It's a bit philosophical, but The Abstraction Fallacy: Why AI Can Simulate But Not Instantiate Consciousness (https://buff.ly/l9C82XG) makes some interesting observations on how good AI can really be. Long paper, good argument to have over a beer.....
AI Abstraction Fallacy: Can AI Simulate Consciousness
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"Eleven Principles of the AI Coexistence Era: Principle 10" This piece reflects on using AI to deepen human thinking, creativity, and mutual understanding through careful judgment and literacy. From a Medium note: https://ift.tt/C0laIcM
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Academic, practitioner, and platform research all found the same thing: what makes AI systems cite your site. We synthesized all three streams to cut through the noise. See what your site's missing → https://lnkd.in/gtzg7N-Z
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The AI Office - Strip#8 The Myth Of AI Reasoning AI reasoning is just math disguised as conversation. It’s not conscious thought; it’s just high-dimensional probability in a suit. #GenerativeAI #MachineLearning #LLM #AIEthics #DataScience
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Most of the AI conversation right now is still about productivity — faster drafts, faster decisions. That framing isn't wrong. It's just not the most useful one. The more useful question is who is actually getting better outcomes because of AI. And how far that radius reaches. Next Tuesday: the framework that finally cracked it open for me — six layers of AI maturity and the diagnostic question that goes with them.
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In French, to know something from the inside — really know it — is savoir. A distinctly different version of knowing more aligned with familiarity is connaître. We should understand the difference as the praises ascend for the potential of the future benefits of AI. To truly know, in the savoir sense, is not something possible with technical advancements such as AI. I like the analogy of automatons*. They appear to be humanistic in their performances but we know they lack the ability to internalize and synthesize thoughts from their societal, cultural and everyday experiences. They are mimetic in every way. https://lnkd.in/eYcD3KAj
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New from Anthropic: Teaching Claude Why. The shift from "give me the answer" to "show me the reasoning" is one of the most important things happening in AI right now. Transparency builds trust. Trust drives adoption. https://lnkd.in/gF2y46hx
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America is winning the AI race. But the lead is more fragile than anyone wants to admit. Anthropic just published a paper outlining two versions of 2028. One is genuinely good. The other keeps AI safety researchers up at night. Here’s what’s actually at stake 👇 Link : https://lnkd.in/dyaCv2Xr
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Don’t be distracted by human knowledge, as AI has been historically. Instead focus on methods for creating knowledge that scale with computation, like search and learning. - Richard Sutton
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If you're going to use AI, here's the minimum quality control you should do: use AI to vet the AI's output. Specifically, ask (1) What factual errors are present in this text? Provide literature citations to support that belief. (2) What references don't exist? (3) What citations contradict or misrepresent the cited source?
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