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Researchers (Including Google) are Betting on Virtual 'World Models' for Better AI

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2 months 4 weeks ago
"Today's AIs are book smart," reports the Wall Street Journal. "Everything they know they learned from available language, images and videos. To evolve further, they have to get street smart." And that requires "world models," which are "gaining momentum in frontier research and could allow technology to take on new roles in our lives." The key is enabling AI to learn from their environments and faithfully represent an abstract version of them in their "heads," the way humans and animals do. To do it, developers need to train AIs by using simulations of the world. Think of it like learning to drive by playing "Gran Turismo" or learning to fly from "Microsoft Flight Simulator." These world models include all the things required to plan, take actions and make predictions about the future, including physics and time... There's an almost unanimous belief among AI pioneers that world models are crucial to creating next-generation AI. And many say they will be critical to someday creating better-than-human "artificial general intelligence," or AGI. Stanford University professor and AI "godmother" Fei-Fei Li has raised $230 million to launch world-model startup World Labs... Google DeepMind researchers set out to create a system that could generate real-world simulations with an unprecedented level of fidelity. The result, Genie 3 — which is still in research preview and not publicly available — can generate photo-realistic, open-world virtual landscapes from nothing more than a text prompt. You can think of Genie 3 as a way to quickly generate what's essentially an open-world videogame that can be as faithful to the real world as you like. It's a virtual space in which a baby AI can endlessly play, make mistakes and learn what it needs to do to achieve its goals, just as a baby animal or human does in the real world. That experimentation process is called reinforcement learning. Genie 3 is part of a system that could help train the AI that someday pilots robots, self-driving cars and other "embodied" AIs, says project co-lead Jack Parker-Holder. And the environments could be filled with people and obstacles: An AI could learn how to interact with humans by observing them moving around in that virtual space, he adds. "It isn't clear whether all these bets will lead to the superintelligence that corporate leaders predict," the article concedes. "But in the short term, world models could make AIs better at tasks at which they currently falter, especially in spatial reasoning."

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