Quantum Machine Learning
How quantum computation accelerates machine learning workflows: faster optimisation, improved data encoding, and quantum-enhanced gradient methods. Current state of hardware and what is practically achievable today.
Quantum Technologies
Quantum Machine Learning and AI
Expert lectures on Quantum Machine Learning and its intersection with artificial intelligence. Covers quantum neural networks, transformers, generative models, and practical case studies from defence, finance, and security.
What the Lectures Cover
Each lecture runs approximately 20 minutes. Delivered by researchers and engineers applying quantum computation to existing AI problems. Recordings are available in the member archive alongside lectures on all other quantum subjects.
Quantum Neural Networks
Variational quantum circuits as analogues to classical neural networks. Architecture differences, training approaches, and the current gap between theoretical promise and hardware reality.
Quantum Transformers
Applying quantum computation to transformer architectures. Potential advantages in attention mechanism computation and what quantum speedup in large language model training would require.
Quantum-Assisted Generative AI
Quantum-assisted generative adversarial networks and variational approaches to generative modelling. Current research directions and near-term application candidates.
Quantum AI in Defence and Security
Applications of quantum-enhanced AI in threat detection, cryptanalysis, and signals intelligence. Industry case studies from UAE, finance, and defence sectors.
QAI Companies and Vendors
The organisations building quantum AI capabilities: hardware providers, software stack developers, and application-layer companies. How to evaluate quantum AI claims and timelines.
Recent Expert Lectures
Speakers include academics, founders, and senior practitioners from quantum computing, AI, and applied security. All lectures are included in your QSECDEF membership.
Sreekuttan Lalimol Sukesh
Co-Founder and CEO, Bloq Quantum
How Global Businesses Can Start with Quantum Without the Headache
Paulo A. Viana
Chief Scientist, Quant.Bond
Quantum Certification On-Chain
Yury Kurochkin
Lead Researcher, Technology Innovation Institute
New Challenges in Quantum Communications: Applied Use Cases in the UAE
Bernard Soo
Co-Founder and CCO, Aires Applied Tech
Quantum Technology in the Financial Industry and Private Banking
Khrystyna Gnatenko
Professor of Theoretical Physics
Detecting Graph Characteristics Using Quantum Programming
Xenia Bogomolec
CEO, Quant-X Security & Coding GmbH
Post-Quantum Security for Distributed Systems
Quantum Computing Applied to AI
Classical AI is computationally expensive. Training large models requires significant energy and time. Quantum computing offers potential advantages in specific components of that process: optimisation problems, matrix operations, and sampling tasks that are tractable on quantum hardware before classical computers.
The near-term picture is more constrained. Current quantum hardware has limited qubit counts and high error rates. Quantum ML advantages are demonstrated in research settings but not yet at production scale. The QSECDEF lecture series presents both the genuine promise and the honest current limitations, from researchers and practitioners who work on these systems directly.
The intersection of QAI and security is particularly relevant for QSECDEF members. Quantum-enhanced AI may accelerate cryptanalysis. Understanding that trajectory is important for organisations planning long-term cryptographic strategy.
Access the Full QAI Archive
All quantum AI and machine learning lectures are included in QSECDEF membership. Individual lifetime membership starts at $149. Corporate access for up to 10 users from $499 per year.