LLMOps

LLM Monitoring and Observability: Hands-on with Langfuse

: You will have built a fancy LLM application that responds to user queries about a selected domain. You will have spent days organising the entire pipeline, from refining your prompts to adding context...

The Rise of LLMOps within the Age of AI

Within the fast-evolving IT landscape, MLOps—short for Machine Learning Operations—has develop into the key weapon for organizations aiming to show complex data into powerful, actionable insights. MLOps is a set of practices designed to...

LLMOps: The Next Frontier for Machine Learning Operations

Machine learning (ML) is a robust technology that may solve complex problems and deliver customer value. Nonetheless, ML models are difficult to develop and deploy. They need a variety of expertise, resources, and coordination....

Bridging Large Language Models and Business: LLMops

The underpinnings of LLMs like OpenAI's GPT-3 or its successor GPT-4 lie in deep learning, a subset of AI, which leverages neural networks with three or more layers. These models are trained on vast...

LLMOps: My Thesis & Market Map Table of Contents Introduction Why does LLMOps matter now? Issues with LLMs in production? LLMOps Market Map My predictions for LLMOps Concluding Remarks

: Just as we saw with SQL, document, graph, etc. databases — I foresee that two major players will emerge within the vector database space (one closed source and one open source player). While...

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