What is LLMOps?
LLMOps (Large Language Model Operations) is a specialized domain within the broader machine learning operations (MLOps) field. LLMOps focuses specifically on the operational aspects of large language models (LLMs). LLM examples include GPT, BERT, and similar advanced AI systems.
LLM models are large deep learning models trained on vast datasets, adaptable to various tasks, and specialized in NLP tasks. Addressing LLM risks is an important part of gen AI productization. These risks include bias, IP and privacy issues, toxicity, regulatory non-compliance, misuse, and hallucination. Mitigation starts by ensuring the training data is reliable, trustworthy, and adheres to ethical values.
LLMOPS vs MLOPS: Making the Right Choice
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. 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, clarifying their roles, and illustrating the impact of each approach on the deployment and management of AI initiatives.
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