But Red Hat Summit and Ansible Fest In Boston this month, a lot of publicity and overflow about generic AI took a rear seat for dialogue as to how organizations can actually build and deploy AI for their own business using their own data.
Of course, it is a red hat summit, and core themes such as open source were given a lot of attention, with a red hat enterprise Linux 10 release, and automation and management with unasable. But like everything nowadays, AI attracted a lot of attention to the conference, but at least it was very fresh and severely practical.
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Instead of more hypnotized A-eirs as AI assistants, which recently found limited interest for most users in the Aberdeen/ZDNET poll, most sessions and key announcements were focusing on technologies and strategies that could use today to take advantage of AI.
https://www.youtube.com/watch?v=hcrcdubkdqu
For example, the process of running the AI model with new data for predictions or decision making was a lot of focus on estimating. Such announcements on technologies like VLLM And LLM-D Provide better scaling and perineogen options while spreading compute loads that simplify the complications of henning when spreading compute loads.
Aberdeen Research has consistently gained high level of interest for most businesses, in which 37% of organizations want to deploy AI’s estimate internal. These organizations want AI solutions that help them use their own data to run AI solutions that are ready to meet their specific requirements by improving data sovereignty and internal control.
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With henning, we also saw a major focus on agentic technologies and emerging technologies that can help businesses automate and integrate with custom-made AI agents. Many of these discussions focus on MCP (Model Reference Protocol), a new open source standard designed to reduce the manufacture of agents manufactured using custom data and integrate with custom services.
Again, instead of focusing on hyped AI assistants and chatbots, the summit saw the technique to help businesses to automate important tasks, to streamline operations and to help free human resources for more strategic initiatives. And there was also an honest discussion about security implications, especially some outstanding issues such as authentication such as the next version of MCP.
This is bound in one of the most reception discussions at the summit how to enable the safe use of AI within a commercial context. While the discussion about AI often involves questions about data integrity, especially when public LLMs are involved, talk about the security implications of the construction and deployment of AI, it is often difficult to find.
Again, most of this focus aligns well with research that is using AI in Aberdeen businesses. Our research shows that cyber security is a matter of concern for companies availing AI and a top barrier for effective AI deployment.
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It will be interesting to see if AI follows the same path as other over-snake techniques. Already there are arguments that AI is on the bottom of public spirit.
But in previous propaganda cycles, we have seen that when over-the-top predictions go wrong, exactly occurs when business and practical user technology are putting out the hyp bicycle for effective use. Given the focus of the Red Hat Summit/Ansiable Festival on cases of practical and business-taiyar use for AI, it may be what is happening now.
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