DeepMinds

Working with player-tracking data from 7,176 corners taken in the Premier League during 2020 and 2021, the researchers began by representing the arrangement of players as a graph, with the players’ position, movement, height, and weight encoded as nodes on the graph, and relationships between players as the lines between them. Then they used an approach called geometric deep learning, which takes advantage of the symmetry of a soccer field to shrink down the amount of processing the neural network needed to do. (This…

The main benefit is that the AI assistant reduces the workload of the coaches, says Ondřej Hubáček, an analyst at the sports data firm Ematiq who specializes in predictive models, and who did not work on the project. “An AI system can go through the data quickly and point out errors a team is making—I think that’s the added value you can get from AI assistants,” he says.  To assess TacticAI’s suggestions, GoogleDeepMind presented them to five football experts: three data scientists, one video analyst, and one coaching…

“SIMA takes one step further and shows stronger generalization to new games,” he says. “The number of environments is still very small, but I think SIMA is on the right track.A New Way to PlaySIMA shows DeepMind putting a new twist on game playing agents, an AI technology the company has pioneered in the past.In 2013, before DeepMind was acquired by Google, the London-based startup showed how a technique called reinforcement learning, which involves training an algorithm with positive and negative feedback on its…

“It’s cool work,” says Matthew Gudzial, an AI researcher at the University of Alberta, who developed a similar game generator a few years ago.  Genie was trained on 30,000 hours of video of hundreds of 2D platform games taken from the internet. Others have taken that approach before, says Gudzial. His own game generator learned from videos to create abstract platformers. Nivida used video data to train a model called GameGAN, which could produce clones of games like Pac-Man. But all of these examples trained the model…

Policymakers and regulators across the world must think of regulating artificial intelligence (AI) in the next 5-10 years to prevent misuse of such tools in affecting nation states by politicizing the spread of information, said Mustafa Suleyman, cofounder, Inflection AI and DeepMind.“I think the negative consequences here are likely to arise simply because so many people with different organisational interests, different religious and political values will not only affect information but also the real world in practice.…

To train AlphaGeometry's language model, the researchers had to create their own training data to compensate for the scarcity of existing geometric data. They generated nearly half a billion random geometric diagrams and fed them to the symbolic engine. This engine analyzed each diagram and produced statements about their properties. These statements were organized into 100 million synthetic proofs to train the language model. Roman Yampolskiy, an associate professor of computer science and engineering at the University…

DeepMind has used a large language model (LLM) to generate a novel solution to one of humanity’s toughest math problems — in a breakthrough that could herald a new era in AI development.  The model, known as FunSearch, discovered a solution to the so-called “cap set puzzle.” The decades-old math conundrum essentially comes down to how many dots you can joint down on a page while drawing lines between them, without three of them ever forming a straight line. If that gave you a migraine, don’t…

“The model is innately more capable,” Sundar Pichai, the CEO of Google and its parent company Alphabet, told MIT Technology Review. “It’s a platform. AI is a profound platform shift, bigger than web or mobile. And so it represents a big step for us.”  It’s a big step for Google, but not necessarily a giant leap forward for the field as a whole. Google DeepMind claims that Gemini outmatches GPT-4 on 30 out of 32 standard measures of performance. And yet the margins between them are thin. What DeepMind has done is pull…

Demis Hassabis has never been shy about proclaiming big leaps in artificial intelligence. Most notably, he became famous in 2016 after a bot called AlphaGo taught itself to play the complex and subtle board game Go with superhuman skill and ingenuity.Today, Hassabis says his team at Google has made a bigger step forward—for him, the company, and hopefully the wider field of AI. Gemini, the AI model announced by Google today, he says, opens up an untrodden path in AI that could lead to major new breakthroughs.“As a…

Google DeepMind researchers have trained a deep learning model to predict the structure of over 2.2 million crystalline materials — 45 times more than the number discovered in the entire history of science. Of the two million-plus new materials, some 381,000 are thought to be stable, meaning they wouldn’t decompose — an essential characteristic for engineering purposes. These new materials have the potential to supercharge the development of key future technologies such as semiconductors,…