Academician Dai Qionghai proposes building next-generation artificial intelligence based on brain science
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Academician Dai Qionghai proposes building a next-generation artificial intelligence starting from brain science, using cognitive computing as a bridge, supported by multimodal circuit observation and multilevel cognitive models. He states that current AI has limitations in robustness, transferability, energy efficiency ratio, and adaptive capability, and uses the Moravec paradox to illustrate that robots find it difficult to understand the relationships between scenes and objects. At the observation level, Tsinghua University uses the RUSH-II whole-brain imaging system to observe neuronal connections and has built the PANDA, a billion-pixel large-scene multi-object data platform.
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- 机器人全球资讯 · 微信公众号Academician Dai Qionghai: The Future Understanding and Creation of Artificial Intelligence
Academician Dai Qionghai proposes building a new generation of artificial intelligence starting from brain science, with cognitive computing as the bridge, supported by multimodal circuit observation and multilevel cognitive models. He points out that current AI has limitations in robustness, transferability, energy efficiency, and adaptive capability, and uses the Moravec paradox to explain why robots struggle to understand scenes and object relationships. Tsinghua uses the RUSH-II whole-brain imaging system to observe neuronal connections and has built the PANDA 1-billion-pixel large-scene multi-object data platform.
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