Neuro-symbolic ai
Building the Future of Scientific Discovery
Our mission to create the world's first AI Research Factory, combining neuro-symbolic AI with advanced research automation to accelerate breakthrough discoveries.
Our vision
Designing Domain Invariant Problem Solvers
The AI Research Factory integrates symbolic reasoning with neural capabilities, enabling multi-step problem decomposition and autonomous research workflows powered by domain-invariant problem solvers.
Our framework orchestrates specialized research agents through traceable computational graphs, where each node operates as a contained, verifiable unit. This architecture enables complex workflows to emerge from simple, reliable components while ensuring the transparency and reproducibility essential to scientific discovery.
Areas of Research
Research Focus
Integrating symbolic knowledge with machine learning capabilities to advance the foundations of artificial intelligence.
Timeline
Shaping the future of AI
Software 1.0
Refers to classical programming, where people write code manually, defining algorithms, rules, and logic that software must follow. It’s the foundation of how most software has been built traditionally.
Software 2.0
Represents differentiable programming, where neural networks and machine learning algorithms learn from data. Instead of explicit instructions, these systems optimize themselves by learning patterns, allowing for smarter and more adaptable software.
Software 3.0
The next leap in AI, blending neuro-symbolic programming with reasoning capabilities. This stage builds self-improving algorithms that not only learn from data but also reason and make decisions autonomously.
We aim to standardize how algorithms interact with the world, advancing the field toward fully autonomous AI solutions capable of understanding and improving themselves over time.
Publications