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The ever-growing playground teaches AI how to teach multitasking

The ever-growing playground teaches AI how to teach multitasking
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Scientists Working on Continual Learning to Overcome 'Catastrophic Forgetting'

AI Trends April 15, 2021 By  John P. Desmond, AI Trends Editor  Algorithms are trained on a dataset and may not be capable of learning new information without retraining, as opposed to the human brain, which learns constantly and builds on knowledge over time.  An artificial neural network that forgets previously learned information upon learning new information, is demonstrating what is called “catastrophic forgetting.”    In an effort to nudge AI to work more like the human brain in this regard, a team of AI and neuroscience researchers have banded together to form ContinualAI, a nonprofit organization and open community of AI continual learning (CL) enthusiasts, described in a recent account in VentureBeat. 

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AI is (finally) able to master classic 1980s platform games

AI is (finally) able to master classic 1980s platform games By Bang Showbiz Scientists have created an AI program which can master classic 1980s platform games. Researchers formed a family of algorithms - known collectively as Go-Explore - which is capable of completing Atari titles like Pitfall , Freeway and Montezuma s Revenge . These games have been tough for AI in the past, but the algorithms could have real-world implications by helping robots better navigate certain environments. These include the likes of disasters zones or the average home, with a range of benefits. Researchers Adrien Ecoffet, Joost Huizinga and Jeff Clune told BBC News: Our method is indeed pretty simple and straightforward, although that is often the case with scientific breakthroughs.

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AI conquers challenge of 1980s platform games

BBC News By Paul Rincon Published image captionMontezuma s Revenge is deceptively difficult to solve for an algorithm Scientists have come up with a computer program that can master a variety of 1980s exploration games, paving the way for more self-sufficient robots. They created a family of algorithms (software-based instructions for solving a problem) able to complete classic Atari games, such as Pitfall. Previously, these scrolling platform games have been challenging to solve using artificial intelligence (AI). The algorithms could help robots better navigate real-world environments. This remains a core challenge in the fields of robotics and artificial intelligence. The types of environments in question include disaster zones, where robots could be sent out to search for survivors, or even just the average home.

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