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Positive AI Application with Pickleball Vision

Pickleball is one of the fastest-growing sports in the USA and around the world. The appeal is clear - it is easy to get started but takes years to master and there is always room to improve your game. There are now almost 9 million players in the United States alone, not bad for a sport that was invented in the 1960s.

AI and Sports Computer Vision

The sport is often described as a combination of tennis, ping-pong and badminton. It’s a great workout, beginners can become competitive almost immediately and it is suitable for players of almost all levels. And now, with the help of Pickleball Vision AI, it is part of the AI revolution.

Their patent-pending software uses computer vision and machine learning to turn videos of pickleball games into training material, match reporting and insights.

Computer vision is a branch of Artificial Intelligence most commonly known for its use in facial recognition software. It takes video feed or camera inputs and transforms the data into numerical representations that can be more easily processed and analyzed by algorithms. This is then processed via convolutional neural networks (CNNs) and Machine Learning algorithms are applied to identify patterns and garner understanding.

"Convolutional Neural Networks (CNNs) are to computer vision what Large Language Models (LLMs) are to natural language processing. Just as CNNs extract hierarchical features from images to recognize patterns and objects, LLMs parse through vast amounts of text to understand and generate coherent language."

PB Vision appear to be in the early stages of their AI journey, at least in terms of their release schedule. We recommend you follow them on Twitter to stay up to date with them, and maybe pick up a fun new hobby along the way.

This software might seem a little more frivolous than the sort we usually cover here at Aiifi but it is a great example of outside-the-box thinking when it comes to Artificial Intelligence applications. Most instances of computer vision we see in the news related to facial recognition and employee monitoring, but here is a company putting that software to use in a much more positive manner. It is also useful to see the application of AI in new areas rather than the simple automation of tasks that humans currently carry out.


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