I've been saying this since using Databricks at a company almost a decade ago. Most folks do not need big data tools, and it's just so entrenched because everyone wanted to be a "big data" company and pandas was how you handled big data.
I'm with @nilesh on this one, and not exactly sure how merely the existence of a solution precludes the advancement of human knowledge. If a problem is "solved" (say, symbolically verified) without any insights gained, it doesn't seem very interesting to the profession.
Navier-Stokes is a bit different (because there's a prize attached, so "scooping" matters), but almost all interesting problems don't have any prizes attached.
Humanity is very biased for the culmination of work, considering everything that comes before and after busywork for the lower masses.
Replicating a paper is just as valuable scientifically as publishing it, but how many careers advance through replication?
If we move the goal from "find the solution" to "clear up the LLMs work" that doesn't bode well neither for the attractiveness of the problem nor for the career of the professional that takes the challenge.
> Replicating a paper is just as valuable scientifically as publishing it, but how many careers advance through replication?
A lot. In fields where knowledge is incrementally building on previous work the reason the whole field hasn't collapsed from the replication crisis is that usually the results that are really high impact are replicated in as an initial step in new research building on it. It's almost never the focus of the paper but you'll often find a quick mention in methods/supplemental of some previous work that was verified to be valid by a replication of a key technique etc. you'll have crisis where old tools are found to be problematic and findings end up revisited etc. Plus fields like clinical research where there's an awful lot of focus on replicating findings using staged clinical trials with increasing statistical power to determine if new interventions work - that's driven by regulatory requirements grounded in good science and a lot of people make careers in just that.
In mathematics, finding novel proofs of a given result is often valuable; it may be a shorter proof (demonstrating better/expanded understanding of the problem) or a translation of the problem into a new domain, setting up more cross-domain advances.
>Replicating a paper is just as valuable scientifically as publishing it, but how many careers advance through replication?
I don’t think this is true, especially for novel or unexpected results. I suppose it depends on what you mean by scientifically, and there is a debate in the philosophy of science about what the value of research even is, but a successful replication does not result in substantial updates to one’s beliefs in the way new research does. And if the goal of science is to change our beliefs and bring them closer to what is “real”, successful replications can’t be as valuable as the initial research almost by definition.
From a pure statistical perspective the first scientific paper shouldn’t update your beliefs as much as the independent replication study.
People don’t behave this way, but a high percentage of all papers have known flaws and that goes up even higher when you consider unknown flaws. Replication doesn’t own its own solve the underlying issue, but independent replication removes a huge range of potential issues on top of providing more information.
I agree, with the caveat that it probably matters how novel the paper is, the effect size, and the confidence interval. A reputed new psychological phenomenon I'd be more skeptical of than, idk, a newly detected exoplanet.
That alleged superconductor from a few years ago - everybody kind of held their breath and waited for the reproduction.
You have created a fraud machine. Why? With no answer checking then why not make up the most fraudulent crap you can get away with?
Examples: A huge portion of recent non-reproducable science papers.
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Your thinking, along with everybody that's doing this rat race is causing the pumping out of papers with questionable data, but very little to ensure we are actually making correct science.
I find that to be an issue of maturity (focusing only on the climax and not the process). In Japan, where I live, the culture has a greater appreciation for the context & process, not just the moment of victory.
If you examine the consequences of the inversion of the peak, you realise the need for a balanced perspective.
> An AI-generated solution always provides ... proof that there is a solution
This is only true in the most trivial sense. A solution is a solution, sure... but how do you know it's a solution, and not an incoherent jumble of words? A human has to review and vouch for it.
Just because the AI gives you an arxiv-worthy PDF, or a Lean proof which compiles, doesn't mean it proves what the AI says it does. The AI could give you the same PDF/Lean code and says it proves the opposite, how would anyone know the difference?
You can't advance human understanding unless you produce things that humans can understand.
Not an expert by any means but the assumption here as I understand it is that the arxiv worthy PDF would not be acceptable or meaningful for impossible to understand proofs. And the lean proof would be meaningless unless the specific expression being proven is human understandable as the direct translation of the question the human is asking in formal form. So proving the negation is not a thing but if you make a subtle mistake in translating the statement you want to prove then obviously the QI is going to be proving the wrong thing. And otherwise you're relying on the correctness of lean as a system and on identifying/preventing if the proof is adversarially exploiting bugs in lean to falsely prove things.
