Verification of Neural Networks Against Convolutional Perturbations via Parameterised Kernels Brueckner, B., Lomuscio, A. (2025) Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI25)
Ensuring the robustness of neural networks against real world perturbations is critical for safe deployment, but existing techniques struggle. This state of the art method offers precision and scalability.
My First 30 Days as a Developer Evangelist at Safe Intelligence
Hello world, I’m Brain (yes 🧠) After six years of technical writing and public speaking in the AI space plus experience working in the financial industry as a data scientist, I have stepped into a new role as a Developer Evangelist at Safe Intelligence. I am here to...
AI Quality and Safety at the AI Engineer Summit
Building reliable systems with AI is hard. Events like the AI Engineer Summit are bringing these challenges to the forefront!
Scaling AI through more powerful validation and robustness
AI is fast becoming one of the building blocks of society and holds huge potential for productivity gains, automation and improvements to life. As techniques advance we make better models and enable new use-cases. However it remains much harder to validate that AI...
Safe Intelligence Raises £4M To Deliver Advanced Validation for Reliable AI
London, UK – Feb. 20, 2025 - Safe Intelligence, a pioneer in deep validation artificial intelligence (AI) systems, today announced that it has secured £4.15M in seed funding in an investment round led by Amadeus Capital Partners, with participation from new investor...