How MIT researchers are using neural nets to automate manual tasks for novel serotonin research
Jungsoo Kim is a PhD graduate student at MIT’s Flavell Lab which focuses on cutting-edge neuroscience research. His team is currently exploring how computation and behavior emerge from neural circuits. Neurons, just like electronics, need to be properly wired in order to function well. Their project investigates how serotonin
How Pathware is accelerating pathology by delivering AI-powered expert analyses
Learn how an innovative medical device company, Pathware, is leveraging a training data platform to more quickly iterate on high-quality ML data. Their mission is to ultimately simplify digital pathology workflows and save hospitals billions of dollars.
How Arturo builds AI-first products from the ground up to deliver insights for the $1.2 trillion insurance industry
Gareth Jones, data scientist at Arturo, recently spoke with our COO, Brian Rieger on how Arturo’s machine learning team built mature and complex AI-first products while juggling resource costs, data labeling and scalability as top priorities.
Stanford CS230 grad students research the next generation of AI-driven land urban air vehicles
Andrew and Seraj are masters graduate researchers at Stanford University attending CS230 Deep Learning. Their research project focused on identifying suitable areas to land urban air vehicles through satellite imagery.
Using model-assisted labeling to speed up annotation efficiency with Labelbox
Recently, a team of researchers at the Institute of Industrial Science, a part of The University of Tokyo, leveraged Labelbox's model-assisted labeling features in order to speed up their machine learning processes by 2-3x.