> Just because the AI gives you an arxiv-worthy PDF, or a Lean proof which compiles, doesn't mean it proves what the AI says it does. The AI could give you the same PDF/Lean code and says it proves the opposite, how would anyone know the difference?
> You can't advance human understanding unless you produce things that humans can understand.
And you can't advance human understating unless you maintain that understanding.
I can see a version of the junior software engineer problem here: AI wrecks the problems that could train and motivate the next generation mathematicians, so students abandon the field because there's no place for them. The senior mathematicians who can review/vouch/prompt for AI output like Tao retire and die. Then there's no more math that anyone can understand and no more open problems for it to solve.
And that's probably happening already. I've read articles about AI performing the journeyman work that mathematicians cut their teeth on, rendering years of work obsolete, and derailing the careers that work was meant to start.
I might be wrong, but making an assumption that you could learn to read the mathematical output of the AI long before you could write a solution yourself. But hey, what do I know, I'm not a mathemagition.
This is definitely true in an information theory sense: having more knowledge is always better than less knowledge. However, it may not be true in math as a social human endeavor, and having answers without interesting paths to get there may not expand human mathematics in the same way.
If Fermat had a book with larger margins, would Weil have devoted so much time to proving the Taniyama-Shimura conjecture? No one can say.
Were early in this cycle, we will learn to do more, and exercise our new capabilities more fluently, which in turn will create more skilled practitioners
Consider the abacus, calculator, computer, etc, each of these enhanced mathematicians’ capabilities and thus outputs.
> Mathematicians will be less likely to work on a problem if there is a solution
Yes, that is Tao's premise, I'm just not sure I buy it. Suppose an oracle existed which could answer any question truthfully. Let's ignore the mechanics of this for now, but it could say things like "the Riemann hypothesis is False" or whatever and we would take it as gospel.
Does this mean that we wouldn't have mathematicians or physicists or computer scientists or biologists anymore? I genuinely don't think so.
I think his point is that AI is not creating new problems. It may solve "the Riemann hypothesis" but may completely fail to posit a "Mythos hypothesis" which is vital to advance the field. In fact, achieving the former may make the latter even harder because it will disincentivize production of human mathematics which has till now been the only source of "interesting" problems.
FWIW this is my understanding of his argument and I am not a mathematician.
As Tao points out, merely suggesting new open questions isn't really sufficient. Part of what gives these problems their fame is their notoriety, their difficulty, the fact that many prodigious mathematicians have spent an evening or week or month or several years studying it.
It wouldn't be as interesting if it had just been solved by the fifth random mathematician who considered it
Notably, gardening a new field of study in math is somewhat nontrivial. You have to introduce the field, illustrate some relevance or connections, and then - and this is key - not solve all of the low-hanging fruit yourself! Because you need somebody else to become an expert in that particular field.
The analog in programming is: if a large company merely open sources a product that's decent but not great and in a language nobody wants to maintain, but they don't commit to maintaining it themselves.
Suddenly there's a bit of a vacuum because in order to provide something of value, you either need to:
1. Implement something more complete than was initially open sourced
2. Or maintain something in a horrendous language while incrementally improving it and keeping it relevant
3. Or rewrite it into a tolerable and maintainable modern language.
What the large company has done is create a vacuum in the tool space where you now require extreme motivation to get someone else to step in.
Note that in this scenario, in 2026, it's actually not such a big deal. I think several recent models could happily translate it into a more maintainable language themselves or happily maintain it in the original crufty one. And so the question is: which parts of this analogy are true in math, too?
Yes, these things are definitely being conflated and there's a fourth conflated thing I think Tao is particular getting at:
(4) Mathematics, the community which is a living system that decides what is interesting, constructs shared frameworks, transfers ideas between domains, develops taste, teaches new mathematicians, and continually emphasizes what counts as important mathematics, especially in it's overall value to humanity.
This is the level in which theory building, simplification, integration and applications are built on. Contributing meaningfully here requires much more than generating solutions - it requires direction and restraint.
Tao seems to be saying that this direction and restraint is the scarce resource that drives mathematical progress, not problem-solving ability. And AI is not only insufficient at it, but results generated by AI are destroying human ability to excercise this resource.
This seems similar to another problem AI sucks at - drafting legal agreements. Despite being great at evaluating, interpreting, and comparing legal agreements it fails amazingly at drafting them. This is because what you don't say/do is vastly more important than what you do say/do.
