Generate consensus answers with multiple AI models & peer review system

About This Workflow

What This Workflow Does

This workflow allows users to generate consensus answers from multiple AI models and incorporate a peer review system, inspired by Andrej Karpathy's LLM Council. It creates a "council" of AI models that work together to produce a more accurate and reliable output. This workflow is designed to leverage the strengths of various AI models and provide a robust solution for decision-making or problem-solving.

Who Should Use This

This workflow is ideal for developers, data scientists, and engineers working with machine learning models, as well as business owners and marketers looking to implement AI-driven decision-making processes.

Key Features

• Multi-Model Consensus: This workflow combines the outputs of multiple AI models to generate a consensus answer, reducing the risk of individual model biases.
• Peer Review System: A built-in peer review system allows users to review and validate the consensus answer, ensuring its accuracy and reliability.
• Integration with AI Models: The workflow supports integration with various AI models, including those from popular platforms like Google Cloud AI, Microsoft Azure, and Amazon SageMaker.
• Customizable: Users can customize the workflow to suit their specific needs, adjusting the number of AI models, peer review settings, and more.

How to Get Started

To use this workflow, simply import it into your n8n instance and configure the AI models and peer review settings to suit your needs. You can then use the workflow to generate consensus answers and make informed decisions with confidence.