Sorted is designed to assist users in managing their time and tasks effectively using sophisticated AI algorithms. It offers features such as task prioritization, automation of routine planning, reminders, and intelligent scheduling. By analyzing users' habits and preferences, Sorted creates a dynamic plan that adapts as tasks are completed or deadlines approach, empowering users to focus on what truly matters.

DEf-MARL (Decentralized Execution Framework for Multi-Agent Reinforcement Learning) provides a robust infrastructure to execute and train cooperative agents without centralized controllers. It leverages peer-to-peer communication protocols to share policies and observations among agents, enabling coordination through local interactions. The framework integrates seamlessly with common RL toolkits like PyTorch and TensorFlow, offering customizable environment wrappers, distributed rollout collection, and gradient synchronization modules. Users can define agent-specific observation spaces, reward functions, and communication topologies. DEf-MARL supports dynamic agent addition and removal at runtime, fault-tolerant execution by replicating critical state across nodes, and adaptive communication scheduling to balance exploration and exploitation. It accelerates training by parallelizing environment simulations and reducing central bottlenecks, making it suitable for large-scale MARL research and industrial simulations.

Molly is an advanced AI agent that serves as your personal assistant. It helps manage your schedule by organizing tasks, setting reminders, and facilitating meetings. With its smart natural language processing, you can communicate with Molly in conversational language, making it easy to delegate tasks and receive updates. Whether you're running late or need to reschedule meetings, Molly adapts to your needs, ensuring you remain productive.