Mewburn - Artificial Intelligence

Quantum advantage provided by the fundamental quantum properties superposition, entanglement and the quantum parallelism that they provide, is revolutionising the way in which AI is delivered.

Quantum machine learning utilizes qubits and quantum operations to improve computational speed. This is especially beneficial to machine learning algorithms which often process immense quantities of data. Quantum-assisted machine learning uses hybrid methods that involve both classical and quantum processing in which computationally difficult tasks are reserved to a quantum processing unit (QPU) where they can be executed more quickly.

Here at Mewburn Ellis, we work on patent portfolios for a wide range of quantum technologies including quantum-assisted AI and machine learning. We regularly advise our clients in relation to the use of quantum algorithms for quantum-assisted computing.

Our team

Andrew Fearnside, Senior Associate

Andrew has a particular interest in quantum algorithms. He handles patent applications for quantum technologies across the full spectrum of this technology sector including drafting and prosecuting patent applications for quantum computing, such as quantum information processing circuits, quantum algorithms, and quantum error correction, as well as inventions relating to AI, such as classical machine-learning algorithms and those employing quantum information.

Johannes Biniok, Senior Associate

Johannes has a special focus on quantum algorithms. His undergraduate and postgraduate education focussed on quantum physics within the context of quantum foundations and quantum information, with a particular interest in the characterisation of information extractable from quantum states. His academic background is complemented with practical experience prosecuting consumer technology implementing AI/ML, such as cameras and televisions.

Amelia Sloan, Patent Technical Assistant

Amelia is a technical assistant in our AI team with particular expertise in the application of AI to digital security and quantum technologies. She has an MSci in mathematics from Imperial College London, and has experience prosecuting AI patents in relation to med-tech. While personally specialising in topology, her degree covers a wide range of subject areas, with knowledge in machine learning and number theory being especially useful in relation to cryptography and digital security.

Luke Jones, Senior Associate

Luke works across a broad range of software, electronics and communication technologies. He has experience of drafting and prosecuting patent applications in the UK and at the EPO, as well as coordinating patent portfolio management across many multinational territories. He additionally has experience of freedom to operate (FTO) and patent landscape analysis. He also has experience of managing and delivering corporate IP training content.

Luke has a first class undergraduate degree in Physics from the University of Liverpool and a master’s degree in Biophotonics from Cardiff University.

He joined the patent attorney profession in 2016 at another large private practice firm. He qualified as a UK Chartered Patent attorney and as a European Patent Attorney in 2021. He additionally has in-house experience working as a Patent Attorney at a multinational semiconductor manufacturing company.

Simon Eisenmann, Patent Technical Assistant

Simon has extensive experience in robotics, AI, and autonomous systems, covering both research and applied development. Before joining Mewburn Ellis, he worked as an AI Software Engineer at a startup developing autonomous driving solutions for commercial vehicles in industries like agriculture, mining, and logistics. Part of his work focused on developing, optimizing, and deploying deep learning models using Python (including PyTorch and related libraries) and C++. Additionally, he worked with the Robot Operating System (ROS2). Previously, Simon gained industrial automation experience as a working student at a large, international company. With this multidisciplinary background, he offers a broad and practical perspective on the evolving applications of artificial intelligence across various sectors.

Case study: Quantum tech

We supported an international manufacturer of NMR systems in growing a strong patent portfolio related to innovations in NMR image classification.

Using a programmable quantum annealing device including a Restricted Boltzmann Machine, the Restricted Boltzmann Machine was trained to act as a classifier of image data and used to initialize a neural network for image classification thereby providing a quantum-enhanced system for use in classification of NMR images.

Read our blogs

AI agents – future colleagues?

by Emily Lloyd

The onset of AI tools is leading to drastic changes in the workplace with more and more companies outsourcing work to AI. Companies such as Duolingo and Shopify have recently positioned themselves as ...

AI’s Powerhouse: The Hardware Behind the Intelligence

by Luke Jones

As AI models grow ever larger and more powerful, the conversation often focuses on new model architectures, parameter counts, and dataset sizes. But another equally critical part of the AI revolution ...

BluMaiden: Pioneering AI-Driven Precision in Immunotherapy Response Prediction

by Eliot Ward

BluMaiden uses AI and microbiome insights to boost immunotherapy prediction and speed up drug discovery.

FORWARD MAGAZINE

Mewburn Ellis Forward is a biannual publication that celebrates the best of innovation and exploration. Through its pages we hope to inform and entertain, but also to encourage discussion about the most compelling developments taking place in the scientific and entrepreneurial world. Along the way, we’ll engage with the IP challenges that international organisations face every day.

Quantum AI