And AI is great saying and doing things, it's the selection based on implied values that it struggles with.
You pick your axioms and you see what must be true. With math and logic, we can reason about any possible universe even though we live in only one of them.
The sphere of human comprehensible mathematics is finite. Once everything is solve it is not necessary to advance the field. The recurring error her is to say ai is not the product of human effort but another agent. Ai is human. Ai may well be speeding up human comprehension of math to its limits in which case there is no further need to advance the field and mathematicians might need to get a job. Why is this a bad thing?
But this oracle doesn't just say true / false. It also gives a proof. That makes it much less exciting (not to mention beneficial for your career) to find another one (or even worse, the same one).
What do u think lean is? That's like saying a program that works, is inscrutable because it appeals to the oracle of "code test cases" to prove itself correct.
You're either being intentionally obtuse, or unintentionally ignorant.
Have you tried to read the Lean proofs produced for any of the recent high-profile results? They're extremely long, terribly structured, and don't indicate which parts are restating known results from literature and which are unique to the proof at hand. That's what makes them inscrutable.
It's similar to Mochizuki claiming to have proved the ABC conjecture, with a proof depending on ideas developed over a large number of obscure papers, that required mathematicians to spend a lot of time before they felt they understood it well enough to point out flaws.
If AI solves all famous open problems and the non-famous ones, too, without advances in the readability of their output, there'll still be some work to do to digest and rearrange the proofs for human consumption. During that process, the mathematician may well get some new ideas...
For all your bombast, do take a moment to note that no mathematician has actually said openai has not produced a correct solution. Should make you think.
> Does this mean that we wouldn't have mathematicians or physicists or computer scientists or biologists anymore?
In the case of mathematicians, I think not as researchers. What would a research mathematician do? I don't think there would be any reason to try to gain insight from proofs that AI made for the sake of understanding. I don't see what that would achieve besides just retaining extremely niche knowledge (which AI or the oracle already does). The whole point of having that knowledge was to build toward novel work which the AI/oracle does. Also, the time spent and difficulty understanding them could be very high but with no payoff besides just understanding them because the AI/oracle would be used to solve all the problems anyway.
I mean, the oracle doesn't really seem so hypothetical right now. And clearly it's going to drastically change these fields, and mathematics, particularly pure mathematics, must change most of all in order to adapt to the existance of a math oracle (or something close to it).
More of a 'its the journey' rather than the destination type of thing.Since the insights , quirks, tricks and procedures gained along the way allows insights intoother at that moment unknown problem/domains in the future.
As far as researchers sharing their data/notes with the AI hyperscalars looks like that would be coming to an end wihth a mor guild-like structure going forward to prevent their progress being fron-run by the AI labs.
I wonder if it would be possible for researchers and scientists to submit their papers to an organization which would then collect them, submit them for peer review by other experts in the field, and then release them in periodical form ONLY to individuals and organizations who pay a subscription fee in order to read them while suing those who try to redistribute them without permission?
Why would society fund mathematicians if they decided to become a guild that hides secrets? They could pursue that as a hobby, but they’d end up like the coders who refuse to use LLMs - rapidly becoming irrelevant and a bit sad from an outsider’s perspective.
Ah but heres the thing , society/gov expects mathematicians to be productive and tries to measure that by awards/publications/citations gained. Within a guild ope or secret they could possibly use a local LLM (even if slow) to accelerate their collective output.While ensuring their credit/publication/citations remain intact rather than with the AI labs taking a lions share of that.
Think along the lines of the Nicolas Bourbaki persona/collective :
" was a collective pseudonym chosen in 1934 by a group of young French mathematicians. None of them carried the name alone; all of them carried it together. And under that name, they launched the most ambitious mathematical publishing project of the twentieth century: a series of texts rebuilding modern mathematics from scratch, on entirely axiomatic foundations."[1]
Current career structure of mathematicians works partially by looking at whether they have solved novel and interesting problems, or at least done theory-building that can help solve such problems. Many mathematicians are also motivated by being the world's first to solve such problems
Removing this measure suddenly means that academic mathematic norms need to adapt rapidly, and, even more importantly, intrinsic motivation for many mathematicians needs to change rapidly. That is understandably a sea change for the current mathematics community.
