"The more aroused the fly is the harder it tries to shoot" - Google's fully mapped fly brain is now playing Doom, Beat Saber, and more
It's science-fiction Friday as Google's fully mapped fly brain , which was revealed last week, has been engineered to play Doom and rhythm-action game Beat Saber . Read more
Google's recently unveiled comprehensive map of a fly's brain has demonstrated remarkable capabilities, including playing video games such as Doom and Beat Saber. This achievement represents a significant milestone in neuroscience research, as the team painstakingly compiled the fly brain model over several years with the aid of artificial intelligence. The fly brain model was made publicly available for download, allowing other researchers to build upon this foundational resource.
Following its release, engineers quickly put the map to use, training the fly brain to play Doom. While the simulated fly struggled initially, it persevered and managed to play the game numerous times despite still not performing optimally. Not long after, a modder named domi managed to get the fly brain playing Beat Saber, a video game featuring lightsaber-based rhythm-action gameplay. The fly model successfully waved its lightsabers and sliced through advancing tiles, showcasing impressive coordination and precision.
Interestingly, domi also noted that the more aroused the fly is, the harder it tries to shoot in the game, which demonstrated the potential of the fly brain model to adapt and learn from its environment. This observation raises intriguing possibilities for future neuroscience experiments, as the fully mapped fly brain could be utilized to further advance our understanding of the human brain and its intricate workings.
Google's pioneering work in mapping the fly brain is poised to become a foundational resource for neuroscience, with the potential to revolutionize our comprehension of the complex workings of the human mind.
Written by urgent.news from Eurogamer's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.