Scaling Intelligence: Overcoming Infrastructure Challenges in Large Language Model Operations
Author(s): Rajarshi Tarafdar Originally published on Towards AI. The scenario is pretty brightening for artificial intelligence (AI) and large language models (LLMs) — enabling features from chatbots to advanced decision-making systems. However, making these models compatible with enterprise use cases is a …
Prompt Engineering Mastery: Optimizing LLM Performance Through Iterative Prompt Management
Author(s): Rajarshi Tarafdar Originally published on Towards AI. The introduction of large language models (LLMs) has truly transformed AI usage from customer service automation to content creation. The performance of these models is heavily reliant on the interaction with the system, and …
From Code to Conversation: The Rise of Seamless MLOps-DevOps Fusion in Large Language Models
Author(s): Rajarshi Tarafdar Originally published on Towards AI. Artificial intelligence has undergone rapid evolution through large language models which enable technology systems to interact with users like human beings. The sophisticated interfaces of automation systems operate through an operational infrastructure which requires …
Ethics Meets Efficiency: Navigating Compliance and Trust in Next Gen LLM Operations
Author(s): Rajarshi Tarafdar Originally published on Towards AI. Industrial transformations achieved by Large Language Models (LLMs) have introduced breakthrough levels of automation throughout text production and natural language processing and decision-making systems. These computational models produce human-like text which defines artificial intelligence …
Revolutionizing AI Deployment: How Automated LLMOps is Powering the Future of Intelligent Systems
Author(s): Rajarshi Tarafdar Originally published on Towards AI. Increased sophistication in artificial intelligence necessitates an appropriate development of an operational infrastructure framework. Large Language Model Operations (LLMOps) functions as a crucial operating system designed to manage the entire lifecycle process of large …
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