Augento's service is not open source, but it fine-tunes open-source language models, offering an alternative to OpenAI's reinforcement fine-tuning API with more customization options. Users are charged a monthly fee plus training and inference costs, and the platform is accessible for self-service with an initial $20 in training credits. The company aims to improve agent performance in practical applications by leveraging reinforcement learning techniques and seeks user feedback to refine their offering.
Key takeaways:
- Augento offers a fine-tuning service for language models using reinforcement learning, allowing users to optimize models for specific tasks by providing a reward function.
- The platform supports various use cases, such as coding agents, tool specialization, browser navigation, and robot control, by fine-tuning models based on task-specific criteria.
- Augento plans to introduce an "alignment mode" that allows users to provide high-level feedback on agent failures without needing to write formal reward functions.
- The service is not open source but fine-tunes open-source language models, offering a customizable alternative to OpenAI's reinforcement fine-tuning API, with a pricing model based on training and inference costs.