Geoffrey Hinton
PersonRelationship Network
HOUSE_OVERSIGHT_016935.jpg
This document discusses the philosophical and practical differences between traditional computing and modern machine learning, highlighting the "black box" nature of deep neural networks. It expresses skepticism about the near-term feasibility of Artificial General Intelligence (AGI) due to our limited understanding of the human brain's complexity and consciousness. The text emphasizes the necessity for collaboration between AI researchers and neuroscientists to advance both fields, citing examples of prominent figures who bridge these disciplines.
HOUSE_OVERSIGHT_016876.jpg
This document discusses the growing awareness of AI risk among researchers, comparing the current discourse to historical political dissent and the development of the atomic bomb. It highlights that while 40% of experts view advanced AI risks as significant, corporate interests and scientific curiosity often hinder acknowledgment of these dangers. The text urges immediate attention to these risks without waiting for full consensus, using an analogy of a bomb threat on a plane.
HOUSE_OVERSIGHT_016352.jpg
This text explores the philosophical and practical distinctions between human cognition and machine learning, expressing skepticism about the imminence of Artificial General Intelligence (AGI) due to our limited understanding of the human brain. It highlights the "black box" nature of deep neural networks and argues that future advancements in AI will require closer collaboration between computer scientists and neuroscientists. The author cites the complexity of simple human tasks and the backgrounds of leading AI researchers to support the need for interdisciplinary study.
Discussion 0
No comments yet
Be the first to share your thoughts on this epstein entity