A team from Hong Kong Polytechnic University introduced LAMBDA, an open-source, code-free multi-agent data analysis system. This innovation bridges the gap between domain experts and advanced AI models, allowing smooth interaction in data science. LAMBDA’s agents work together to analyze data using natural language.
The process begins with writing code based on user instructions, then executing it on a host system. Agents assume two roles: the “programmer,” who writes code per user directions and dataset, and the “inspector,” suggesting improvements if the code encounters errors.
LAMBDA achieved impressive results in machine learning tasks, with high accuracy rates for AIDS (89.67%), NHANES (100%), Breast Cancer (98.07%), and Wine (98.89%) datasets. Regression tasks saw the lowest MSE of 0.2749, 0.0315, 0.4542, and 0.2528 for respective datasets. LAMBDA’s success lies in handling various data science applications without human intervention or coding skills.
LAMBDA, using AI and human expertise, aims to make data analysis accessible, fostering innovation and future discoveries. The researchers plan to enhance it with planning and reasoning techniques. Join their Twitter, Telegram Channel, LinkedIn Group, Reddit, and follow their newsletter for updates. For more AI webinars, visit the provided link.
Sajjad Ansari is a final-year undergraduate student at IIT Kharagpur with a passion for AI, focusing on real-world applications and understanding AI’s impact. He strives to clarify complex AI concepts.
Source: https://www.marktechpost.com/2024/07/28/lambda-a-new-open-source-code-free-multi-agent-data-analysis-system-to-bridge-the-gap-between-domain-experts-and-advanced-ai-models/