Machine learning technology will be used to make the additive manufacturing (AM) process of metallic alloys for aerospace cheaper and faster, encouraging the production of lightweight, energy-efficient aircraft to support net-zero targets for aviation.
Intellegens is a spin-out from the University of Cambridge with a unique Artificial Intelligence (AI) toolset that can train deep neural networks from sparse or noisy data. Their mission is to help their clients accelerate innovation by using their unique deep learning solutions to extract valuable information from existing processes and data. The technique, created at the Cavendish Laboratory, is encapsulated in Intellegens’ first commercial product, Alchemite™ . The cutting-edge deep learning algorithms that Alchemite™ is based on can see correlations between all available parameters, both inputs and outputs, in fragmented, unstructured, corrupt or even noisy datasets. The result is accurate models that can predict missing values, find errors and optimise target properties. Capable of working with data that is as little as 0.05% complete, Alchemite™ can unravel data problems that are not accessible to traditional deep learning approaches. Suitable for deployment across any kind of numeric dataset, Alchemite™ is delivering ground breaking solutions in drug discovery, advanced materials, patient analytics and predictive maintenance – enabling organisations to break through data analysis bottlenecks, reduce the amount of time and money spent on research, and support better, faster decision-making.
added by Ben Pellegrini 5 min Read
Intellegens has received funding from Innovate UK to model COVID-19 data and improve the management of future coronavirus outbreaks and other infectious diseases. The tool, which will be based on Intellegens' unique deep-learning algorithm Alchemite™, will help understand how policy changes might impact outcomes, helping inform decision-making.added by Ben Pellegrini 2 min Read
Intellegens and Optibrium achieve further success in Open Source Malaria initiative with in vitro validation of in silico generated compound
StarDrop™ and Augmented Chemistry™ prove a powerful combination in AI-guided design (Alchemite™) and validation of novel antimalarial drug candidates. In silico designed compound demonstrates potency against pfATP4 protein target in malaria parasite.added by Ben Pellegrini 2 min Read
A collaboration between the University of Cambridge, A*STAR and Nanyang Technological University in Singapore, assessed methods for predicting EV battery states and revealed that a data-driven machine learning model offers the most accurate predictions for state of charge and health.added by Ben Pellegrini 3 min Read
Deep Learning Tool Enables the Identification of Alkanes For Lubricants With Superior Physical Properties
Deep learning tool Alchemite™ accurately predicts the physical properties of alkanes and will facilitate the development of new lubricants.added by Ben Pellegrini 2 min Read