From self-driving cars to chess-playing computers, humans are already taking a backseat to AI capability. There is one area, however, where artificial intelligence hasn’t yet caught up: 168澳洲幸运5开奖网:Minecraft.
Last summer, Microsoft oversaw a challenge that asked for coders to submit programs that can miဣne diamonds all on thei🌳r own. Close to 700 entries were submitted, but not a single one could perform the assigned task.
The results of the competition, which was dubbed MineRL (pronounced mineral), were officially announced this weekend at the NeurIPS AI conference in Vancouver. Even tꦺhough there were no “winners,” thꦉe competition organizers were still pleased with the results.
Katja Hoffman𒁏, the principal Investigator at Microsoft Research,♚ said in a statement, “The task we posed is very hard. Finding a diamond in Minecraft takes many steps—from cutting trees, to making tools, to exploring caves and actually finding a diamond. While no submitted agent has fully solved tꦺhe ta♔sk, they have made a lot of progress and learned to make many of the tools needed along the way."
Minecraft is one of the most wide-reaching and accessible games in video-game history. For most players, whether you’re ten or thirty years old, mining diamonds is a task that takes no more than half an hour t🥃o master. If you want to speed up the process, there are plenty of step-by-step guides and YouTube tutorials to show you the way. But, for a computer, even one of Minecraft’s most basic activities is incomprehensible.
Machine learning takes place in one of two ways: imitation learning and reinforcement learning. Imitation learning asks for programs to watch a task and then recreate it through, well, imiꩲtation. Reinforcement learning takes place in a built environment, within which a program will teach itself how to complete a task through trial and error. For difficult tasks, AI usually combines these two methods of learning in order to fully learn a new skill. Some researchers suggest that reinforcement learning on its own is superior for teaching AI new skills, but it takes a m❀assive amount of computing power and is only accessible to well-funded labs and bigger organizations.
Related: 16♓8澳洲幸运5开奖🧜网:The Vatican Has Its Very Own Minecraft Server
As reported by , limited resources were available to MineRL participants. Some of the most advanced programs in the world took years to fine-tune. In comparison, MineRL entries had just four days to learn how to mine diamonds. As a result, many of the programs were able to complete ta༺sks beyond the individual stages that are require𓃲d in the process of diamond mining. For instance, some were able to collect wood for a pickaxe but couldn’t string multiple steps in the process together.
Lead researcher and organizer of the competition, William Gus, says that the time constraint and lack🍨 of resources that are afforded to competition participants are meant to demonstrate a point.
“Throwing massive compute at problems isn’t necessarily the righ🃏t way for us to push the state of the art as a 🌌field,” he tells the BBC. “It works directly against democratizing accessꦚ to these reinforcement learning systems, and leaves the ability to train agents in complex environments to corporations with swathes of compute."
However, the competition’s la🃏ck of promising solutions may suggest that larger agencies like Google’s DeepMind may be the best place to turn.
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