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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.

Combating Climate Change with Advanced Visual Analytics and AI

Across the globe, leading organizations recognize that addressing climate change and its effects is an imperative. What’s more, they increasingly believe that AI will play an important role. According to a recent Boston Consulting Group (BCG) survey, a vast majority (87%) of business leaders agree that AI-powered tools will help address climate change and its multifaceted social and economic impacts.

Visual Data Analytics Has Beekeepers Abuzz

Researchers have recognized the potential for artificial intelligence and machine learning to generate insights into bee populations and better support and manage them. Individual beekeepers can enhance tracking and monitoring across their hives by deploying detection models capable of recognizing bees and following their movement. On a broader scale, such models can follow the migration and population changes of entire colonies.

Believe Your Eyes: Optical Illusions and the Future of Vision AI

Researchers like Robert Max Williams believe optical illusions could prove a useful resource for their efforts to develop solutions capable of making the same subtle predictions and adjustments as the human eye. If scientists want to achieve “General Vision,” and truly mimic the human eye with artificial intelligence, teaching machines to recognize optical illusions and mimic a human response may play an essential role.

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.


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