhance everyday life in exciting new ways. In this roundup, we’re taking a look at how Red Hat is pushing the boundaries in the AI space, from advancing open source solutions to automating performance and supporting different industries like life sciences and public services. Red Hat is dedicated to making AI more accessible, transparent and impactful for everyone.
1. Open source AI: Red Hat’s point-of-view
Chris Wright shares Red Hat’s perspective and vision on what truly makes AI open source. At a minimum, we believe that open source AI should include open source-licensed model weights along with open source software components. But this is just a starting point, not the final destination. Red Hat is helping make this vision a reality with projects like InstructLab, which makes AI contribution more accessible, and the Granite family of large language models (LLMs), designed for real-world enterprise use. As AI evolves, Red Hat will continue to drive transparency, collaboration and innovation in open source AI.
2. Future-proof your tech career: 6 essential human skills for the AI era
AI is transforming the tech industry by automating tasks, but human skills like problem solving, critical thinking and communication remain essential. While AI accelerates efficiency, human judgment is still needed for creativity, ethical decision-making and collaboration. To stay competitive, tech professionals should focus on adaptability and using AI as a tool rather than fearing its impact.
3. Unleash the full potential of LLMs: Optimize for performance with vLLM
LLMs offer high potential, but they come with high computational costs and complexity. Businesses can significantly lower infrastructure costs and deployment time by taking advantage of model compression techniques such as quantization and sparsity, as well as vLLM’s high-performance inference capabilities. This combination enables scalable, real-time AI applications with lower costs, making advanced LLMs more accessible and efficient across diverse hardware setups.
4. Beyond the AI pilot project: Building a foundation for generative AI
Many organizations struggle to move AI projects from pilot to production, but open source technologies can help. This article highlights 11 key resources—including e-books, webinars and training programs—to guide businesses in building scalable, secure and efficient generative AI solutions. With a commitment to open source, Red Hat is helping enterprises navigate AI adoption with flexibility, transparency and innovation.
5. Accelerating Azure AI with Ansible Automation Platform: from subscriptions to AI models
Red Hat Ansible Automation Platform helps businesses automate the deployment of Azure AI resources, improving consistency, efficiency and scalability. By using Azure services like Cognitive Services and OpenAI models, organizations can streamline complex tasks, reduce human errors and accelerate AI adoption. Ansible Automation Platform’s integration with Azure, along with its agentless architecture and human-readable YAML playbooks, simplifies the process of deploying and managing advanced AI capabilities.
6. AI in the life sciences: building the platform, growing the ecosystem
AI is changing life sciences and Red Hat's open source initiatives are playing a key role in overcoming the challenges in the field, such as data bias and accessibility. Through collaborations with companies like the Mass Open Cloud Alliance, Red Hat is democratizing access to AI tools, helping researchers drive breakthroughs in drug discovery and healthcare. Through focusing on accessibility, transparency and scale, Red Hat is accelerating its innovation and fostering an ecosystem that benefits researchers, developers and patients alike.
7. What’s new with the command line interface in RHEL AI 1.4?
Red Hat Enterprise Linux AI 1.4 introduces background process management, allowing users to run processes in the background, track their status and easily reconnect them when needed. The update also includes new model management features, enabling users to upload fine-tuned models to platforms like Hugging Face and S3 buckets. These new features improve workflow efficiency and provide more flexibility for developers working with AI models.
8. How Red Hat OpenShift AI can help transform public services and infrastructure in the UK
Red Hat OpenShift AI plays an important role in helping the UK government achieve its AI goals, from fostering a world-class AI ecosystem to powering sector-specific changes in healthcare, transportation and public safety. By providing scalable solutions with an enhanced security posture, Red Hat technologies help support the ethical development and deployment of AI, simplifying transparency and regulatory compliance. Through collaborations and training initiatives, Red Hat also strengthens the UK's AI talent pipeline, making it easier for industries and governments to adopt AI technologies responsibly.
Wrap up
Red Hat is fully committed to advancing AI in ways that are open, scalable and designed for real-world applications. By pushing our open source solutions boundaries, improving performance, and helping industries responsibly use AI, Red Hat is helping enterprises with more efficient and effective AI adoption. With our commitment to collaboration and innovation, we are helping AI make a lasting, positive and meaningful difference in our world.
关于作者
Isabel Lee is the Managing Editor on the Editorial team at Red Hat. She supports the content publishing process by managing submissions, facilitating cross-functional reviews, and coordinating timelines. Isabel works closely with authors to shape clear, engaging blog content that aligns with Red Hat’s voice and values. She also helps with blog planning, internal communications, and editorial operations. With a background in public relations and a passion for thoughtful storytelling, she brings creativity, curiosity, and attention to detail to the team’s work.
