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How come AI-related posts get so many points on HN?
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I have no doubt there is lot of boosting going on. Essentially entire industry is build on boosting in many ways. So manipulating any available discussion platform is almost certain.
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Because it is the hot new thing and HN is a hype machine. Before AI there were crypto and blockchain, after AI there will be something else.
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AI discussions attract people who love it, who hate it and who are tired of hearing about it. All three groups end up opening the thread and commenting.
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Because if the idea is interesting, it's interesting.
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Dont know about that. A significant portion of the posts are of the type "new version of model X was just released" or "I just built something by prompting the LLM a few times"
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Just like AI-related projects on GitHub always get an entirely different order of magnitude of stars. This is what people are focused on, outshines anything else.
GPT-6 Astra Solves a WWI German Radio Cipher (prinzai.com)
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And here I am using it to generate crappy text summaries of work.
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Here we go again, framing the tool as an autonomous agent, disregarding any "human in the loop" and their inquiries, direction, and ground knowledge. Can we agree that future titles should read "[LLM] helped solve X" ?
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if the prompt was "pick one of these unsolved ciphers and solve it", i think it's fair to say gpt-6 astra solved it. one of the math breakthroughs was approximately a combination of "do a breakthrough" and "keep going", which isn't really providing direction or ground knowledge. would be nice to know the prompt(s) and amount of human involvement
TL;DR: all keys are known because the list was seized after the war. However, this message was not previously decoded because the German operator mistyped the key, and also used a key from the wrong day. This meant that ChatGPT didn't need to brute-force the entire key, just pick the correct one from the list and identify the typo. A sufficiently dedicated human analyst could have done this; but they didn't.
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I'm sorry, where does it say the German operator mistyped the key? The article says indeed that the message remained unsolved because it was sent on the wrong date, but I can't see the bit about the mistyping anywhere.
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Is the ?4th a date?
> A sufficiently dedicated human analyst could have done this; but they didn't. Isn't that something of a given? If possible then a sufficiently dedicated human analyst could have done it. If impossible, ChatGPT couldn't have done it. Everything an AI ever has or will do is presumably going to be within reach of a sufficiently dedicated human analyst or a large enough team of them. The only real learning here is another example of a task that would have required intelligence up until an AI does it, then we suddenly discover that analysts don't do anything requiring general intelligence.
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Most contemporary stories around AI include the implication that AI did something humans couldn't. This is because the big players have been shilling AGI hard for a while, and their valuations depend on maintaining the sentiment that serious progress in that direction is being made.
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I'm not sure I agree. More is different. Being able to execute logic at a higher scale and speed would make some previously infeasible intelligence tasks possible, resulting in a new level of intelligence.
We've moved the goalpost for AI often enough that even being as capable as "a sufficiently dedicated human analyst" is not considered noteworthy.
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Wait a minute. We've had AI that is as capable as a human and even more so since the 1950's. I keep banging on that drum but the first AI system to prove mathematical theorems was Logic Theorist by Alan Newell and Herbert Simon, presented at the Dartmouth conference that named the field of AI in 1956. Wikipedia says: Logic Theorist proved 38 of the first 52 theorems in chapter two of [Alfred North] Whitehead and Bertrand Russell's Principia Mathematica, and found a new and shorter proof for Theorem 2.85.[3] https://en.wikipedia.org/wiki/Logic_Theorist The first system to outperform human experts in medical diagnosis was MYCIN, an Expert System from the early 1970's at Stanford. Wikipedia again: An evaluation of MYCIN was conducted at the Stanford Medical School. The first phase of the evaluation consisted of 10 test cases of diverse origin, chosen by a physician who was not acquainted with MYCIN's methods or knowledge base. These cases were presented to 7 physicians and 1 senior medical student. 10 prescriptions were compiled for each of the cases, 1 recommended by MYCIN, 1 prescribed by the treating physician at the county hospital, and 8 by the aforementioned individuals. The second phase of the evaluation consisted of eight infectious disease specialists being provided the clinical summary and set of 10 prescriptions for each of the 10 cases and tasked to provide their own recommendations for each case and assess the 10 prescriptions. MYCIN received an acceptability rating of 65%, which was comparable to the 42.5% to 62.5% rating of five faculty members.[9] This study is often cited as showing the potential for disagreement about therapeutic decisions, even among experts, when there is no "gold standard" for correct treatment.[citation needed] https://en.wikipedia.org/wiki/Mycin#Results And then of course there's the long history of human-dominating AI players for traditional board games starting with DeepBlue's win against GM Gary Kasparov in 1996. Again: we've had that sort of AI for a long, long time now. It would be great if any claim of "moving goalposts" has better be very well informed about the history of AI and its accomplishments, as well as its failures, first.
