Computation is at a crossroads

Exciting new developments around the Internet of Things, Big Data, autonomous vehicles, and Artificial Intelligence highlight how our approach to computation must fundamentally change.

Present-day computers are enormously successful at a huge range of tasks that require fast number-crunching. They are excellent, and getting better, at complex things like image recognition, autonomous decision-making, and interacting with humans in an intuitive way. We have seen remarkable achievements from modern Machine Learning systems. However, these achievements come with a very significant energy cost. While the human brain works happily on 20 Watts of power, modern Machine Learning systems can consume tens of kilowatts and only perform a fraction of the tasks our brains are capable of. This is largely because Machine Learning algorithms use conventional digital computer architectures to simulate the analogue behaviour of biological systems.

In order to properly exploit the potential of machine learning to improve our lives we need a step change in computer architectures to radically reduce their power consumption for these new tasks.

Silicon-based resistive random access memory technology has the potential to become the backbone for the next generation of computer memory

The Missing Element

Intrinsic is a UCL spinout company, established to commercialise the novel memristive RRAM devices developed by Prof Tony Kenyon and Dr. Adnan Mehonic in UCL Electronic and Electrical Engineering.

The research that led to the demonstration of the RRAM devices was supported by EPSRC, UCL Business Proof of Concept funding. The team are also supported by UCL Technology Fund as recipients of funding through their Proof of Concept early stage investment.

UCL Technology Fund

Dr Mark Dickinson – CEO

Prior to joining Intrinsic Mark held a number of senior and executive positions at leading semiconductor companies and brings a deep experience in IP licensing and development. He was most recently at Imagination Technologies where he was Executive Vice President responsible for the circa $100m PowerVR business unit. Prior to Imagination Mark was at ARM as VP/General Manager of the Mali GPU/multimedia business unit. Mark also spent many years as a vice president at Altera, an FPGA company now owned by Intel, where he built up the UK R&D team as well as running a world-wide system IP development group.

Mark’s technical background spans a wide range of semiconductor and electronics technologies and applications including artificial intelligence, graphics, multimedia, automotive and communications. Mark has a PhD in electronics (wireless communications) from Birmingham University and a degree in Physics from Oxford University.

Professor Tony Kenyon – Chief Scientific Officer

Tony Kenyon is the Vice Dean (Research) for the Faculty of Engineering Sciences and Professor of Nanoelectronic & Nanophotonic Materials in the Department of Electronic & Electrical Engineering. His research interests include resistance switching; RRAM; neuromorphic devices; nanostructured materials for electronics and photonics; silicon photonics, and self-assembled nanoscale systems.

Professor Kenyon is a Fellow of both the Institute of Physics and the IET, a Senior Member of the IEEE, a member of the EPSRC ICT Strategic Advisory Team, and serves on the Executive Committee of the European Materials Research Society. He is the author of more than 100 peer-reviewed publications, and regularly gives invited talks at major international conferences.

Dr Adnan Mehonic – Chief Technical Officer

Adnan Mehonic is the Research Fellow of Royal Academy of Engineering at the Department of Electronic & Electrical Engineering, UCL. To date, he has authored more than 20 journal publications, a book chapter, and over 50 international conference proceedings (including five invited talks). His research includes RRAMs, novel hardware for machine learning, neuromorphic architectures and electronic nanomaterials. He has been a member of the technical programme committee for multiple international conferences, he serves as a reviewer for various materials, applied physics and engineering journals and he is frequently involved in reviewing international research grants.

He graduated in Electrical and Electronic Engineering from the University of Sarajevo, Bosnia in 2009 and was awarded the Golden Award Badge for the best student of the 2006-2009 cohort (~200 students). He received the MSc (Distinction) and PhD degrees in nanotechnology and electronic engineering from the University College London in 2010 and 2014, respectively, receiving the Oxford Instruments prize (the best MSc project) and being selected among the top 3 PhD graduated students in 2013/14 in E&E Department. In 2017, he has been awarded a highly prestigious 5-year Royal Academy of Engineering Research Fellowship (seven applicants are awarded annually from more than 130 applicants in the UK). He received the “One to Watch 2015” award from UCL Enterprise for UCL’s most innovative staff.

Dr Wing Ng – Staff Scientist

Dr Wing Ng is a senior scientist at Intrinsic Semiconductors Technologies and a senior research fellow at Department of Electronic and Electrical Engineering, University College London. He holds a MSc in Physics from Durham University, a MSc in Optics and Photonics from Imperial College London and a PhD in Semiconductor Physics from University of Sheffield. His PhD work was mostly carried out at the National Centre for III-V Technologies, and his main achievements include development of the first broadband quantum cascade laser operating at room temperature. Wing has extensive experience in design and fabrication of semiconductor electronic and optoelectronic structures and devices at micro and nanoscales.

After working at a UK based scientific instrumentation company as an application engineer for several years, Wing moved to his current position at UCL and Intrinsic where he develops and fabricates novel metal oxide-based resistance memory devices. In the course of his work he has developed a novel fast electron beam lithography technique improving the patterning time by over an order of magnitude compared to conventional methods. He has published over 20 peer-reviewed papers in high impact journals and over 30 international conference proceedings. Wing is also a patent holder for a resistance memory technology developed at UCL.