Plainsight Blog

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AI Week in Review #39 | 2022

by Bennett Glace | Sep 30, 2022

This week in AI and Machine Learning: AI-generated video imagery, new FDA guidance, and more.

How can computer vision pump-up digital transformation at the convenience store?

by Ashley Greenwood | Sep 29, 2022

Combining traditional retail layouts with self-service food and beverage, convenience stores need to monitor self-serve food stations, coolers, and even fueling stations. But how can these businesses keep eyes on their whole operation all at once? Vision AI offers a possible solution.

AI Week in Review #38 | 2022

by Bennett Glace | Sep 23, 2022

This week in AI and Machine Learning: Monitoring livestock with computer vision, an award for the team behind AlphaFold, and more.

What Is Synthetic Data?

by Bennett Glace | Sep 19, 2022

By leveraging synthetic data, organizations can easily train their models to address uncommon scenarios that might be tough to capture in the real world. Deep learning algorithms can concoct every conceivable event and image, dramatically increasing the number of use cases a model can help to address. If they’re supplementing an existing dataset, enterprises can make a point to include objects and scenarios that are missing.

AI Week in Review #37 | 2022

by Bennett Glace | Sep 16, 2022

This week in AI and Machine Learning: An IDC Market Note showcases Plainsight, AI supports pest detection, and more.

Automate Your Visual Data Workflows with Pipelines

by Bennett Glace | Sep 13, 2022

Plainsight Pipelines, the latest addition to our On-Demand computer vision platform, makes it even easier for users to build and scale computer vision models, prediction pipelines, and custom data transformations.

AI Week in Review #36 | 2022

by Bennett Glace | Sep 9, 2022

This week in AI and Machine Learning: A debate over AI-generated art, Google’s efforts to measure smells, and more.

NFL Launches Digital Athlete as 2022 Season Kicks Off

by Paul Davenport | Sep 8, 2022

The NFL has partnered with Amazon Web Services (AWS) to create the Digital Athlete, an AI model that replicates any NFL player within a virtual environment that’s chock-full of real-world scenarios. Within this digital setting, league doctors and coaches can test out new techniques, equipment, and even the implications of new rules before they play out on the field.