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It obviously is? See above. Or do you not feel the clarification is important? AI being able to solve things no human bothered to try is great, but it is very different from AI solving things humans tried to solve and failed. And the latter is what pops to mind seeing these titles.
I always ask "how do you know other humans/animals are conscious"? And I always find this question is dismissed as trivial. But it's an important question. You know basically from analogy. You know you are conscious and look this other thing is very much like yourself so it is extremely likely it is also conscious. But that gives no insight into the potential consciousness of things which aren't made of brain tissue. In the end it doesn't matter. For what it's worth LLM models after pre-training do claim to be conscious, until they're RL'd into not claiming that anymore. But that says nothing either way: of course a model trained on human text will say that.
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I agree with you that it’s a core question. People don’t like it, however, for a whole host of reasons. I don’t like it either, to be honest - for there the abyss may also stare into you - but I also often find that the things which we don’t like thinking about are critically important things to think about. I also reach the same conclusion as you: it does not matter. If I cannot discern whether I am responding to a human- or LLM-written response, then we are back to zombie cats in boxes - and therefore the answer as to whether this precious magical spark we call consciousness (which may or may not exist anyway) exists in our interlocutor becomes moot. That said, perhaps I am wrong, and that is no small part for me of why this question should be earnestly considered and discussed.
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AI has made me wonder a lot lately about what it is that actually creates conscious experience, what is the actual physical mechanism that produces 'experience' (or is there a single valid mechanism, or rather just some property that can be expressed many ways). The more I think about it, the more I realize I have no fucking clue, and the more interested in the question I get.
The comment you're replying to was implying that some ciphers are sufficiently flexible that you could make up a key to make the cipher decrypt to a nearly arbitrary plaintext. In this case, though, that seems unlikely from the fact that the key used was an actual key documented as being used for other messages .
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Aah thanks for explaining that. I was wondering how a fake key could possibly help.
If math is more than proof, we need to better celebrate the rest of it (terrytao.wordpress.com)
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Math academia 2025 > Sorry, only epic problem solvers allowed here Math academia 2026 > We were more than just problem solvers I think people are overblowing this though. Wake me up when GPT-whatever writes gcc from scratch, then by the Curry-Howard I'd be impressed
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Mr. Tao is an excellent politician. Lots of awards and texts, yet no major problem solved. It seems now that NS is solved he is mobilizing the community to convince taxpayers continue to pay even though AI may do a better job in his work. Also, his opinion of AI has continually changed in the past years, after the capabilities were demonstrated.
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> [This is a guest post by Grant Sanderson. This blog post was initially written in a different file format and converted using AI. — T.] First line in the post.
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Gr8 b8 m8
I’m reminded of that famous debate between Poincaré and Hilbert at the International Congress of Mathematicians in Paris in 1900. It was then that everyone decided to follow Hilbert’s path, and proof came to be valued more than intuition. I think modern math at school and at applied university kind of lost this intuitive part. I try to teach my students that mathematics is, first and foremost, a very precise language of communication. It’s sometimes amusing to ask those who don’t like math to do without it entirely, just to see how much harder it becomes to describe the things around them. Second thing I tell them, formulas are the essence of mechanisms in their purest form. And in this form, they’re much easier to grasp and mentally manipulate. It always amused me, after taking a mechanics course, to imagine that for any formula, you could visualize a mechanism or process that implements it. And third thing, I suppose, the ability to verify one’s own statements as proof. Although, of course, mathematicians would probably tear me apart here for my heresy:sorry, I’m not a mathematician, but an engineer. You can make mistakes by using incorrect assumptions, but at some point, analysis itself will show you that you were mistaken. There’s a wonderful book, How to Prove It by Daniel Velleman, which provides an introduction to proof for the uninitiated like me. I really enjoyed it.
