Democratising access to reinforcement learning for building human-level artificial intelligence systems via tooling and RLOps.
AgileRL is creating the systems and tools that allow reinforcement learning development at scale. Reinforcement learning is capable of producing human-level artificial intelligence and we are only seeing the beginning of this emergence with the growing popularity of large language models. However, only a handful of companies have the resources to create these models. Projects require specialist engineers, cost companies millions, and take months and years to productionise.
To solve this, AgileRL is pioneering RLOps; MLOps for reinforcement learning. This comprises fast, easy-to-use tools for the entire development pipeline; simulation, training, deployment and monitoring. The team has built and released an MVP which speeds up model training and hyperparameter optimisation by an order of magnitude over popular reinforcement learning libraries, and is being adopted by enterprise businesses.
By introducing RLOps and simplifying the development cycle, AgileRL wants to democratise access to reinforcement learning for building advanced artificial intelligence systems.