AGI Progress Stagnation
Despite significant investments and advancements in AI, the same fundamental challenges persist, echoing concerns from 2021. The need for rich cognitive models, common sense knowledge, and better reasoning remains critical. A recent paper explores the transition from generative to trustworthy AI, emphasizing lessons from psychology. The historical context of AGI's development reveals that, even after nearly seven decades, true AGI still feels distant.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Gary Marcus' keynote at AGI-24
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