June 13, 2024, 6:06 p.m. | Aayush Mittal

Unite.AI www.unite.ai

As the capabilities of large language models (LLMs) continue to expand, developing robust AI systems that leverage their potential has become increasingly complex. Conventional approaches often involve intricate prompting techniques, data generation for fine-tuning, and manual guidance to ensure adherence to domain-specific constraints. However, this process can be tedious, error-prone, and heavily reliant on human […]


The post Optimize LLM with DSPy : A Step-by-Step Guide to build, optimize, and evaluate AI systems appeared first on Unite.AI.

ai systems become build capabilities constraints data data generation domain dspy expand fine-tuning gpt guidance guide however language language models large language large language models llm llms lm prompts openai potential prompt-engineering prompting python robust step-by-step systems

Senior Data Engineer

@ Displate | Warsaw

Professor/Associate Professor of Health Informatics [LKCMedicine]

@ Nanyang Technological University | NTU Novena Campus, Singapore

Research Fellow (Computer Science (and Engineering)/Electronic Engineering/Applied Mathematics/Perception Sciences)

@ Nanyang Technological University | NTU Main Campus, Singapore

Java Developer - Assistant Manager

@ State Street | Bengaluru, India

Senior Java/Python Developer

@ General Motors | Austin IT Innovation Center North - Austin IT Innovation Center North

Research Associate (Computer Engineering/Computer Science/Electronics Engineering)

@ Nanyang Technological University | NTU Main Campus, Singapore