Pioneering the Future of Autonomous Agent Development

In 2023, Gartner’s AI Hype Cycle recognized First-Principles AI (FPAI) and Multiagent systems as innovative emerging technologies. These technologies represent the next major advancements in AI.

FPAI and multiagent systems together form a powerful concept, combining the fundamental principles of self-organization seen in biological systems with the collaborative capabilities of multiple AI agents. This synergy enables the creation of AI systems that are highly adaptive, context-aware, and capable of real-time problem-solving in uncertain environments. As these technologies continue to develop, they promise to unlock new potentials in AI, driving the evolution of intelligent systems and their applications in real-world scenarios.

Need

AI breakthroughs have always been critically supported by the availability of the right infrastructure and software engines. For instance, Computer Vision technology surged ahead through the availability of OpenCV , and more recently, the breakthroughs in Generative AI would not have been possible without services like Azure , AWS , HuggingFace , and the right toolboxes such as TensorFlow and PyTorch . Similarly, a powerful, user-friendly toolbox that supports the development of deployable autonomous agents is needed to propel innovative technologies from an innovation trigger to a mature and impactful stage. Lazy Dynamics is committed to providing the tools and knowledge that will enable a broad community to develop cutting-edge deployable autonomous agents.

Need

Vision

Supporting the need for adaptive agents immersed in their environments, Lazy Dynamics’ support stack focuses on four key aspects: smart data selection, low-power operation, real-time processing, and structural model adaptation. Departing from traditional dependencies on large datasets, we prioritize support for agents that extract maximum insights from minimal, relevant datasets selected on-the-fly. Our approach, inspired by Reactive Principles and the physics of the Free Energy Principle , ensures robust and efficient real-time processing. As outlined in a recent key research paper , this strategy guarantees that our agents are equipped to thrive throughout their lifespan in dynamic and unpredictable real-world environments.

Need

Mission

Lazy Dynamics is dedicated to fostering strong partnerships with experts and enthusiasts in the field of FPAI and multi-agent systems. We plan to leverage RxInfer to develop intelligent agents for real-world applications. Our immediate strategy involves initiating pilot projects with select clients to showcase the practicality and strengths of our approach. Concurrently, we intend to continue collaborating with the academic BIASlab research team to enhance the research version of RxInfer, nurturing a vibrant community of innovators and researchers in typical application fields such as immersive hearing technology, autonomous drones, safe robotics, and smart cities. This dual approach underscores our mission to advance technology through collaboration and practical innovation.

Need

Benefits

Lazy Dynamics is set to create RxInfer-Pro, a professional, licensed version of the toolbox designed for companies and individuals aiming to develop and deploy cutting-edge autonomous agents. This premium version will emphasize facilitating real-time inference and advanced lifelong structural adaptation for agents deployed in the field. We firmly believe that the true potential and optimization of agents can only be realized through direct field applications, where dynamic real-world data and conditions serve to test and refine the agents’ capabilities.

Timeline

Need

Lazy Dynamics Vision

In this short 3-minute video, Lazy Dynamics showcases a concept of what the future of autonomous agent development could look like.
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Technical Literature

  • Ismail Senoz, Thijs van de Laar, Dmitry Bagaev and Bert de Vries
    ‘Variational Message Passing and Local Constraint Manipulation in Factor Graphs’
    Entropy 2021
    https://doi.org/10.3390/e23070807
  • Dmitry Bagaev and Bert de Vries
    ‘Reactive Message Passing for Scalable Bayesian Inference’
    Scientific Programming 2023
    https://doi.org/10.1155/2023/6601690
  • Bert de Vries
    ‘Toward Design of Synthetic Active Inference Agents by Mere Mortals’
    4th International Workshop on Active Inference, Ghent (BE) 2023
    (https://arxiv.org/abs/2307.14145 )