Neuromorphic Computing
Neuromorphic Architecture Neuromorphic computing represents the third generation of neural networks, is biologically plausible and is fundamentally different from conventional neural networks and related AI accelerators. Compared to conventional Artificial Neural Networks (ANNs), they can provide higher computational power and…
Explainable AI
Many neural network based artificial intelligence applications are effectively “black boxes” that lack the ability to “explain” the reasoning behind the results they provide. They can make important decisions without being able to provide detailed information regarding the reasoning that…
Healthcare
Clinical Decision Support Systems Cyceer’s Neuromorphic Framework (NF) can be used to synthesize clinical decision support systems (CDSS) for a diverse range of healthcare disciplines such as the examination of real-time data from monitoring devices, analyses of patient and family…
Robotics & Autonomous Systems
Factories Of The Future Factories of the future will be very different to the traditional labour intensive manufacturing plants of the past. Advances in High Performance Computing (HPC), data analytics and automation will transform the manufacturing process into a more…
Machine Learning
Autonomous learning from one or several examples remains a key challenge in Machine Learning (ML). Despite recent progress in related fields such as vision and language, deep learning methodologies do not provide a satisfactory solution for learning new concepts rapidly…
Bioinformatics
Our novel knowledge extraction and neuromorphic computing methods enable more detailed models to be created, simulated and analysed allowing a better understand biological processes. Cyceera’s Neuromorhpic Framework (NF) facilitates the creation and advancement of databases, algorithms, computational and statistical techniques,…