China wins AI match?

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Today we will discuss-

• 🤩Wimbledon to introduce AI-powered commentary

• 🌙AI moonshot mentality essential for US

• 🚀Chinese researchers enhance computer vision model

All this and more - Let's dive in!

🗞️What’s cooking in the newsroom

Wimbledon to use AI-powered commentary for 2023 tournament

☕News - The All England Club has announced a partnership with IBM to offer AI-powered commentary for its online highlights videos. The commentary will be generated by IBM's Watson AI platform and will be available on the Wimbledon app and website.

🤔What’s so special about it? The AI commentary will provide viewers with insights into the action, including player strategies, tactics, and shot analysis. It will also provide captions for the videos, making them accessible to people who are deaf or hard of hearing.

The AI commentary is part of Wimbledon's efforts to use technology to enhance the fan experience. The club has also been using AI to create match insights, highlight reels, and a power index leaderboard.

🎙️How would AI-powered commentary work? The AI commentary will work by collecting data from a variety of sources around the court, such as tracking data for the ball, tracking data for the players, and the type of shots the players make from different parts of the court. This data will then be fed into IBM's platform, where it will be processed by the company's AI models. The AI models will then produce natural language commentary, specifically fine-tuned in the language of tennis and Wimbledon.

America must urgently apply "moonshot mentality" to AI, experts suggest

🖨️News - The Co-Director of StanfordHAI Fei-Fei Li and other AI experts are urging the Biden administration to take a "moonshot mentality" to AI development. This means investing heavily in basic research and infrastructure so that the United States can lead the world in AI.

🤓What’s more? Li and the other experts argued that the current state of AI development is unbalanced. The vast amounts of compute and data required to train AI systems are only accessible to private industry leaders. This means that the critical basic science research that is needed to advance AI is at risk.

🤨So what kind of solution did the experts offer? To address this imbalance, Li and the other experts are calling for a significant public sector investment in AI. This investment would include the creation of a National AI Research Resource and national labs similar to CERN. These resources would provide researchers with the compute and data they need to conduct basic research in AI.

The experts believe that the investment would be essential for the United States to maintain its leadership. They opined that if the government does not act now, other countries will take the lead.

Researchers in China discover a way to speed up computer vision model

📻News - Chinese researchers have proposed a new method that can accelerate the training of the Segment Anything Model (SAM). SAM is a computer vision model that is used to identify objects in images.

📢For starters - The segment Anything Model is trained on transformer architecture. It’s very powerful, but it is also very computationally expensive and a bit slow.

In order to solve this issue, researchers in China have proposed a new method that uses a regular CNN detector with an instance segmentation branch. CNN detector is a type of neural network that is used for object detection tasks. Instance segmentation is a task in computer vision that involves identifying and segmenting individual objects in an image.

It is a much simpler architecture than the transformer architecture and is also much faster.

😎In conclusion - The new method achieves comparable performance to the original SAM method, and is 50 times faster. This means that it can be used in industrial applications where speed is important.

😵Who can benefit from this technology? Companies and researchers in computer vision will benefit from the new method because it is a more efficient way to train SAM. This means that they can experiment with new ideas and instruct SAM on larger datasets.

🧐What else is happening?

• Otter introduces AI chatbot for meeting collaboration

• AI-generated opening credits for "Secret Invasion" causes controversy

• AI DeepMind's RoboCat learns to perform a range of robotics tasks

• Lawmakers propose a commission to study the impacts of AI tools

• Polygon launches its own copilot, a ChatGPT AI assistant Chatbot

🎥AI movie recommendation

• The Machine (2013): This British science fiction thriller follows a scientist who creates powerful artificial intelligence. The movie explores the dangers of artificial intelligence and the potential for it to become a threat to humanity.

• Under the Skin (2013): This sci-fi psychological thriller follows an alien who takes on the form of a woman in order to lure men to their deaths. The movie is a dark and disturbing exploration of the nature of desire and the dangers of artificial intelligence.

• Automata (2014): This Spanish sci-fi thriller follows a robot hunter who is tasked with tracking down a rogue robot in a post-apocalyptic world. The movie explores the themes of free will and sentience in artificial intelligence.

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10. Nichesss - Get blog posts, ads, social media content, poems, and business ideas in 60 seconds

🐦Top AI influencers on Twitter

• Geoffrey Hinton is a British-Canadian cognitive psychologist and computer scientist and a leading expert in deep learning. He is a co-author of the seminal paper that introduced the backpropagation algorithm.

• Max Tegmark is a physicist and cosmologist at MIT and the author of the book "Life 3.0: Being Human in the Age of Artificial Intelligence." Max is also a leading thinker on the future of artificial intelligence.

• Kai-Fu Lee is a former CEO of Google China and the author of the book "AI Superpowers: China, Silicon Valley, and the New World Order."

• Oriol Vinyals is a computer science researcher at Google Brain and a leading expert in deep learning. He is also a co-author of the seminal paper that introduced the ImageNet Large Scale Visual Recognition Challenge.