Rephrasing the argument made in the post, math was like a "take a book, leave a book" exchange where you solved a problem, and in the process you discover more problems so the pool of interesting open problems is renewed. What OpenAI and the other labs are doing is akin to
- taking all the books in the exchange (which is technically allowed, no rules about how many books you can take)
- destructively scanning them (still technically allowed, no rules about what you do with the book)
- and not leaving any new books in their place (which is frowned upon, but there's no rule that says you have to replace books you take)
Let's say for the sake of argument that an LLM finds a counter example to the Reimann hypothesis. Wouldn't that just create a bunch of opportunities for understanding and explaining _why_ there is a counter example?
This is my question too. If we are all just going “well that sucks” after AI solves this problem, why did anyone care about the problem being solved in the first place?
Is the bummer that we got a solution we didn’t want - that navier-stokes is not always applicable or something, but we hoped it was?
I think the Navier Stokes problem kind of illustrates what he’s highlighting. I think most people even before AI expected that this would resolve in the negative and that you could get finite time blow up. There wasn’t really ever going to be a situation where the resolution to this question, or really any of the other Millenium Prize problems as far as I know, gives some kind of immediate massive practical feedback.
The hope with many of these problems in math is that in trying to prove that, we get some additional insight into why it blew up that could be applied elsewhere to more general PDEs that cannot be easily controlled.
I think the observation from Tao and many others is that when humans solved these problems, the additional insights into intuition and theory building came for free since humans can give expository on what they found hard or what was their own intuition. This is much more difficult or tedious to extract from an AI model. Even when people did have access to the chain of thought, it wasn’t always very helpful to figure out what was the exact thing that made it all click. This is even more difficult how that the CoT are hidden but I would think the sort of difficulty of extracting the key ideas for a human might be worse now with more advanced models.
There’s a long term aspect to this too where we have historically used these problems as markers for the other parts of mathematics but if AI can solve it all, then suddenly this signal is not very meaningful.
Maybe to bring it closer to home. If an oracle just gave you P \neq NP, then this would be generally uninteresting since this was already expected. There’s a deeper question of why that needs to be answered. However, one would hope that creating such a separation would give us tools that allow us to create lower bounds on a lot more problems we do care about and perhaps some bigger insight onto what makes a problem intrinsically hard or easy. These long term considerations are helpful but are definitely more vague. The remarkable part is that AI is separating the part about proving theorems and the “free” insight you get.
Because the mathematicians consulted 25 or so years ago believed their solutions would lead to the greatest amount of interesting new maths to explore, and because they had been validated as being hard by being attempted and not solved for a long time.
Honestly, the attitude of the math community is a bit cringe and increasingly I think some of the elite/mystical aura is fading. Rather than a rich fertile jungle where AI can barely chomp through a fraction of the luscious terrain, one gets the sense it's a desert and all the oases are running dry.
AI companies don't share the dead ends and only sometimes a bit of the process toward success so people don't understand what was curious along the way.
> and not exactly sure how merely the existence of a solution precludes the advancement of human knowledge.
You'd be more sure if you read the tweets.
Tao's point is very simple.
1. Working on problems that AI solvers can solve is a waste of human time.
2. We have no idea which problems can be solved by AI solvers...
3. ...Because the AI labs are keeping their negative results secret, and don't tell us which problems they've tried and failed to solve, and why they've failed to solve them (or succeeded at solving others).
There are additional points surrounding it, but that is the thrust of his argument. His issue is not the existence of AI, but the anti-scientific secrecy in how it is used to solve problems. All the incentives around its current use result in closed, uncollaborative work - which while very attractive to a vulture capitalist, is anathema to scientists.
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He also posits that having a solution to a problem is a small part of the value of solving a problem. What the AI labs are doing is the equivalent of a student turning in their homework, which has 100% of the right answers, but with none of the 'show your work' steps. Those steps are a critical artifact for doing mathematics, because the process of solving a difficult problem teaches us things about other problems.
> perhaps most importantly on what makes humans, human
What makes humans human is love, laughter, community, children, art, beauty. How are LLMs even remotely a threat to this? The piece is so hyperbolic, it's just hard to take seriously
I really feel that the anti-AI crowd is becoming a weird religion, kind of like the crypto NFT crowd was a few years ago. Most people that use AI are just like "yeah whatever, it does X, Y or Z, sometimes it sucks and I have to re-prompt it, it's pretty neat."
