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The Next Generation of AI-Powered Observability

AI is changing our world, and its impact on observability is no different. This article discusses some of the components of a good observability platform, how AI is well-positioned to revolutionize observability, and how Lumigo Copilot Beta will provide substantial value to customers and partners.

Enhancing Collaboration with AI Security Assistants with Robert Grazioli, CIO, Ivanti

Ivanti CIO Robert Grazioli shares his insights on how AI is transforming the cybersecurity industry. Read the full report for more: ivanti.com/ai-security This expert commentary highlights the importance of AI assistants in empowering security professionals, breaking down silos, and improving response times. Learn how AI is radically reshaping the cyber threat landscape due to AI’s ability to quickly penetrate siloed security operations. However, security teams can leverage AI to counter these sophisticated attacks and boost their own skill sets.

Intel the era of AI: business transformation with open source | Data & AI Masters

AI is transforming the way organizations work globally. It makes everyone look differently at all scales, from workstations to data centers and edge devices. Intel’s strategy heavily focuses on AI as the next milestone to drive innovation and enable other organizations to move their projects beyond experimentation.

Flowmon - AI-Powered Cybersecurity Platform

Today's primary cybersecurity challenge is event overload. With a flood of alerts coming from numerous systems, analysts struggle to prioritize and investigate effectively. This not only delays responses to genuine threats, but also leaves organizations more vulnerable. For Progress Flowmon, accuracy and rapid response are essential. Flowmon is an AI-driven network security analyst that works alongside your team, monitoring your network 24/7.

What is RAG?

In a 2020 paper, Patrick Lewis and his research team introduced the term RAG, or retrieval-augmented generation. This technique enhances generative AI models by utilizing external knowledge sources such as documents and extensive databases. RAG addresses a gap in traditional Large Language Models (LLMs). While traditional models rely on static knowledge already contained within them, RAG incorporates current information that serves as a reliable source of truth for LLMs.

How to Build Omni Model Dynamic AI Assistants using Intelligent Prompting

My name is Tim Gühnemann, and as an AI engineering working student at ilert, I had the privilege of developing and continuous improving ilert AI, ensuring it meets the needs of our customers and aligns with our vision. ‍ Our goal was to provide all our customers with access to ilert AI. We aimed to develop a solution that could adapt dynamically and function independently based on our use cases, similar to the OpenAI Assistant API.

AI Log Analysis - Shaping the Future of Observability

As digital applications and infrastructures grow increasingly complex, managing and understanding log data has become increasingly vital in achieving practical observability, enabling organizations to detect, diagnose, and prevent issues across their systems. However, traditional log analysis methods often struggle with the volume and complexities of modern log data in cloud-native environments.

AI and the Demand for Data Center Interconnectivity

Attention is growing in the market towards developing infrastructure capable of accommodating the rising demand and scale of AI. Furthermore, there is a rising trend in the planning and construction of edge data centers located nearer to end users, aimed at addressing the high power requirements of GPUs and the ongoing transition of enterprise IT toward cloud solutions.