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Posted by Peter Mattson, Senior Staff Engineer, ML Performance, and Praveen Paritosh, Senior Research Scientist, Google Research, Brain Team Machine learning (ML) offers tremendous potential, from diagnosing cancer to engineering safe self-driving cars to amplifying human productivity. To realize this potential, however, organizations need ML solutions to be reliable with ML solution development that is …

Read more “Data-centric ML benchmarking: Announcing DataPerf’s 2023 challenges”

Bounding box annotation is a time-consuming and tedious task that requires annotators to create annotations that tightly fit an object’s boundaries. Bounding box annotation tasks, for example, require annotators to ensure that all edges of an annotated object are enclosed in the annotation. In practice, creating annotations that are precise and well-aligned to object edges …

Read more “Snapper provides machine learning-assisted labeling for pixel-perfect image object detection”

Scientific Research with Palantir: A Review of Health Research in 2022 Editor’s note: At Palantir, we support our partners in health and life sciences by providing them with the technology they need to achieve their most critical missions. In recent years, our partners across hospital systems, life science companies, and Federal agencies have expanded their use …

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This is a guest post by Neslihan Erdogan, Global Industrial IT Manager at HAYAT HOLDING. With the ongoing digitization of the manufacturing processes and Industry 4.0, there is enormous potential to use machine learning (ML) for quality prediction. Process manufacturing is a production method that uses formulas or recipes to produce goods by combining ingredients …

Read more “HAYAT HOLDING uses Amazon SageMaker to increase product quality and optimize manufacturing output, saving $300,000 annually”