Accelerating The Next Generation of AI Powered Devices
Mignon has developed a novel edge AI accelerator architecture which is uniquely underpinned by propositional logic-based AI, allowing for explainable decisions.
Mignon is an advanced AI accelerator architecture design technology that is revolutionising the field of machine learning. Its novel approach to AI has resulted in significant direct performance improvements, with Mignon chipsets already demonstrating up to ~10,000x improvements in on-chip inference.
This is a major breakthrough, as Mignon is the first architecture to enable the potential for on-chip training at scale.
One of the major challenges with traditional neural network-based models is their resource-intensive nature. As models become more complex, so too does the resource requirement. Mignon’s architecture, based on propositional logic, requires significantly fewer resources to solve AI problems, meaning that Mignon can deliver intelligent compute on devices with minimal energy usage and with little or no internet coverage.
Mignon’s technology also allows for explainable Artificial Intelligence from the chip level upwards. Neural Network-based approaches can make inferences and decisions within an unintelligible ‘black-box’. With Mignon-based chips, decisions can be interpreted and explained so that decisions can be understood.
As demand for AI continues to increase, Mignon is poised to play a major role in creating a new world of powerful AI-enabled devices with explainable decisions for use in critical industries, unlike other chip architectures.
Mignon is an exciting technology that is poised to make a significant impact in the future Artificial Intelligence.
meet the team
Professor Alex Yakovlev
CSO & Inventor
Professor of Computer System Design, Head of the µSystems Research Group at the University of Newcastle and Fellow of the Royal Academy of Engineering.
Serial Tech Entrepreneur in AI, HR & MarTech Founder. Start Up Operations Expert. CVC Capital Young Innovator for 2017. Cambridge Judge Business School alumnus.
Dr Rishad Shafik
CTO & Inventor
Reader in Electronic Systems within the µsystems Research Group at the Newcastle University. Research focusing on AI hardware design using learning automata and ultra low-power design
CFT's Work with Mignon
- Supported the Company in the Spin-Out Process
- Developed the commercial and operational plan
- Launched Seed Round
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