While the anti-AI crowd is like "I PLEDGE TO NEVER USE AI, HERE IS MY BLOOD OATH." Like, calm down. It's not that big of a deal. Some of these bullet points are just straight-up nonsense.
> I won’t read AI summaries as a substitute for reading the source material with my own damn eyes.
Author is... just defining what a summary is. Yeah, no one looks at summaries as if they're the original text. Ever. What is he even saying here?
Absolutely opposite experience. People do not shut up about it once they’ve tried it, and come up with all sorts of whacky use cases for it. Best friend suggested I ask ChatGPT whether it’s cheaper to renovate or knock down a house I bought specifically to renovate it, which I’ve told him on multiple occasions.
AI is the successor to all things crypto, there’s definitely religious fervour to it like there was around blockchain/NFT’s changing the world.
> People do not shut up about it once they’ve tried it, and come up with all sorts of whacky use cases for it.
Other than Twitter engagement baiting (which people have done w.r.t. every other new hyped up thing, whether it's drop shipping, SaaS, crypto, whatever), I really don't see this day-to-day.
> Best friend suggested I ask ChatGPT whether it’s cheaper to renovate or knock down a house I bought specifically to renovate it, which I’ve told him on multiple occasions.
I don't understand what this anecdote has to do with AI, it sounds like your friend is just a bad listener.
> What cool problems did you (not the robot) solve?
Building products has nothing to do with technical problems, just the end result. This is in contrast with things like writing a library or coming up with a new algorithm, or doing research, or even writing a technical blog post, etc.
> or is it just pretty?
People have been sharing "just pretty" things on HN for decades. It might be interesting, thought-provoking, discussion-worthy, or whatever. Even if this wasn't vibe-coded, it wouldn't be some monumental technical achievement. Your point is absolutely moot.
> Computer folders are still organized in structures set up some 50 years ago. Operating systems change. Computers change. Search changes. But this has never changed. I can't change that.
And we've been using the Dewey Decimal System for like 150 years. Both are good systems. Kepter (a visual/gallery system) would break down when looking at more than a dozen files (or when files are very similar). I don't really think it's a good idea.
What we desperately need is a system-wide (or at least documents-wide) semantic/vector search, which is basically a weekend project and a $4.99 one-time purchase.
> So unless you're willing to become a literal terrorist organization and die with a bunch of your friends in an uphill battle (not technically unwinnable, but at least lopsided and the casualties will be tremendous), the only option is to cave.
Honestly, the internet has made folks so lazy. It's very ironic that the most "revolutionary" act taken recently (January 6) was actually done by the far-right. Yeah: if you believe in something, you need to actually get out of the basement, grab a gun, and storm the Capitol. And if you take it all the way, a lot of people are going to die. That's how revolution works. Unless we're all LARPing?
But Americans/Westerners (left, right, center) are way too comfortable for a revolution, so for people that are, or have been, actual dissidents (think Arab Spring, or IRA, or ETA, or whatever), this is all just a big meme.
If everyone is so comfortable, what do we need a revolution for? Wasn't that the goal of civilization? If someone doesn't like civilization, why try to bring it down? There's plenty of places on earth you can go to live without it.
Most people are comfortable, but not everyone. At least, comfortable in the sense that they are not willing to die for their country/people at the moment, and aren't personally affected by most of the bad things their government does. In the US at least, things like high food/gas prices or unemployment/healthcare issues are just one of many other issues, and aren't causing most people so much pain that they are willing to pick up a weapon and give up their lives. Or even peacefully protest.
People that had enough money that they weren't paying attention to the price of groceries before Trump, probably still don't care all that much now. I might eat out less, but that's not worth abandoning my family or dying over to me.
The kind of problems you're describing certainly don't sound like things you should "pick up a weapon and give up your life" for, so this doesn't seem to add an argument in favour of "revolution".
Or maybe people realize that revolutions, and the civil war that almost always ensue, are a very high price to pay, for a very uncertain reward.
Talking about the Arab spring, look what it lead to:
- Egypt and Tunisia are again being lead by a dictator, it's just a younger one.
- Libya is destroyed, lacks leadership and conflict could resume any day should Haftar decide he doesn't like the result of the upcoming (but long postponed) elections.
- Syria has suffered the worst civil war of the decade and the situation is still very brittle. It looks like Jolani could bring redemption to Syria, but with the Israeli playing around with fire it could also collapse any day. And that's assuming Jolani doesn't turn into a dictator himself: we're not talking about someone with a good track record of honoring his promises (which is a good thing when the promise is made to ISIS or Al Qaeda, but still).
