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artificial superintelligenceFortune
•78% Informative
A 164 -page analysis of this AGI is nigh and superintelligence- ain’t -far-behind argument was published last month by Leopold Aschenbrenner .
He argues every year we see what he calls “effective compute,” a term that includes both the growth in the size of AI models and innovations that squeeze more power out of a model of a given size, resulting in about a 3x increase in capability.
Over time, the increases compound.
Bill Gates said last week that he thought current approaches to building bigger and bigger AI systems could carry on for “ two more turns of the crank” Gates said that we would run out of data to feed these unfathomably large LLMs before we achieve AGI.
Gates said what's really needed is “metacognition,” or the ability of an AI system to reason about its own thought processes and learning.
VR Score
77
Informative language
74
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54
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informal
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English
Language complexity
45
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External references
9
Source diversity
8
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