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IBM and The All England Lawn Tennis Club Launch New Generative AI Feature for Personalised Player Stories at ... - IBM Newsroom: IBM and The All England Lawn Tennis Club Launch New Generative AI Feature for Personalised Player Stories at ...  IBM Newsroom http://dlvr.it/T8NJpT #ai #artificialintelligence

Today's topics: -AI Bubble and Future Impact -GitHub Repository on AI Hallucinations -Weight Averaged Reward Models Paper -New AI Features in Google Chrome -AI-Powered Meeting Notes Tool -Optimizing Matrix Multiplication Code -Facial Recognition Wrongful Arrest Case -Text-to-Image Diffusion GitHub Project -Replication of ColBERT-v1 Research -AI Librarian for Saved Content -Realistic Talking Head Video Synthesis -Improving LLMs in Machine Translation -Elon Musk vs. Larry Page on AI Future -Aligning LLMs with User Preferences -Benchmarking Multimodal Models -AI in Gymnastics Judging -Training AI Models to Deceive -ElevenLabs' Series B Funding and Products -NVIDIA RTX Video HDR and RTX Remix Beta #ai #news

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Hello everyone, I have been working on a new project, a Tennis Analysis model. I will be sharing the highlights of the project and progress on LinkedIn, as it might help anyone and could open doors to interesting questions. The project detects and tracks the player and the tennis ball across a given video. We will also detect the courts' key points to know the player's position relative to the court, measure the distance ran by a player and whether the ball was in or out (Although Hawkeye is much better than the model that'll be created). The output of those models will be used to know how many times a player shot the ball (rallied) and how fast the ball was shot. We will also measure the player's speed and the distance he covered. In addition, Two CNNs (Convolutional Neural Networks) will be trained, the first one will be used to detect the moving tennis balls to enhance the detection accuracy of the out-of-the-box model (YOLO in our case). The other model is a CNN that will be trained to estimate the court's key points. This will be done using pytorch. The following videos showcase the beginning of the project, where we have an input image and input video and the output video shows the bounding boxes around the objects. As seen from the output video, the model detects the tennis ball but does not track it very well. We will be using a custom dataset from Roboflow, to train the out-of-the-box model to better track the tennis balls. Looking forward to sharing more soon! #TennisAnalysis #MachineLearning #DataScience #SportsAnalytics #PyTorch #CNN #AI #Innovation

🎾 My own #DeepLearning process about #DeepLearning techniques while watching deep shots at #Wimbledon! Combining the best of both worlds – work and play – with some ‘extras’. 🍺🖥️ In the meantime, got curious about specific developments through deep learning applied to Tennis: 📚 Tennis Action Classification: Using deep learning to identify and analyze different tennis shots. This tech could revolutionize how we collect game statistics and improve player strategies. (https://lnkd.in/eHAEVApv) 🤖 AI-Simulated Tennis Players: Researchers have developed an innovative approach using broadcast videos to teach AI systems how to play tennis with remarkable realism. Perfect for creating advanced training simulations. (https://lnkd.in/eMAadtdA) 🎥 TrackNet: A cutting-edge tool for tracking tennis balls during matches, providing precise data for better performance analysis. (https://lnkd.in/eigm_pi4) Cheers to a productive and enjoyable weekend start! 🍺🖥️ “Success is where preparation and opportunity meet.” - Bobby Unser 🚀 #AI #DeepLearning #LifeIsNotEasy

A way to go #AI ;-) The new frontier for AI is how to act in the physical world. Something we humans excel at but never really appreciate our capabilities like driving cars, skiing, kitesurfing, horse riding, cooking, etc.

🎨 AI Image Generation Showdown I’m thrilled to share my latest video where I put three AI image generation tools to the ultimate test. I wanted to see how these tools stack up using a fun and unique prompt: an alien character playing tennis with Lacoste branding. After all, tennis core is the main theme this summer! 🎾👽 And here’s the kicker: the video’s voiceover and text are entirely AI-generated too! Nothing human involved except for my creative direction. Curious to see which tool came out on top? Check out the video and find out! 🌟 https://lnkd.in/dZbJW2g5 #aimarketing #creativity #technology #ai

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Hello everyone, An update on the Tennis Analysis project: In the previous post, I highlighted the challenge of ball tracking with the YOLO model. To address this, we utilized a custom dataset from Roboflow, downloaded via their API, and trained the YOLO model on Colab's free version. After training, I've tested the model on an input video and observed a significant increase in ball tracking accuracy, showcasing the effectiveness of the trained model. Moving forward, a PyTorch model will be created to detect court keypoints. This will enable us to derive tennis metrics such as player position and distance covered and a few other interesting things. Here's the link to the Roboflow Dataset: https://lnkd.in/d8WYxmum Looking forward to sharing the last and final result soon! #TennisAnalysis #MachineLearning #DataScience #SportsAnalytics #PyTorch #CNN #AI #Innovation