I agree, but only in the sense that we have created several Frankensteins (dedicated guys with big labs), but none of them has succeeded in creating a decent monster
@plinz
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Tech Companies Must Prioritize Customer Value Over Narratives
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Tech companies concerned about social impact (and the success of their products) should serve customers, not journalistic narratives
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AI Substrate for Mind Uploading and Consciousness Transfer
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But there is an easier path: we may be able to create an AI substrate that is able to support empathetic resonance to such a degree that you could expand your mind into it, reach full self awareness, and move yourself over.
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Mind Upload Limitations: Connectome Data Proves Insufficient
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In practice, if you want a faithful substrate based copy, the connectome is not sufficient. You may have to get data from the soma of cells, scan a lot of RNA and need to digitize not just your nervous system. Substrate based upload may not be a realistic path.
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Mind Uploading and Substrate Independence Theory Debate
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I think there is nothing wrong with what Andy Clark says here. At least in theory, it should be possible to extract the substrate configuration that gives rise to your experience of yourself, and implement it on a different substrate (= upload).
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Consciousness as Pattern: Substrate-Agnostic Identity Construction
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Consciousness itself has no identity, it's a pattern. The traits and memories over which identity is constructed are not easily extracted from the substrate, it's easier to construct a new, substrate agnostic identity
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Hiring for Taste: The Human Element in AI Teams
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That's exactly the point of hiring someone with taste
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Does AI Eliminate More Jobs Than It Creates?
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Do you think gen ai is the first technology that obliterates more jobs than it enables? I understand that there are many people who work in the manual prompt completion industry right now, but is AI not opening up more jobs for prompt engineers?
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AI Alignment Bias: Risks of Homogeneous Thinking in LLM Training
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Ironically, the Gemini debacle illustrates the problems of a lack of diversity. The data that Gemini was trained on is extremely diverse, but the aligners chose to impose a desired bias. If your AI aligners are a homogeneously thinking monoculture that excludes dissent, they fail
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Is AI Geminification the Solution Forward?
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When did that happen? And is the solution the geminification of AI?