GAIALAB systemically safe AI
World Models · Neurosymbolic AI · Physical Simulation Est. Meschede · Germany

AI for Fusion & Complex Physical Systems

Supporting researchers, engineers, and interdisciplinary builders leveraging world modeling, neurosymbolic AI, and physical simulation to solve critical bottlenecks in next-generation nuclear fusion and complex real-world physics.

Technical Vision

Verifiable, high-assurance intelligence for real-world physics.

Some of the hardest technical challenges on earth.

Controlling high-beta plasma, mastering extreme thermodynamic regimes, and navigating non-linear physical systems represent some of the hardest technical challenges on earth. Traditional deep learning alone lacks the causal reasoning and strict safety guarantees required for real-world physical deployment, while classic physics models struggle to operate at the speed of real-time control.

GAIA Lab develops next-generation AI architectures that bridge this gap. By combining world models capable of internalizing complex environment dynamics with neurosymbolic AI that embeds explicit physical laws, logic, and safety constraints directly into neural networks, we aim to solve long-standing bottlenecks in nuclear fusion. Our goal is to enable verifiable, high-assurance intelligence capable of modeling, predicting, and controlling complex real-world physics—accelerating the path toward safe, abundant fusion energy.

Alisa34 · BMBF

≈ 2.1 M€

Approved and funded by the BMBF over the course of three years. Project start 02/2025.

KIKO · BMBF

≈ 2 M€

Approved and funded by the BMBF over the course of three years. Project start 03/2025.

Compute & energy

1,000,000× less

Up to a millionfold reduction in computational power/energy for training and operation.

Selected publications

08

Across arXiv, Zenodo and conference venues, 2024–2026.

Focus areas

GAIA-enabled systemically safe AI.

01 / Active Inference

Model-based, real-time, explainable risk analysis based on Active Inference

  • First-principles metric “fully loads” uncertainty and risk
  • Stakeholders can see likely system trajectories, given current knowledge
  • Modelers can target effort towards most impactful model improvements

How GAIA works

From a repository of world models to a bounded knowledge economy.

Five stages

  1. 01

    The Repository

    A Github for world models bootstrapped then growing over time

  2. 02

    Protocol

    Defining the rules for communication, updating and behaviour of world models

  3. 03

    Decision Support

    Extract information from the GAIA world models for important decisions in your organization

  4. 04

    Convergence

    Akin to Darwinian processes models compete between each other for top score wrt. quality, accuracy and transparency

  5. 05

    Knowledge economy

    The knowledge explosion ensues driven by increasing capabilities within a safe space bounded by GAIA

Affiliations & partners

  • Q.ANT
  • Q.ANT
  • Universität Stuttgart
  • FuseNet
  • Lazy Dynamics
  • BMBF
  • SPAR

Contact

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