AI innovation in the supply chain of consumer packaged-goods for recognising objects in retail execution, supply chain management and smart factories: using novel diffusion-based optimisation algorithms and diffusion-based generative models

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Retail is a stepping stone on our path to becoming _a "plug-and-play" Computer Vision platform propelled by a synthetic data generation engine_ that can be adapted to multiple use cases & industries. In the future, we strive to become _a world-leading provider of computer vision as a service_ to the many use cases that exist across the supply chain of consumer product goods, i.e product sorting in waste management and recycling, product recognition in autonomous checkout stores, or inventory visibility in warehouses.Using the synergy between a team of experts at the University of Edinburgh and the South Korean team, we will be the pioneers in the creation of computer vision models that offer absolute guarantees for their performance. Our primary objective is to attain cross-domain generalisability for our platform, enabling us to streamline model development across various domains by harnessing our expertise in synthetic data generation. This approach will result in fewer models required to serve multiple clients efficiently.At Neurolabs, we are committed to democratising the field of computer vision, making sure that every small and medium-sized enterprise can harness the power of this transformative technology. To achieve this, we are open sourcing a selection of the groundbreaking algorithms developed throughout this project, incorporating them into optimisation packages. This strategic move aims to expand the applicability of these algorithms beyond Neurolabs' proprietary models, fostering their adoption across a wider range of applications.