Plainsight Blog
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Plainsight Granted U.S. Patent for Foundational Vision AI Technology
Plainsight, the leader in proven vision AI, announced today it has been granted a patent by the United States Patent and Trademark Office (USPTO) for its breakthrough technology used to identify, count, and monitor livestock automatically in real time.
Introducing Computer Vision for Ranching
The work done by AI-powered ranch vehicles comes down to more than automating key processes. When they’re armed with cutting-edge solutions like custom-built computer vision models, ranchers, farmers, and other agriculture industry players are able to act with greater agility with the insights necessary to independently innovate, build competitive advantages, and make more informed decisions.
Plainsight and MarineSitu Announce Collaboration to Propel a Sustainable Blue Economy Into The Future
The companies will focus on developing vision AI solutions for monitoring marine energy devices to protect aquatic ecosystems.
Best Practices for Solution-Centric Computer Vision
Projects often fail when the focus is placed on technology alone instead of holistic business solutions. AI is just one tool in an enterprise’s toolbox and every solution needs the right resources to support its success. It’s rare for AI to prove the only tool necessary for creating a solution…
Back (of House) to the Future: Vision AI in Restaurant Kitchens
Vision AI offers solutions to a number of the challenges facing restaurants, presenting use cases for everything from keeping kitchens cleaner to ensuring each patty spends the exact right amount of time on the grill.
What Is Machine Vision?
Machine vision was really born on the assembly line, designed as a system of existing technologies and machinery that, combined, “watch” the production process and recognize when flaws occur.
What Is Deep Learning?
Deep learning sits within the machine learning subset of AI technologies. Machine learning systems are designed to educate themselves and adapt with or without human intervention. ML systems attempt to learn the same way humans do, through trial and error. Targeted ads, recommended products, and predictive search terms are all the result of successful machine learning.
Taking a Data-Driven and Model-Driven Approach to AI
Taking the first step toward more data-centric AI is as simple as recognizing the immense value your data holds and the value inherent in curating it carefully. But centralizing and systematizing your approach to AI isn’t enough—nor is it enough to focus on updating and testing the models you deploy at the expense of data quality. Even better than a data-centric approach to AI is a data-driven approach, one that focuses on both the quality of the data collected and the efficacy of the models this data is used to train.
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Featured Articles
Plainsight and Ericsson Launch 5G Innovation Partnership for Vision AI Solutions at the Edge
May 9, 2023 | Press
CRN’s 2023 Women of the Channel Honors Elizabeth Spears of Plainsight
May 8,2023 | Press
Computer Vision-Enabled Restaurants: The Recipe for Super-Sized Innovation
May 2,2023 | Blog
