This artificial intelligence makes it possible to construct, To form and operate AI agents in simulated or real environments shared with humans. Cogment is an open source software designed to facilitate the ongoing training of mixed teams of humans and AI. The software integrates seamlessly with existing tools, such as PyTorch, Open AI Gym, and TensorFlow, offering broad compatibility for developers. By orchestrating intelligence ecosystems, Cogment makes the most of human capabilities and AI under human supervision, maximizing compliance and performance in a modular framework. Users can train their agents effectively with less data, real-time adaptation, and faster training processes while strengthening the trust. The transition from simulation to real environments is smooth, ensuring safe design and gradual deployment. Cogment is therefore essential for researchers and developers requiring high performance and flexibility in AI training in collaborative or competitive contexts.
In an age where rapid adaptation is crucial, functionality allows for the continuous training of artificial intelligences and humans in cooperation. This dynamic ensures less data needed for learning, a capacity to react in real time and an accelerated pace of training. Ideal for businesses looking to strengthen mutual trust between people and intelligent agents.
This ability to orchestrate combines the best of human skills and AI capabilities under careful human supervision. Modular approaches reduce the use of computing capacity while facilitating validation, thereby optimizing the compliance and performance of hybrid AI systems. It is an effective solution for businesses looking for agility and savings in IT resources.
The transition from simulation to real environments is seamless through a secure and simplified design and training process in simulated environments. Progressive integration into reality, with the use of digital twins and numerical simulations, allows companies to test and deploy innovations with minimal risk, ensuring optimal continuity between development and deployment.
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