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A team of computer programmers at IT University of Copenhagen has developed a new way to encode and generate Super Mario Bros. levels—called MarioGPT, the new approach is based on the language model GPT-2. The group outlines their work and the means by which others can use their system in a paper on the arXiv pre-print server.

Mario Brothers is a first introduced in 1983—it involves two Italian plumbers emerging from a sewer and attempting to rescue Princess Peach, who has been captured and held by Bowser. To rescue her, the brothers must travel (via input from the game player) across a series of obstacles made of pipes and bricks. As they travel, the terrain changes in accordance with the level they have achieved in the game. In this new effort, the team in Denmark has recreated one aspect of the game—the number of levels that can be traversed.

The researchers used Generative Pre-trained Transformer 2 (GPT-2)—an open-source language created by a team at OpenAI, to translate user requests into graphical representations of Super Mario Brothers game levels. To do so, they created a small bit of Python code to help the language model understand what needed to be done and then trained it using samples from the original Super Mario Bros. game and one of its sequels, “Super Mario Bros.: The Lost Levels.”

The Methuselah Foundation is a non-profit medical charity focused on extending the healthy human lifespan by making 90 the new 50 by 2030. Our goal is to accelerate results in the longevity field, as well as the biotechnology, regenerative medicine, life sciences sectors. We incubate and sponsor mission-relevant ventures, fund research, and support projects and prizes.

The Methuselah Foundation is a non-profit medical charity focused on extending the healthy human lifespan by making 90 the new 50 by 2030. Our goal is to accelerate results in the longevity field, as well as the biotechnology, regenerative medicine, life sciences sectors. We incubate and sponsor mission-relevant ventures, fund research, and support projects and prizes.

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What if, instead of using X-rays or ultrasound, we could use touch to image the insides of human bodies and electronic devices? In a study publishing in the journal Cell Reports Physical Science (“A smart bionic finger for subsurface tactile-tomography”), researchers present a bionic finger that can create 3D maps of the internal shapes and textures of complex objects by touching their exterior surface.

“We were inspired by human fingers, which have the most sensitive tactile perception that we know of,” says senior author Jianyi Luo, a professor at Wuyi University. “For example, when we touch our own bodies with our fingers, we can sense not only the texture of our skin, but also the outline of the bone beneath it.”

“Our bionic finger goes beyond previous artificial sensors that were only capable of recognizing and discriminating between external shapes, surface textures, and hardness,” says co-author Zhiming Chen, a lecturer at Wuyi University.