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LL-Mesh (nickname Athon) is a pioneering initiative by HPE Athonet aimed at democratizing Generative Artificial Intelligence (Gen AI). Our vision is to make Gen AI accessible and beneficial to a broader audience, enabling users from various backgrounds to leverage cutting-edge Gen AI technology effortlessly.
Gen AI has the potential to revolutionize businesses, but adopting it comes with challenges:
- Technical Complexity: Gen AI tools are powerful but often require both coding and machine learning expertise. This makes it difficult for companies to use these tools effectively without specialized skills.
- Organizational Challenges: Simply adding a Gen AI team isn’t enough. The real value comes from using the knowledge of your existing teams, especially those who may not be tech experts. However, if not done right, Gen AI can impact team dynamics. It’s important to find ways to use Gen AI that enhance collaboration and make the most of everyone’s expertise.
LL-Mesh empowers users to create tools and web applications using Gen AI with Low or No Coding. This approach addresses the technical challenges by simplifying the integration process. By leveraging the Pareto principle, Athon focuses on the 20% of features that cover 80% of user needs. This is achieved by abstracting complex, low-level libraries into easy-to-understand services that are accessible even to non-developers, effectively hiding the underlying complexity.
This simplicity not only helps technical teams but also enables non-technical teams to develop tools related to their domain expertise. The platform then allows for the creation of a "Mesh" of these Gen AI tools, providing orchestration capabilities through an agentic Reasoning Engine based on Large Language Models (LLMs). This orchestration ensures that all tools work together seamlessly, enhancing overall functionality and efficiency across the organization.
- Product Vision: Background information and the broad goals of our project.
- Installation Guide: Step-by-step instructions to get our project up and running on your system.
- Usage Guide: How to use LL-Mesh, including examples and templates.
- Software Architecture: An overview of our project's architecture, including key components.
- Federated Governance: Governance model ensuring consistency, ethics, and quality across the project.
- Contribution Guidelines: How you can contribute to the project, regardless of your skill set.
- Changelog: History of updates and changes made to the project.
Explore the Wiki to discover more about how LL-Mesh can revolutionize your approach to Gen AI!
We welcome your feedback and questions! If you have suggestions, questions, or encounter any issues, please reach out to us through mail at antonio.fin@hpe.com. Your input is valuable to the success and continuous improvement of LL-Mesh.
