Operations | Monitoring | ITSM | DevOps | Cloud

Several open-source standards have emerged for AI agents and agentic frameworks, aiming to improve interoperability and standardization in the rapidly evolving field of AI.

GRPO is a new reinforcement learning technique that replaces traditional methods like Proximal Policy Optimization (PPO) DeepSeek’s Group Relative Policy Optimization (GRPO) represents a paradigm shift in reinforcement learning (RL) for large language models, addressing key limitations of Proximal Policy Optimization (PPO) through innovative simplifications and efficiency gains. Here’s why GRPO stands out.

When choosing between Retrieval-Augmented Generation (RAG) and Low-Rank Adaptation (LoRA) for model training, the decision hinges on your specific use case, resource constraints, and performance requirements. Here’s a structured comparison to guide your selection.

The recently concluded Cisco Live’25 event in Amsterdam, gave a glimpse into Cisco’s strategy for the coming years, has the potential to join the $1 Trillion club, with its broad reach across Networking and Security. The recent market trends around Agentic AI are ripe to act as a catalyst for this.

Over the past couple of years, many of us have been utilizing Generative AI interfaces and co-pilots to enhance our communication, conduct research, and summarize complex information. AI-based agents are digital entities created to autonomously derive insights from data and execute actions. Agents are focused on accomplishing a specific outcome without the needfor constant human intervention.

In the rapidly evolving landscape of artificial intelligence, DeepSeek has emerged as a potentially transformative player, challenging conventional approaches to AI development with its innovative open-source model. This breakthrough raises important questions about the future of Agentic AI and AGI development, particularly in terms of accessibility and cost-effectiveness.

Following up on NASA’s Artemis mission Roadmap for Lunar exploration CloudFabrix has been embarking on its own Roadmap for CY’2022, CY’2023, and beyond. It was an incredible year of innovation, execution and global growth for the CloudFabrix team and the following summarizes our key 2024 achievements.

With agentic AI integrated, seamless workflow automation in IT operations is now achievable. By utilizing this advanced AI, organizations can achieve autonomous systems that respond in real-time and learn and adapt, creating operational efficiencies that reduce manual oversight. CloudFabrix, a provider of AI-driven IT solutions, leverages agentic AI to transform complex workflows, reduce manual workloads, and help organizations become more resilient and agile.

At the GenAI Summit in San Francisco, from May 28th to 31st, CloudFabrix proudly showcased the latest advancements of its Macaw GenAI Assistant and its Robotic Data Automation Fabric (RDAF) platform. These technologies are not only reshaping the future of IT operations and observability but also setting the stage for the company’s next chapter as a member of the NVIDIA Inception Program.

In an era where digital infrastructures are increasingly hybrid, the ability to efficiently monitor, analyze, and act on vast amounts of operational data is a significant challenge. According to Gartner, the surge in data volumes, with some workloads producing petabytes of telemetry annually, has led to heightened complexity and soaring costs—potentially exceeding $10 million annually for large enterprises.