Consulting / Artificial Intelligence
Six specialist workshops covering PQC migration for AI model weights and training infrastructure, quantum threats to federated learning, quantum machine learning capabilities, and cryptographic security for AI inference APIs. Delivered by practitioners with direct AI and quantum technology experience.
AI systems introduce new cryptographic attack surfaces: model weights represent valuable intellectual property, training infrastructure handles sensitive data, and inference APIs carry long-lived authentication tokens. Each presents a distinct quantum risk profile.
All sessions are delivered by subject-matter experts with direct experience in AI systems and quantum technology. Each session is fully vendor-agnostic and configurable to your organisation's technical level and governance requirements.
Five structured sessions covering the highest-impact quantum applications for AI and machine learning teams. Each session combines technical depth with operational context.
Covers the cryptographic exposure of large language model weights, training checkpoint files, and distributed training cluster communications. Addresses NIST PQC standards for securing model artefact storage, cryptographic signing of model versions, and post-quantum secure NCCL and MPI collective communications in GPU training clusters. Aimed at MLOps engineers, AI platform security teams, and AI governance leads.
Addresses the quantum cryptographic exposure in federated learning frameworks including TensorFlow Federated, PySyft, and FATE. Covers secure aggregation protocol vulnerabilities, differential privacy mechanisms under quantum attack, and PQC migration for homomorphic encryption schemes used in privacy-preserving machine learning. Aimed at AI researchers, data privacy engineers, and organisations deploying federated AI across sensitive data.
Technical workshop examining the state of quantum machine learning: variational quantum circuits, quantum kernel methods, quantum neural networks, and quantum-enhanced optimisation for ML training. Separates credible near-term use cases from speculative long-term claims, examines performance comparisons with classical ML on benchmark tasks, and identifies where quantum ML offers genuine advantage versus marketing noise.
Covers the quantum cryptographic exposure of AI inference APIs, model serving infrastructure, and LLM deployment pipelines. Addresses TLS security for AI API endpoints, authentication token cryptography, and the specific risks of long-lived API keys used in agentic AI systems. Covers PQC migration for AI-as-a-service architectures and the intersection with OWASP LLM Top 10 security considerations.
Examines how quantum computing may accelerate specific bottlenecks in AI model training: hyperparameter search, neural architecture search, combinatorial feature selection, and attention mechanism optimisation. Covers realistic timelines for quantum advantage in AI training tasks, current hardware constraints relative to GPU cluster scales, and how to structure a quantum-AI research agenda for an enterprise AI team.
Advanced briefings for executive and governance audiences. These sessions address investment sequencing, regulatory intersections, and board-level AI risk governance in depth.
Executive briefing for CISOs, CTOs, and AI governance leaders at enterprises with significant AI investment. Covers the dual agenda: quantum computing as an AI capability accelerator alongside quantum security as a critical protection requirement for AI assets. Addresses emerging EU AI Act intersections with quantum security obligations, board-level AI risk governance, and investment prioritisation for quantum-ready AI infrastructure.
Learn MoreAll tiers include access to the full lecture archive, weekly webinars, and the member directory.
For professionals working in quantum computing, post-quantum cryptography, or adjacent security fields.
For organisations building, deploying, or evaluating quantum-safe solutions across their supply chain.
For recognised specialists contributing lectures, advisory work, or research to the QSECDEF community.
Sessions are configured around your team's technical level and operational priorities. Get in touch to discuss requirements and schedule a date.