Jan 6, didn't work, not entirely sure why you bring this up as a blueprint for anyone. It was an actual LARP and as Bruno Macaes wrote resembled a bunch of people making it to the end of a videogame, then running around confused in costumes and going for a drink.
What did work for them was pouring money into the election system and party apparatus, media, the courts and then taking control over politics
What worked was getting people stirred up to the point that some would turn to violence. Even now a majority of their party believe they were justified.
That helped them take control of politics. And so that tactic will surely turn people to violence again. The violence itself may not be effective but the level of outrage is.
> Jan 6, didn't work, not entirely sure why you bring this up as a blueprint for anyone.
Might want to let the Democrats know that. According to them the government was >this< close to being overthrown. Which is funny, because if anyone truly believes that, we don't stand a chance against pretty much any country on earth.
Then you weren't paying attention. Watch the videos of the mob inside the building. If they hadn't been led away from the senate chambers by capitol police [1], we'd be having a very different conversation right now. Did you think the American History X extras leading the pack were just there to see the sights? Come on, man.
What conversation do you think we would be having? Would we be debating the laws that January 6 attendees are passing in the chambers? What alternate outcome do you think was likely, or even possible?
I don't know a single prominent Democrat who thought they had a chance of succeeding, just that they even tried was enough for them to be unpatriotic cultists
Ya'll don't realize what the actual plan was. It wasn't to use the mob to overthrow the government, it was to use the mob to delay the certification of the vote. Which they did, but it wasn't for long enough. They were going to overthrow the Constitution by just deciding for themselves they won despite the votes. And they're in power again, so they're very likely going to do exactly that next time.
The whole plan after the judicial effort failed (using the courts to overturn the vote outcome) and the individual shakedowns failed (calling up governors and demanding they change the vote outcome) was to pressure senators to throw out the state certificates, kick them back to the states, and have the states decide that Trump won instead. They had a whole slate of fraudulent shadow certificates with Trump as the winner ready for Senators to certify. That 10000% would have worked because there are more red states than blue, so they would have just picked Trump over Biden.
But Pence refused to go along with the plan. So the mob was the last ditch effort to convince the senators. Its purpose was not to kill the senators but to delay the vote to give more time to affect the influence campaign. So that plan was also very very close to working because they did delay the vote. It only didn't work because Mitch McConnell refused to end the session and kept everyone around to complete the certification of the vote on January 7. But the fact that it happened on January 7 means that the plan very nearly worked.
You need to look at J6 as a buffer overflow attack. There are no instructions for what to do if the J6 vote is disrupted by a mob, the hope was that but putting the country in that illegal state would allow for arbitrary instructions to be executed.
> ~~2k~~ 250 unarmed people ~~broke into work~~ mysteriously allowed in are looking for you, while dozens of trained armed police officers surround you, it would probably be something you think about a whole lot
The one person who died violently was one of the rioters, an unarmed woman who was shot by Capitol Police. Four other rioters died of natural causes around the time of the riot.
An unarmed woman climbing through a smashed window with a capital police officer on the other side, sidearm drawn, warning her not to advance, in the middle of a crowd storming the capitol building while a gallows stood outside,
waiting for the crowd to bring out a member of congress or the Vice President.
> * U.S. representative Markwayne Mullin [currently head of DHS], a witness to Babbitt's attempted breach, said that Byrd "didn't have a choice" but to shoot, and that his action "saved people's lives".* [0]
The shooting was deemed “lawful and within department policy”.
>The shooting was deemed “lawful and within department policy”.
I do not disagree with this at all. I only mentioned her death as contrast to the usual rhetoric of how the mob at the Capitol "killed" Officer Sicknick and others (who are always mysteriously unnamed).
It's hard to reconcile a conspiracy theory that protestors were allowed to storm the Capitol with the fact that Ashli Babbitt was shot on video for refusing calls to stop breaching a barricade.
Police and security trying to manage a dynamic situation with minimum loss of life by not immediately gunning down quasi-violent crowd is a more reasonable conclusion.
