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The team at Agile Loop is building an adaptive action model for carrying out diversified actions on your operating systems

A foundation model combined with a reinforcement learning driven multi-agent system that can not only intelligently execute any task action on your computers based on human commands, but also self-improve over time with the help of memory-augmented neural networks.

Research Areas

Our research team focuses on an objective that is yet to be accomplished in the field of AI.
The problem we’re trying to solve focuses around an RL agent and how that agent can learn and train continuously on new and real-time inputs (unsupervised) as well retaining pre-existing labeled training dataset.