RAIC Labs
Dylan Rich is a Sales Engineer at RAIC Labs, where employment commenced in May 2023. Prior to this role, Dylan served as a Senior Machine Learning Engineer at Perennial from August 2022 to April 2023, and held positions as Data Scientist IV and Platform Consultant at Descartes Labs from November 2017 to August 2022, as well as Data Scientist III and Platform Consultant. Academic contributions include a Graduate Assistantship at the University of Maryland Baltimore County from August 2015 to June 2017, focusing on teaching Physical Geography and Science of Water courses while conducting research for a Master's thesis on Bayesian network learning algorithms in environmental systems. Early research experiences included a Research Assistantship at Seattle University’s Department of Biology, where urban carnivores were studied, and another in the Department of Mathematics, which involved neural data processing for barn owls, leading to a published paper. Dylan holds a Bachelor of Science in Applied Mathematics from Seattle University.
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RAIC Labs
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We've rebranded, Synthetaic is now RAIC Labs! Quickly derive insights from large, unlabeled geospatial, video, and image datasets without time-intensive human labeling or pre-built models. Rapid Automatic Image Categorization (RAIC) is an unbiased tool that meets users’ ever-changing analytic demands for their perpetually evolving datasets, in an unrivaled timeline. RAIC enables users to find and classify anything in minutes, not months, without labeled data. Simply provide a single example object image and RAIC will find similar objects in your unlabeled dataset and return contextually-related results. You can then improve the AI by identifying the best results through an intuitive human nudge tool. From there, you can run inference jobs and turn results into insights using dashboarding tools or existing analytics platforms.