AI: Hardware

Artificial Intelligence is transforming numerous industries, and the hardware that accelerates AI models and tools is at the heart of this revolution. At Mewburn Ellis, we specialise in protecting innovations in AI hardware, ensuring our clients maintain their competitive edge in a rapidly evolving industry which encompasses:


AI Hardware:

  • Accelerators and Processors: Enhancing computational speed and efficiency with specialised AI chips and processors.
  • Edge Computing Devices: Bringing AI capabilities closer to data sources for real-time processing and decision-making.
  • Neuromorphic Computing: Mimicking the human brain to improve efficiency and performance of AI applications.

AI Model Optimisation:

  • Hardware-Software Integration: Improving performance through seamless integration of AI models with hardware.
  • Energy Efficiency: Reducing power consumption while maintaining high performance with advanced hardware design.
  • Scalability Solutions: Enhancing the scalability of AI models with innovative hardware solutions.

Work in these fields drives computational efficiencies, enhances performance, and supports innovation for our clients. The strategic use of AI hardware provides a significant market advantage, making the protection of these innovations crucial. We understand the importance of securing IP quickly due to the fast-paced uptake of this technology, and its ubiquitous applicability.

Our team comprises skilled advocates with extensive experience preparing applications and arguing for patentability at the UKIPO and EPO. We are committed to providing expert representation to ensure our clients' innovations are well-protected and their competitive edge is maintained.

Our team

Tom Furnival circle-1

Tom Furnival

Tom has a particular interest in transport and logistics, AI hardware as well as health/bioinformatics. He has a wealth of hands-on experience in the AI space, having worked with companies across the technical spectrum in areas such as multi modal threat detection, neurological assessments, and video analysis.

Tom works with inventors during the invention capture process to ensure that the resulting patent application is robust and suitable across jurisdictions. He also regularly assists foreign attorneys to obtain European protection for AI inventions. 

Emma Graham - Circle

Emma Graham

Emma focuses on AI as applied to e commerce, educational tools, digital health, internet of things, as well as optics/photonics. She recognises the fast moving nature of software and the need to obtain protection quickly. She takes a proactive approach in prosecution including arranging examiner interviews and regularly advises upon acceleration mechanisms, both locally in the UK and Europe as well as across global portfolios. Emma has a particular focus on drafting applications designed to achieve the best protection possible in both Europe and the US; a skill that often requires just the right amount of compromise. In 2014 she spent time on secondment working in Silicon Valley, giving her a unique perspective of the challenges that US applicants face when patenting in Europe.

rebecca frith-1 (2)-1

Rebecca Frith

Rebecca has a particular interest in transport/logistics and AI hardware as well as electronic design. Before joining Mewburn Ellis, Rebecca worked as an electronics and firmware engineer for a technology consultancy where she undertook a variety of research and development projects for the defence and aerospace industries. Rebecca has a breadth of practical experience in FPGA design, analogue and digital electronics, radar modelling, and radio communications. Additionally, Rebecca has significant experience in applying AI/ML for signal processing, computer vision and data security applications. She has practical experience using Caffe, Pytorch, Keras, and Tensorflow to build and test neural networks such as CNNs, GANs and LSTMs. 

Alessio

Alessio Incitti

Alessio maintains state-of-the-art knowledge in high-growth areas of applied artificial intelligence, including robotics, natural language processing, network security, embedded systems, and AI agents. He also has an in-depth expertise in custom hardware, such as programmable logic devices (e.g. FPGAs), and other high-performance hardware for optimised neural network implementations.

Alessio has an MEng in Computing from Imperial College London. In addition to solid computer engineering foundations, he gained exposure and practical experience in various areas of knowledge representation, AI planning, machine learning, and high-performance computing. His final year research project investigated optimisation techniques for radiation therapy simulation on FPGA for use in adaptive radiotherapy. Additionally, Alessio worked as a software developer at a cyber security company specialising in military-grade encryption solutions for everyday mobile devices.

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