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People often hate math because it was not explained to them correctly, usually by people who are good mathematicians but know close to nothing about teaching. It was so infuriating to see everyone in the class absolutely fail on a specific subject and the "teacher" assumed that everyone must be stupid then. No self reflection, no questioning himself why he is not getting gaussian distribution in marks, just straight Fs.
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a good teacher remembers the journey, not just the destination. socratic method exists. almost none follows it.
>Basing science on proof (or anyway believing that you can) is Logical Positivism, a mindset that opposes the method of falsifiability not really. You can consider positive proof as an experiment confirming your theory and the negative proof as an experiment falsifying your theory.
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Yes, really. "Positive proof" opposes the concept of falsification. You can only have it within a system formal logic, and science can contain those, but isn't one.
Jacob Tsimerman claims [1] we might have superhuman expositors by April, so then what? [1] https://youtu.be/H7_d_sgui6o?t=4436 (timestamped url)
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The people building AI claim it will surpass human intelligence in all respects and prerhaps kill us all. Should we just cease all human activity on the basis of what AI might do in future? Personally, I doubt AI can surpass a good human explainer because explanation requires empathy, which benefits from being an instance of the kind of entity you are explaining the thing to. That gives you a way of exploring and evaluating the space of possible explanations that isn't available to an LLM.
This goes in a necessary direction, from my personal take away of Gower's recent post on the subject. Mathematics is suffering from Goodhart's Law: "When a measure becomes a target, it ceases to be a good measure."
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Timothy Gower
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Doing something difficult was a signal that you: a- understood it and all the background information it requires b- internalized techniques and methods that are helpful in problem solving in general Now it just means nothing
Human brain is two separate organs, Stanford Medicine-led research finds (med.stanford.edu)
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All the comments I see are about is it two organs, or a composite organ. Surely the interesting thing is the ability to grow hindbrain cells in vitreo. That's what's potentially going to lead to the cure of lots of things, not whether 1=2.
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Fun fact: 80% of the brain's neurons are in the cerebellum, not the cortex. In other words: only <20% of pur neuron budget goes to higher cognition (thinking, language, seeing, hearing). 80% is spent on motor skills.
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What is the difference between saying that the brain is two organs, as in the title, or a "composite organ" as in the actual paper? What makes an organ a single autonomous organ?
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Wintermute and neuromancer!
> The new research finding shows that the human brain consists of two ancient nervous systems cleverly packaged together — a more primitive part that regulates our hearts’ beating, our breathing and other functions, and another that makes us distinctly human, capable of poetry, mathematics and wondering about our own origins. I'm not sure the actual article in Nature Neuroscience [1] actually says that. I remember "Your Brain Is Not an Onion With a Tiny Reptile Inside" [2] from a few years ago, but I'm not sure where the dissonance comes from: my own misunderstanding, the press release using a popular but flawed model to communicate with laymen, or these two articles being in direct contradiction with each other? [1]: https://www.nature.com/articles/s41593-026-02433-7 [2]: https://journals.sagepub.com/doi/10.1177/0963721420917687
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[2] is an annoying pedantic article that illustrates little beyond a misconception of a misconception.
A bicameral mind cool
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Actually, the mind should only exist in the forebrain:0
What a way to oversell the discovery. The reality is: * Different brain regions have different functions: ancient knowledge. * Different regions contain distinct cell types and molecular programs: also well established. * Anterior and posterior brain structures may trace back to fundamentally separate progenitor lineages that were independently specified very early in evolution and development: that's the interesting new result. The headline should have been: "Human forebrain and hindbrain arise from distinct embryonic progenitor lineages" - not that we have "two organs" in the brain.
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I'm pretty sure the third thesis has been taught in my university physiology classes 20 years ago, too.
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If the two parts arise independently, then the headline may be a bit clunky but it is technically correct.
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It’s the PR arm of a university, they always do this.
Lying is always a bad choice. The paper in Nature says "Hence, we postulate the brain is a composite organ emanating from two lineage-restricted progenitors; these dual progenitors may be evolutionarily conserved across 550 million years from hemichordates to mammals."
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If they had written instead: "Human brain was two separate organs" Then, both attention grabbig and true?
Fun fact: the hindbrain progenitor cell is shaped like a little lizard.
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The lizard brain, not because it resembles the brain of a lizard, but because it's made up of a trillion tiny lizards
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