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A team of researchers at Stanford University has created an artificial intelligence-based player called the Vid2Player that is capable of generating startlingly realistic tennis matches—featuring real professional players. They have written a paper describing their work and have uploaded it to the arXiv preprint server. They have also uploaded a YouTube video demonstrating their player.

Video game companies have put a lot of time and effort into making their games look realistic, but thus far, have found it tough going when depicting human beings. In this new effort, the researchers have taken a different approach to the task—instead of trying to create human-looking characters from scratch, they use sprites, which are characters based on of real people. The sprites are then pushed into action by a computer using to mimic the ways a human being moves while playing tennis. The researchers trained their AI system using video of real tennis professionals performing; the footage also provided imagery for the creation of sprites. The result is an interactive player that depicts real professional tennis players such as Roger Federer, Serena Williams, Novak Jovovich and Rafael Nadal in action. Perhaps most importantly, the simulated gameplay is virtually indistinguishable from a televised match.

The Vid2Player is capable of replaying actual matches, but because it is interactive, a user can change the course of the match as it unfolds. Users can change how a player reacts when a ball comes over the net, for example, or how a player plays in general. They can decide which part of the opposite side of the court to aim for, or whether to hit backhand or forehand. They can also slightly alter the course of a real match by allowing a shot that in reality was out of bounds to land magically inside the line. The system also allows for players from different eras to compete. The AI software adjusts for lighting and clothing (if video is used from multiple matches). Because AI software is used to teach the sprites how to play, the actions of the sprites actually mimic the most likely actions of the real player.

OpenAI’s new language generator #GPT-3 is shockingly good—and completely mindless: https://bit.ly/3kphfsX

By Will Douglas Heavenarchive page from MIT Technolgy Review

#AI #MachineLearning #NeuralNetworks #DeepLearning


“Playing with GPT-3 feels like seeing the future,” Arram Sabeti, a San Francisco–based developer and artist, tweeted last week. That pretty much sums up the response on social media in the last few days to OpenAI’s latest language-generating AI.

Individual frequency can be used to specifically influence certain areas of the brain and thus the abilities processed in them — solely by electrical stimulation on the scalp, without any surgical intervention. Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences have now demonstrated this for the first time.

Stroke, Parkinson’s disease and depression — these medical illnesses have one thing in common: they are caused by changes in brain functions. For a long time, research has therefore been conducted into ways of influencing individual brain functions without surgery in order to compensate for these conditions.

Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig have taken a decisive step. They have succeeded in precisely influencing the functioning of a single area of the brain. For a few minutes, they inhibited exactly the area that processes the sense of touch by specifically intervening in its rhythm. As a result, the area that was less networked with other brain regions, its so-called functional connectivity, decreased, and thus also the exchange of information with other brain networks.

The discovery has led to a new polymer that allows humans to integrate electronics into the brain after challenges with substances such as gold, steel and silicon resulted in scarring of organic tissue.

A major breakthrough in materials research may allow the human brain to link with artificial intelligence, it was announced at an American Chemical Society Fall 2020 event on Monday.

Scarring due to previously used materials can block electrical signals transmitted from computers to the brain, but University of Delaware researchers developed new types of polymers aimed at overcoming the risks.