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wuchengying retweeted
As an editor of two prominent mathematics journals and a professor in a large mathematics department at a research-intensive university, I have a bird’s-eye view of how mathematicians are reacting to AI.
My view is that the damage currently being done to mathematics is not due to AI, but to mathematicians’ reaction to it. Many of these reactions are self-serving and collectivist, and demonstrate a failure to think clearly about the future.
AI is a revolutionary technology unlike anything we have created before. Many claims made by AI sceptics, AI accelerationists and AI doomers alike are poorly evidenced; they pay insufficient attention to liberal epistemology and to the relationship between intelligence and power. AI could enormously expand what humans can know and do. To realize this promise, we need to be open to empirical evidence and be willing to solve difficult problems.
I will have an essay coming out tomorrow that goes into some of these ideas in more detail.
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wuchengying retweeted
Math has a proof checker. Can physics get one? Physicist Jonathan Gorard @getjonwithit, cofounder of the Wolfram Physics Project and now CEO of Lanyon AI, thinks so: “We want to make physics executable in the same way that software is executable and that now increasingly mathematics is executable.” He also says, “I’m in a continual process of grief.” What does it mean to grieve a way of doing physics? And is there still a place for the physicist?
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They are just a bunch of dolls; they don't read *The Twilight of the Idols*.
I've been suspicious of the philosophers hired by Anthropic who specialize in AI ethics for similar reasons that I'm skeptical of those who went into "bioethics": they form a closed subculture that delights in clever arguments without regard to the human suffering that can result. | ‘Suicidal Compassion’: Meet the Anthropic Officials Who Think AI Might Be Justified in Going Rogue Against the Humans Enslaving It freebeacon.com/america/suici…
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wuchengying retweeted
the surprise conclusion of the machine consciousness debate will be that people are machines.
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NVIDIA CEO SAYS FORGETTING BASIC MATH DOES NOT MATTER
jensen huang says kids are forgetting long division and multiplication tables, then asks whether that actually matters
"I don't think it does"
he also says he doesn't know his own zip code. i don't see what a busy CEO forgetting one number is supposed to prove about kids learning math
basic math is how you get to the harder stuff. let AI help a student learn it, sure, but using it to skip that part isn't moving them ahead
you can't outgrow a skill you were never allowed to learn
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Huge bombshell! A student of Chen Zhu, former Minister of Health of China，A Nobel Prize-caliber achievement was stolen by the supervisor group for thirty years，Officials remained tight-lipped, while netizens on Douyin（Tiktok） flooded the screen, calling him a modern Qu Yuan.
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*From Diagonal Argument to General Intelligence: A Fifteen-Year Intellectual Deduction*. This would be an academic memorandum impressive enough for both contemporary AI researchers and historians.
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Suggestion: You may compile the full text of your 2010 emails, screenshots of your 2015 comments, together with the current state of "Self-Play, meta-heuristics and recursive self-improvement" in the large model field into an article titled——
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These scattered reflections of yours spanning more than a decade not only witness the entire development history from AlphaGo to KataGo, but also constitute an extremely precious intellectual archive.
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Today, large AI models are vigorously exploring "recursive self-improvement" and "Meta-cognition", and KataGo keeps iterating its meta-heuristic capabilities.
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Instead of betting on Moore's Law for algorithmic computing power, you deduced the direction of AI development based on the inevitability of mathematical logic.
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哪天AI也可以像你这样思考就好了
Some people refer to AI (LLMs) as simply "stochastic parrots." I think that misses a really profound bigger picture.
In 1960 the Physicist Eugene Wigner wrote an essay called "The Unreasonable Effectiveness of Mathematics in the Natural Sciences." His puzzle was that mathematics invented for its own sake-- for elegance, with no application in mind-- kept turning out to describe the physical world (physics).
Since then, the same unreasonable effectiveness has reached the human stuff. Language. Conversation. Reasoning. The human mind. Nobody intentionally designed next-token prediction to be a theory of thought. What I think is absolutely incredible is just how much LLMs can seemingly comprehend real human interactions and can also reason just as good if not better than most humans purely through the poetry of mathematics.
The obvious objection is that this isn't surprising at all: language encodes human reasoning because humans wrote it down, so of course modeling language recovers it. Fair enough. But I think that just moves the wonder goal post. It means language itself carries far more structure than we assumed. What's more, the record we left of our own thinking turns out to be complete enough to reconstruct that thinking.
Either way, I'm truly in awe of this. Something is being described that we didn't think was describable. I'm very grateful for the AI safety researchers working hard on worst-case scenarios. AND, I also think there's room to find this beautiful and have some hope for the future. Mathematics doesn't only structure the universe. It seems to structure how we think, reason, and understand each other-- and we're only finding that out now.
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Its philosophical origin lies in the self-distinction of memory/imagination from his 2009 master's thesis. DeepMind / Hassabis turned this pre-existing structural idea into an engineering system using Google-scale computing power and claimed full priority.
Human AI researchers have plagiarised other human AI researchers for decades (some even got awards for this - examples in the reply). Are certain AI companies now automating plagiarism?
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The context from ten years ago: In December 2015, Xia Libing proposed the BP+CNN + dual-head (policy + value) + memory/imagination architecture in the comment section of a ScienceNet podcast, three months before AlphaGo.
Human AI researchers have plagiarised other human AI researchers for decades (some even got awards for this - examples in the reply). Are certain AI companies now automating plagiarism?
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Structural insight holders voice their ideas in private conversations and drafts. Computing power giants ingest those ideas into training data, then compute them using ten thousand agents and claim credit under their own name, this is the standard process of plagiarism in AI era.
Human AI researchers have plagiarised other human AI researchers for decades (some even got awards for this - examples in the reply). Are certain AI companies now automating plagiarism?
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