InnovateEnergy’s Post

Tennis is getting an AI upgrade.🎾 At Fortune Brainstorm AI London, Wimbledon’s Chris Clements and IBM’s Matthew Candy explained how the world's oldest tennis tournament is implementing the tech. Learn more about #FortuneAI: trib.al/bG9jwRU

Great to join this panel at Fortune Brainstorm AI London yesterday and share some of the use cases for AI at Wimbledon. Few key takeaways from some of the other (far more knowledgeable than me) speakers on the day: - As important as knowing the capabilities of AI models is knowing the limitations, and therefore the safeguards you need to put in place. - At its heart, adoption of AI is all about people and change management. Organisations most effective at change management will be those that can realise the benefits of AI most effectively. - There is some really cool AI capability out there, but just because you can use it doesn’t mean you should. Knowing the value to your fans (or customers) and business is essential. Take a look at Fortune for some key clips and live coverage of day 2.

I'm excited to share my latest project where I explore how computer vision can revolutionize tennis analysis! 📊 Using advanced machine learning techniques, this system tracks player movements, analyzes shot patterns. 💻 What's Inside: Real-time player tracking Shot classification and prediction Whether you're a tennis enthusiast or interested in how AI can be applied to sports, this video demonstrates the immense potential of technology in transforming how we view and analyze tennis. #AI #ComputerVision #TennisAnalysis #MachineLearning #SportsTech #DataScience #ArtificialIntelligence #TennisTech #AIinSports #SportsAnalytics

A new generative AI tool called Scout Advisor, developed by IBM for Spain’s Sevilla soccer club, is indicative of how GenAI is becoming a key player in sports. #aitool #genai #generativeai #sports

AI/ML is future...

DeepMind's latest robot can play table tennis. It’s the first agent to achieve amateur human level performance in this sport. Once deployed to the real world, it collects data on its performance against humans to refine its skills back in simulation - creating a continuous feedback loop. Source: https://lnkd.in/ddczMxm8 ♻️ Repost this if you found it useful. ↓ Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.

IBM has been the technology partner for Wimbledon since 1990. Each year IBM works to deliver new innovations to engage Wimbledon’s 19M fans around the globe. This year, IBM and The All England Lawn Tennis Club are launching a new generative AI feature – ‘Catch Me Up’ – built and trained using IBM’s Granite LLM, through the watsonx platform – helps fans stay up to date on players across all ladies’ and gentleman’s singles matches. IBM at Wimbledon is transforming the fan experience with AI-generated player stories. ‘Catch Me Up’ was built using IBM’s Granite large language model (LLM) to provide AI-generated text using the capabilities of the watsonx platform. See more at https://ibm.biz/Bdm68H #tennis #AIforTennis #Wimbledon #IBM #watsonx #ProudIBMer #AI #genAI

DeepMind's latest robot can play table tennis. It’s the first agent to achieve amateur human level performance in this sport. Once deployed to the real world, it collects data on its performance against humans to refine its skills back in simulation - creating a continuous feedback loop. Source: https://lnkd.in/gcVTqRQZ ♻️ Repost this if you found it useful. ↓ Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.

Let’s break down what this tennis-playing robot could really be learning. It’s not just about hitting the ball — the potential goes far beyond the game, opening up fascinating possibilities. 🤖 1. A Robot That Reads Minds Through Movement This robot doesn’t just track shots; it reads the opponent’s body language — tense movements, subtle pauses, shifts in posture. It learns to anticipate actions before they happen, bridging the gap between motion and psychology. Imagine robots that understand human intentions without a single word. ⚛️ 2. Detecting Hidden Physics in Every Shot What if the robot captures tiny vibrations in the ball and racket, invisible to the human eye? This could reveal previously unknown principles of physics, transforming not just sports, but how we build precision technology. 🔄 3. From Tennis to Mastering Physical Systems For the robot, tennis is practice for mastering complex physical interactions. It’s learning dynamics like collisions, friction, and speed. With this understanding, the robot could one day control any physical system — from machines to biological processes — instantly adapting to new challenges. 🌪️ 4. Robots That Thrive in Unpredictability The robot isn’t just learning to play; it’s learning to thrive in chaos. Each unpredictable shot is a new problem, and it improvises in real-time, like a human — but faster. This could lead to robots that excel in scenarios where human control fails. 🧠 5. Reading the Room: Robots Sensing Human Reactions The robot isn’t just focused on the game; it’s aware of the people watching. By detecting subtle changes in the audience’s reactions, like a breath or shift in attention, it adjusts its behavior. This suggests a future where robots don’t just perform tasks — they read the room, understanding humans on a deeply intuitive level. #Robotics #AI #FutureTech #HumanMachineInteraction #Innovation #ChaosEngineering #PrecisionTech