We’re building a system that represents domain knowledge as modular probabilistic models — making analysis rigorous and transparent. Users can connect these models flexibly into larger structures. The system enforces consistency across them, and propagates un…

We’re building a system that represents domain knowledge as modular probabilistic models, making analysis rigorous and transparent. Users can connect these models flexibly into larger structures; the system enforces consistency across them and propagates unce…

Hellas.AI is building a compiler for categorical deep learning to power decentralised, serverless AI. We're looking for an experienced Rust engineer. You must have demonstrated experience in designing and implementing BFT consensus protocols, ability to engag…

Traceoid is revisiting the theory that underlies machine learning. Our approach opens up the door towards scalable energy-based models, faster and cheaper training and inference and interpretability. If we succeed, our approach will mark a significant step fo…

We are working on making energy-based models (EBMs) viable by revisiting some of the math that underlies machine learning. Ideal candidate would understand how one goes about writing high perf code as well as be able to explain the concept of a Hamiltonian. I…

We are working on making energy-based models (EBMs) viable by revisiting some of the math that underlies machine learning. Here is what Yann LeCun had to say about EBMs https://x.com/ylecun/status/1380066315600343042 If you have background in any of these (o…