Three roles in Flexstack AI

The Flexstack AI platform decomposes the modern AI tech stack into three primary jobs, each with unique requirements for qualified participants.

Interface

The Flexstack Interface role is pivotal for users looking to interact with the AI as API consumers. Besides requesting AI services from our extensive network, users in this category have the unique opportunity to train a LORA (Learning and Optimization Reflective Agent) using either private data or data available through our network.

AI Stack

Individuals assuming the Flexstack AI Stack role are integral to the computational backbone of the AI model. These users are tasked with either computing results from existing AI models or engaging in the training of new models. The Flexstack AI Stack serves as a foundational element of our platform, ensuring the seamless execution and continual advancement of AI capabilities within the network. This role is suited for users with the resources and desire to contribute to the computational and developmental aspects of AI technologies.

Validator

The Flexstack Validator is important to the synthesis and delivery of AI-generated outputs to end-users. Beyond result generation, the Validator is also charged with the collection of user feedback and the initiation of network updates. This feedback loop is vital for the iterative improvement of AI models and AI stacks. Initially there will only be one validator with plans to allow development of multiple competing validators in the future.