We are very proud that Nicholas Guttenberg, Senior Research Scientist at GoodAI, recently won the Evocraft 2021 competition - the Minecraft Open-Endedness Challenge!
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Progress from recent experiments.
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In 2021/22 GoodAI will focus on four core research areas: learning to learn, lifelong (gradual) learning, open-endedness, and generalization / extrapolation of meta-learned algorithms.
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Is sharing where we’re stuck more important to furthering research than sharing the answers we’ve found?
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Dr. Kai Arulkumaran of Araya has received a grant from GoodAI in order to apply open-ended algorithms to generating video game content (such as spaceships and space stations) in the sandbox game Space Engineers.
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Researchers at Carnegie Mellon University (CMU)’s School of Computer Science in Pittsburgh are working on a project aiming to make artificial intelligence (AI) more resourceful and curious.
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New project aims to create AI that can continually acquire knowledge in different domains as well as utilize past experiences to quickly adapt to new unseen tasks.
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Self-improving artificial intelligence that can learn new tasks from small amounts of data is a crucial step for the advancement of strong artificial intelligence.
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Current artificial intelligence is limited in its scope and is far from human-level intelligence. One of the key components missing is learning to pursue multiple goals, ones that are dynamic, changing, and that depend on knowledge acquired from previous tasks.
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If we are to develop artificial intelligence (AI) capable of learning as humans do, it needs to be tested in complex environments just like humans are.
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