Jun 12, 2024
TEXTGRAD - Revolutionizing LLMs with Automatic Differentiation via Text
Artificial Intelligence (AI) is constantly evolving, and one of the latest breakthroughs is the introduction of TEXTGRAD, a novel framework that utilizes automatic differentiation via text to optimize various components within AI systems. Developed by researchers at Stanford University, TEXTGRAD is designed to improve the performance of Large Language Models (LLMs) by leveraging natural language feedback.
May 30, 2024
Optimizing Gen-AI Applications with DSPy and Haystack - A Practical Guide
Building Gen-AI applications often involves the challenging and time-consuming task of manually optimizing prompts. DSPy, an open-source library, addresses this by transforming prompt engineering into an optimization problem, making it more scalable and robust.
Mar 24, 2024
Dynamic Movement Primitives
Dynamic Movement Primitives (DMPs) are a framework used in robotics and computational neuroscience to model and generate complex motor behaviors. This framework was designed to capture the essence of movement skills, making it easier to learn and reproduce various motions.