Imagine an AI that thinks like a human brain—only smarter and way more energy-efficient. That’s the breakthrough just achieved by researchers in China! Scientists from the Institute of Automation, Chinese Academy of Sciences, teamed up with Tsinghua and Peking universities to develop a brain-inspired AI model that could revolutionize tech’s sustainability game.
Traditional AI systems guzzle energy like a Netflix marathon , relying on massive neural networks (think: the 'Inception' of computing). But this new approach flips the script. Inspired by the brain’s internal complexity—how 100 billion neurons work together on just 20 watts (like a lightbulb!)—the model tackles tasks efficiently without draining resources.
Why it matters: Current AI methods, which prioritize 'external complexity' (bigger networks = more power), are hitting limits. 'We’re mimicking the brain’s genius,' says researcher Li Guoqi. Their experiments showed the model can handle complex jobs while staying energy-lite—a win for green tech and smarter machines.
Could this blend of neuroscience and AI lead to eco-friendly robots or climate-solving algorithms? The team’s Nature Computational Science paper says it’s a leap toward 'general intelligence' that doesn’t cost the Earth—literally.
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That’s the breakthrough just achieved by researchers in China! Scientists from the Institute of Automation, Chinese Academy of Sciences, teamed up with Tsinghua and Peking universities to develop a brain-inspired AI model that could revolutionize tech’s sustainability game.
, relying on massive neural networks (think: the 'Inception' of computing). But this new approach flips the script. Inspired by the brain’s internal complexity—how 100 billion neurons work together on just 20 watts (like a lightbulb!)—the model tackles tasks efficiently without draining resources.
Why it matters: Current AI methods, which prioritize 'external complexity' (bigger networks = more power), are hitting limits. 'We’re mimicking the brain’s genius,' says researcher Li Guoqi. Their experiments showed the model can handle complex jobs while staying energy-lite—a win for green tech and smarter machines.
The team’s Nature Computational Science paper says it’s a leap toward 'general intelligence' that doesn’t cost the Earth—literally.
