The State of Agentic AI

AI Development & Trends - The modern AI movement significantly accelerated with the advent of ChatGPT two and a half years ago [1] - Open models like LLaMA and Mistral are democratizing AI, making it accessible for broader deployment on-premise or in the cloud [1] - The industry is evolving from Retrieval Augmented Generation (RAG) models to agentic AI, focusing on making AI more actionable and integrated with enterprise data [1] - DeepSeek, an open model, has emerged as a significant advancement in AI, demonstrating reasoning capabilities comparable to proprietary models [1] Enterprise AI Adoption & Impact - AI is increasingly integrated into applications used by a billion knowledge workers, enhancing productivity [1] - 50% of organizations are expected to leverage AI agents to derive better value by 2025 [1] - AI is facilitating quicker content creation, exemplified by the ease of producing videos for platforms like YouTube [1] - NVIDIA focuses on providing a platform for partners to build AI-powered solutions, rather than developing end-user applications [1] Data & Infrastructure - Enterprise data is growing massively, with 11 zettabytes created, highlighting the need for AI to leverage this unstructured data [2] - NVIDIA emphasizes high-performance ingestion tools and data efficiency improvements (35% data improvement) to ensure accurate and reliable AI outputs [2] - NVIDIA Enterprise provides enterprise-ready AI solutions with constant CVEs, tech support, and ABI stability, ensuring solutions built today will continue to work [2] Customer Solutions & Partnerships - NVIDIA partners with companies like DDN to deliver AI solutions to customers, focusing on solving customer problems and driving revenue [1][2] - NVIDIA's Nemo solutions and custom models have enabled partners like Justt.ai to achieve rapid growth and customer adoption [2] - SAP is leveraging NVIDIA's AI to improve its ABAP programming language, helping customers clean up code and solve 80% of coding problems [2]