Regardless, 100% of which is Trump's fault for incitement.
alright but the point still stands? people were yelling out names carrying zipties... they broke windows hit police officers and a woman was killed while crawling through a broken window?
if that happened to me at work it would be something I talked about all the time, there are a thousand ways it could have gotten even worse
Jan 6 was an attempt to convince the American public that the 2020 election was stolen, and to keep Trump in power. Today, more people believe the 2020 election was stolen than on January 7th, Trump is in power despite causing an insurrection, and all the J6 insurrectionists have been pardoned. They’re even setting up to pay them “restitution” out of your pocket.
You can be the judge as to whether it succeeded or victory was deferred, but violence definitely won in the end.
Or sue, or organize and protest, or win the next election. Not every government problem warrants revolution, and not needing to revolt is not a failing of the people.
> Americans/Westerners (left, right, center) are way too comfortable for a revolution
A better read is that the situation for most Americans and "Westerners" whatever that means, is that things are good enough that the people do not see value in revolution, or they are able to adjust the government's course enough through elections, redress, courts and other political feedback mechanisms.
They were terrorists. Every single participant in J6 was a terrorist and deserves the full fury of the United States of America to treat them as such. They were also attempting to assassinate the VP. 1500+ terrorist and failed assassination attempts.
It's a shame we went so light on them. Care bear punishment. Sweetheart deals, and then pardoned by a man that literally, factually, supports terrorism against the USA and supporting the attempted assassination of his VP.
I just don't see that the main thrust of their argument, (oversimplified) "humans will become so dependent on AI, they'll become dumb," holds any water. I mean even from an evolutionary standpoint, intelligence is (by far) our most valuable competitive advantage. Arguing that "cognitive offloading" (their term) will have runaway effects is reaching to say the least.
It's like saying that moving from manual-labor-intensive agrarian societies to industrial ones will make us weak and meek. In fact, it's had the opposite effect: humans, on average, are healthier and live longer than ever in human history.
Haven't read the article but I think in some limited timeframes it's true. I'm already turning over a lot of my thinking to LLMs. Not so much of a problem if I own the LLM but when big tech can just turn off the tap when they want or skew the results it seems a bit dangerous. It's possibly less dangerous for me, being old already, but seems quite risky for younger folk.
> humans, on average, are healthier and live longer than ever in human history.
Kinda. We also have incredible rates of cardiovascular disease, obesity, and diabetes.
While I do mostly buy that the mind and the body are connected, I don't think being able to bench press 250lbs is a necessary, fundamentally human capability. I do think being able to think is. Literally Rene Descartes cogito ergo sum. If we lose cognition, executive function, analysis, skepticism, etc., I don't think we're human anymore.
> We also have incredible rates of cardiovascular disease, obesity, and diabetes.
To me, this is kinda like saying we have incredible rates of autism. While technically true, the science is still fairly new, so we simply don't have very much historical data. In all likelihood there isn't a sudden epidemic of autism, only improvements to how it's diagnosed.
The higher rates don't make any sense if you don't try to take into account the fact that we live longer. Of course we will accumulate more diseases if we last longer.
This is such a weird nitpick, it's clear the website deals in averages and assumptions. It's meant to be an interesting window into possible lives intermixed with historical happenings at, or around, those times.
I get that some people just hate AI, but of all things, this is a pretty fun & educational use of it.
I think our core disagreement is that I do not consider teaching falsehoods to be educational. My antipathy towards LLM outputs that haven't been fact-checked is mostly downstream of things like that.
This website doesn't "teach" anything. It's a fun way to explore and get exposed to history. Kind of like Civilization 6 or something. Do you think CIV6 "teaches falsehoods" because you can build the Pyramids as the French?
I haven't played Civilization. Generally I would not consider something educational if it contains mostly false information. Perhaps clearly demarcated parts of it with true information could be considered educational -- for example, looking at screenshots I don't see anything immediately objectionable in the civiliopedia "historical context" sections.
I think most players would understand that in-game choices will not reflect the choices people actually made historically. Having not played Civilization, I'm not sure whether I would consider it to be educational -- I think it would depend on whether playing the game provides insight into real historical events.
For example, I would consider a sufficiently detailed LARP of a historical event to be educational[1] -- the actual choices and outcomes do not match what happened historically, but they can teach participants a great deal about the motives and limitations of real historical actors.
This website, on the other hand, seems to consist of 90% AI hallucinations and 10% data that was actually extracted from a real source[2]. Since these types of data are thoroughly mixed together, I think this website is about as educational as just making up something to believe about the past.
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