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In the rapidly evolving landscape of artificial intelligence and machine learning, new terminologies and concepts frequently emerge, often causing confusion among business leaders, IT analysts, and decision-makers. Among these, two terms have gained prominence: LLMOps vs MLOps. While sounding similar, LLMOps and MLOps represent distinct approaches that can significantly impact how organizations harness the power of AI technologies. This article compares LLMOps and MLOPs to equip you with the necessary insights, facilitating informed decisions tailored to your business objectives and technological needs. What is LLMOps? LLMOPS stands for Large Language Model Operations, denoting a strategy or system to automate and refine the AI development pipeline through the utilization of expansive language models. LLMOPs tools facilitate the continuous integration of these substantial language models as the underlying backend or driving force for AI applications. Key Components of LLMOps: 1.) ....
When exploring the use of AI, methods used to explore the use of social media platforms, allowing technology companies to track you through cookies, sharing your camera, voice, and location are still relevant in assessing the risk of using AI technology. ....