Plainsight’s Co-Founder and CTO, Logan Spears, sits down for a podcast discussion on image-generating AI, the tech behind it, and implications for the future.
Save a Spot at the Thanksgiving Table for Computer Vision
When it comes time to plan the Thanksgiving feast, some cooks turn to timeworn family recipes. More adventurous chefs, however, take the holiday as an opportunity to try something new, searching for inspiration online or in the pages of cookbooks.
A Class Action Lawsuit Could Soon Shake AI
This week in AI and ML news: An AI-centered class action lawsuit, Google’s 3D flyovers, and more.
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.
AI Week in Review #40 | 2022
This week in AI and Machine Learning: Looking ahead to Google Cloud Next, the AI Bill of Rights, and more.
Computer Vision Insights and More at Google Cloud Next
October 11th-13th, Plainsight’s Co-Founder and CEO, Carlos Anchia, is joining AI professionals from around the globe to discuss the future of computing at Google Cloud Next. Get the full run down on the events must watch sessions.
How can computer vision pump-up digital transformation at the convenience store?
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.
What Is Synthetic Data?
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.
NFL Launches Digital Athlete as 2022 Season Kicks Off
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.
Data Annotation for Computer Vision
Feb 8th 2022 | Labeling Tutorial
Detecting Unwanted & Hazardous Objects
Oct 26th 2021 | Computer Vision
Dew-able AI: Solving the Mountain Dew Super Bowl Challenge
Feb 13th 2021 | Computer Vision