news
IBM Red Hat Having a Slop Festival/"AI" Fest
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Red Hat Official ☛ Why standardization is the key to agentic AI success: How a unified platform spurs innovation [Ed: More "AI" and not real innovation at Red Hat; they're only being toyed around by IBM for vapourware purposes]
Standardization is a primary factor in meeting this challenge, primarily by reducing complexity and increasing efficiency. By combining Model Context Protocol (MCP) and Llama Stack on a platform like Red Hat OpenShift AI, you can create a unified and portable environment for your AI applications.
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Red Hat Official ☛ Red Hat AI 3 delivers speed, accelerated delivery, and scale [Ed: Nothing left to show but stupid buzzwords and misnomers like "AI" (slop, plagiarism)]
Red Hat’s strategy is to serve any model across any accelerator and any environment. The latest inferencing improvements offer features to meet Service Level Agreements (SLAs) of generative AI (gen AI) applications, support for additional hardware accelerators, and an expanded catalog of validated and optimized third-party models. Some highlights include:
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Red Hat Official ☛ Introducing AI hub and gen AI studio: The new command center for enterprise gen AI in Red Hat OpenShift AI [Ed: Red Hat is not focusing on engineering and is instead trying to pump up IBM's share price based on lies]
At Red Hat, we believe the future of AI is open, accessible, and manageable at scale. That's why we’re excited to announce 2 new consolidated dashboard experiences in Red Hat OpenShift AI 3.0: the AI Hub and the Gen AI studio.
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Red Hat Official ☛ How Red Hat partners are powering the next wave of enterprise AI [Ed: Stupid hype wave, sold for IBM instead of GNU/Linux]
The Red Hat partner ecosystem is the engine that will deliver the generative AI (gen AI) and agentic capabilities that customers need for broad market adoption. It’s about bringing together the best in hardware, software, and services to create a whole that is far greater than the sum of its parts.
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Red Hat Official ☛ Deploy with confidence: Announcing the latest Red Hat AI validated models [Ed: Just hype and slop, not real substance being sole]
Red Hat AI’s validated models go beyond a simple list, providing efficient, enterprise-ready AI. We combine rigorous performance benchmarking and accuracy testing with a comprehensive packaging process designed to deploy with security and simplicity in mind. Each model is scanned for vulnerabilities and integrated into a managed software lifecycle, helping ensure you receive a high-performing and resource-optimized asset that is focused on security, easy to manage, and ready for long-term updates.
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Red Hat Official ☛ Beyond the model: Why intelligent infrastructure is the next AI frontier [Ed: Red Hat overselling hype and bubbles]
As discussed in a recent episode of the Technically Speaking podcast, most organizations' AI journey and PoCs begin with deploying a model on a single server—a manageable task. But the next step often requires a massive leap to distributed, production-grade AI inference. This is not simply a matter of adding more machines—we believe this requires a new kind of intelligence within the infrastructure itself—an AI-aware control plane that can help manage the complexity of these unique and dynamic workloads.