ICHEC adds fifth company to EUROCC SME Accelerator

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The Irish Centre for High-End Computing (ICHEC) has announced details of a fifth company to join the EuroHPC Competency Centre SME Accelerator. Fathom is a digital transformation company which has been working in partnership with NUI Galway to develop a platform for predicting seaweed biomass, a potential source of food for humans as well as cattle. 

ICHEC will assist Fathom access expertise in the area of machine learning, earth observation and multi-sensor data fusion to improve the accuracy of its existing model in addition to supporting further research in adapting the model for additional seaweed species. 

Launched in Dublin in September 2020, the EuroCC_Ireland Competence Centre is one of 33 centres across Europe operating under the EuroHPC project. The focus of these centres is to upskill SMEs in AI and HPC as well as provide access to academics to European exascale and Supercomputing resources.

Commenting on the EuroCC_Ireland success in attracting SMEs, Public Sector Liaison & Business Development Manager at ICHEC, Peter Woods said; ‘Since we launched the accelerator, we have seen strong demand for skills development in HPC, AI and ML from organisations across diverse domains. In addition to this collaborative work with Fathom in the field of marine agrifood, we have companies from the Agriculture, Construction, Earth Observation  and Bioengineering sectors. The range and caliber of the projects is superb and we are looking forward to working with all of the project leads. By working with ICHEC, the companies involved are ensuring that their projects are harnessing the benefits provided by cutting-edge technologies in the field of artificial intelligence (AI), multi-sensor remote sensing data sets, and high-performance computing (HPC).’

The companies who have signed up for the accelerator are:

Fathom:  This project will build on work that has already commenced to develop a platform for predicting Seaweed biomass powered by Earth Observation data sets. The EuroCC will provide support in the areas of machine learning, multi-sensor data fusion and model enhancement for improving the accuracy of the existing model. The support also aims to focus on the application of the model at a regional scale and the potential inclusion of other seaweed species.

Telenostic: Telenostic is using machine learning and AI in Agriculture for the detection of parasite infection in bovine herds. This project consists of the development of a post-detection filtering of AI object detection results in order to improve prediction accuracy by further analysing results and filtering out likely false positives. Size, shape and aspect ratio of detected parasite eggs will be measured, and a filtering process will classify these as genuine-looking detections or false positives, as well as use the known properties of the various species to infer the full size of partially detected eggs on an image’s edge.

Evercam: Evercam provides advanced camera software solutions for the construction industry. Evercam is working with the SME Accelerator to further enhance their software solutions by applying novel Machine Learning techniques to a large volume of video streams. HPC techniques and infrastructure will be used to speed up the development, training and deployment phases of Machine Learning models, which will allow customers to perform better analysis on the most pressing challenges on the construction sites.

The SME accelerator is assisting Evercam to develop a next-generation system for communicating with top-notch video/image analytics and an added layer of visualisation to enable 3D/4D volumetric construction site simulation. We want to combine easily retrievable & searchable recording, live streaming, and BIM integration, with multiple-camera volumetric view allowing the users for seamless and interactive ability to move virtually around the construction site, while still keeping low latency and high frame rates.

Ubotica: Ubotica specialises in solutions for extracting meaning from visual data at the source. Building on the successful completion of the Space Networks project which is part of a groundbreaking program in which state-of-the-art Deep Learning technology for the in-orbit processing of Earth Observation data is being deployed on a European satellite for the first time. The SME Accelerator will assist Ubotica in identifying and testing of use cases for commercial applications which can use the platform once developed.

Nuritas: Nuritas is a Life Sciences company specialising in AI and Peptidomics. The planned work aims to simulate aspects of chemistry on a Quantum Computer. Quantum Computers are an emerging technology that work in a fundamentally different way to existing forms of computer. This technology is so new that before we proceed with a full Innovation Partnership we need to first investigate if it is possible to encode our intended problem in a satisfactory way. In this Feasibility Study we will investigate:

  • How we can encode the problem in quantum computing.
  • Can we formulate a problem that we can solve in the quantum computer using the available problem encodings.
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