Illumination estimation remains a pivotal challenge in image processing, particularly for robotics, where robust environmental perception is essential under varying lighting conditions. Traditional approaches, such as RGB histograms and GIST descriptors, often fail in complex scenarios due to their sensitivity to illumination changes. This study introduces a novel method utilizing the Wasserstein distance, rooted in optimal transport theory, to estimate illuminant and light direction in images. Experiments on diverse images indoor scenes, black-and-white photographs, and night images demonstrate the method's efficacy in detecting dominant light sources and estimating their directions, outperforming traditional statistical methods in complex lighting environments. The approach shows promise for applications in light source localization, image quality assessment, and object detection enhancement. Future research may explore adaptive thresholding and integrate gradient analysis to enhance accuracy, offering a scalable solution for real-world illumination challenges in robotics and beyond.

Seldon, a London-based data-centric machine learning operations (MLOps) platform, has secured a $20M Series B funding round led by new Portuguese investor Bright Pixel (former Sonae IM) with participation from existing investors AlbionVC (backed Ophelos), Cambridge Innovation Capital, and Amadeus Capital Partners. The funding will help Seldon expand its machine learning product's market fit and unlock enterprise-ready solutions based on open source. "AI is in everything, and Seldon is uniquely positioned to ensure a return on ML investment by providing robust, scalable, and secure infrastructure, pioneering a data-centric approach to ML pipelines, prioritizing team collaboration across the organization, and making sure teams can solve meaningful problems at scale by building trust in machine learning, even under the most intense regulatory conditions. "We're excited to bring together new investor Bright Pixel Capital and our existing partners, who believe in our vision and can help us become the trusted MLOps partner of any organization worldwide." Currently, numerous companies are investing a lot of resources into artificial intelligence, but they are having difficulty expanding their models for practical use. This is due to bottlenecks in team workflows, increased regulation and compliance restraints, a lack of trust in model outputs, and ensuring peak model performance are all top of mind for AI-powered enterprises. Here's where Seldon helps Data Scientists, ML Engineers, and other stakeholders in the company to quickly and efficiently adopt machine learning to address these challenges. Founded in 2014, Seldon is a data science and machine learning operations platform that aims to empower Data Scientists, ML Engineers, and MLOps teams to deploy, monitor, explain, and manage their ML models. With Seldon, organisations can minimise risk and drastically cut down time-to-value from their models. The UK company offers both an open-source framework, "Core," which focuses on model deployment, and an enterprise product, "Deploy Advanced," which builds on this functionality to power model monitoring, explainability, and management. Seldon claims that it has achieved a 400% YoY growth rate in its open-source frameworks installed and running since its series A in November 2020. "Seldon has differentiated itself by presenting a unique solution that can reduce the friction for users deploying and explaining ML models across any industry.

Seldon, a data-centric machine learning operations (MLOps) platform for the deployment, management, monitoring and explainability of machine learning (ML) models, announced a $20M Series B funding round today. The round was led by new investor Bright Pixel (former Sonae IM) with significant participation from existing investors AlbionVC, Cambridge Innovation Capital, and Amadeus Capital Partners. Organizations are investing heavily in AI but many are struggling to scale out their models in production due to bottlenecks in team workflows, increased regulation and compliance restraints, a lack of trust in model outputs, and ensuring peak model performance are all top of mind for AI-powered enterprises. Seldon empowers Data Scientists, ML Engineers and other business stakeholders to accelerate the adoption of machine learning to help solve these challenges with unprecedented efficiency. "AI is in everything, and Seldon is uniquely positioned to ensure a return on ML investment by providing robust, scalable and secure infrastructure, pioneering a data-centric approach to ML pipelines, prioritizing team collaboration across the organization and making sure teams are able to solve meaningful problems at scale by building trust in machine learning, even under the most intense regulatory conditions. "We're excited to bring together new investor Bright Pixel Capital and our existing partners, who believe in our vision and can help us become the trusted MLOps partner of any organization worldwide." As a category leader in the MLOps space, the funding will be used to continue to pioneer a data-centric approach to AI across Seldon's suite of products. Seldon has achieved a remarkable 400% YoY growth rate in its open source frameworks installed and running since its series A in November 2020. Seldon's cutting-edge research, in collaboration with teams at Cambridge University, has been key to their innovative product development and is a central focus of the company following the raise. Seldon is also investing in customer success and strengthening the global support function. "Seldon has differentiated itself by presenting a unique solution that is able to reduce the friction for users deploying and explaining ML models across any industry.