I'm sorry, but no, you don't get to lecture me about my privilege when I'm responding a grotesque coddled techbro pontificating about how Doordash has solved the problem of eating to the point that cooking is some quaint cute whimsical thing that people do as a hobby on the same level as owning a typewriter.
This reminds me of an HN comment years ago where an engineer at some big tech company was at a loss as to how he would get snacks/drinks as the company was ending its free/open kitchen policy (the obvious answer being to just go to the store and pack stuff the night before).
That was the day I realized being a software engineer from greater America is totally different than those from SV. The coddling was (is?) unreal.
Sure I do, the only difference between the two is which society considers normal. Your argument basically boils down to how dare these spoiled kids operate outside of the Overton Window of acceptable externalizable labor I was raised to consider normal. It wouldn't even be two generations ago where someone could write this exact rant about sewing. And today it is relegated to a quaint hobby. The same thing happened with car maintenance and food preservation within living memory.
Don't get me wrong, I partake in the group hazing ritual of guys who can't cook—it's good fun. But on the tiniest bit of introspection it's pretty obvious it's well on the way to becoming a hobby. We're already 90% of the way there with the hallowing out of the 'middle' between glorified warming prepared foods and enthusiast home cooks. The class divide isn't really cooks/non-cooks anymore it's DoorDash vs grocery store freezer section. Sad but not unexpected.
edit: to offer a slightly more substantive reply I will offer the Merriam Webster definition of cooking, which is "to prepare food for eating by a heating process" which applies just as much to warming preprepared or frozen foods as it does to enthusiast home cooks. I agree with you that the class divide is exemplified by the extremes of rich idiots who can just order Doordash for every meal and people who rely on the grocery store freezer section. The difference is that the people in the grocery store freezer section are actually cooking their food, while the Doordash people aren't, and the former category of people is substantially larger than the latter.
What a disingenuous, willfully ignorant take. None of these AI companies have been acting in good faith or in any way other than grotesque self-aggrandizement to the expense of everyone else.
Also a ton of comments in this thread: breathless frothing hype declaring mathematics is over and assuming these proofs are exactly what they claim they are at face value, giving the company with a vested interest in everyone unquestioningly believing this is all real every conceivable benefit of the doubt
By all accounts the "dangerous for math" claims seem to be primarily around flooding the field with complicated impossible-to-understand proofs that according to recent research may or may not be correct depending on what's going on with the Lean implementation.
It's looking to me like it's more of a slop PR problem than it is that these things are genius at math and will displace mathematicians. I am happy to be wrong but I strongly suspect the next few weeks to months will result in more and more of this work being exposed as slop.
These things are ok-ish to halfway decent at coding tasks with a ton of babysitting and still make tons of extremely simple errors almost constantly, why should math be any different?
Yes, Lean verified proofs could be wrong, but the chances for that are much smaller than human not spotting error (in absence of formal verification). IIRC the main concern that Tao voiced are indeed impenetrable proofs that humans won't understand, but not concerns about truthfulness (I might have missed something though, so if he or other Fields medalists have talked about that recently I'd be grateful if you could link it).
> These things are ok-ish to halfway decent at coding tasks with a ton of babysitting and still make tons of extremely simple errors almost constantly, why should math be any different?
1) AI is winning programming competitions, 2025 was probably the last year we've had human participant winning* 2) Math is different because there's formal verification.
* Of course competitive programming is different than enterprise programming, but competitive programming is closer to math.
I agree with this too and I find this article extremely depressing.
The AI "revolution" as described here is the wholesale outsourcing of vast swaths of thinking and decision-making to a single entity. A project coded with Claude is a project coded by Anthropic. A business whose decisions are made with ChatGPT is a business run by OpenAI.
Is that what these people really want? To become a conduit through which two or three companies get to exert control over everything in the world?
I don't buy this analogy and I think it takes a depressingly reductive view of creativity. In both cases, the photographers had to take the time to go to a place, see a view they thought was worth capturing, operated their equipment to get a shot, and then had enough discernment to recognize which of their final products were worth something. Both the traditional photographer and the modern photographer can create images of value in different ways.
If you want to shoehorn AI into this analogy at all then no one is even bothering going hiking at this point, let alone seeing anything worth capturing. It would just vomit up endless permutations of statistically average images that look like the kind of pictures people take of landscapes.
However, for writing software with AI the analogy still works. Just as the photographer needs to pick a shot worth capturing, you have to figure out software worth building. That often also involves some leg work: you need to understand the problem and user needs. Then you need discernment to figure out where the software works well, and which parts need improvements
Well yeah and then you can be liberated by the fact that maybe getting to the landscape and experiencing it and not taking the photo was the goal all along.
You can be creative and take the photo for your sake but at the same time accept that you can generate 1000s of them and many of the generated ones will be more liked by the general public than your creative one.
There used to be no such thing as a woodworker. It used to be a number of different professions, such as the jointer, the cabinet maker, the planer, etc. now with modern tools it’s merged into one job
In the past few could afford to be photographers due to time and money. Many were not the most artistic or talented minds in the universe on the subject (you can’t find those until you give everyone a camera) but just people who enjoyed it and could make money off of it. Those who gained experience with the old tech were essentially AI models trained on statistically good probabilities of getting good shot. You had smaller selection and the model / brain quality determined what % of
the best that photo was between 0 and 100% for any sunset. In modern days more people get a camera - more people with bad taste and more people with good taste. You also get more attempts at the shot - more photos taken, more tries. More tries means you are now preserving more of that moment from more angles and extending the time your taste people have to pick the best shot of all possible.
Your plethora of statistically average photos happen if you don’t have anyone filtering the ginormously increased output. If the problem is really valuable, someone will filter it. Possibly a model.
The real filter is value, not capability anymore. Do you have the empathy and taste to know what matters? The AI tokens/cost lets everyone make and become interested in making of someone hasn’t solved their problem. And then if search isn’t improved - everyone will just repeat the making of the same thing over and over. So if you don’t want repeated slop. fix search.
Or do you copy everything and everyone into making more of nothing.
>The Defense Department’s 1970s-era IBM Series/1 Computer and long-outdated floppy disks handle functions related to intercontinental ballistic missiles, nuclear bombers and tanker support aircraft, according to the new Government Accountability Office report.
If they're not being held legally liable, then I would not agree that "no one is confused about the liability". Sure, I agree with your analogy with a machine cutting off a finger, but you and I are just two people gabbing on HN. Nothing we say has any effect on OpenAI. And if law enforcement doesn't have an effect on them, then talk about "liability" is just empty words.
Well... if that's true, and I don't know that it is, it's not because of the agents. It's because of the money. People with money get away with crimes all the time and it has nothing to do with agents.
I don’t know what spectrum you’re on, but attacking an argument and attacking a person are two wildly different things. There’s nothing pedantic about that.
I apologize, but I don't find the syntactic rules of this site to be well thought out. "Your comments are stupid" and "You are stupid" carry the same meaning.
> Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes.
> Comments should get more thoughtful and substantive, not less, as a topic gets more divisive.
> When disagreeing, please reply to the argument instead of calling names. "That is idiotic; 1 + 1 is 2, not 3" can be shortened to "1 + 1 is 2, not 3."
As near as I can tell, I was in fact right. I just didn't follow the laws of HN communication to express it, on a thread where the person I replied to didn't follow it either.
It would have been more appropriate to pile on with the others above.
One of the main purposes of LLMs is to launder responsibility/culpability for (possibly nefarious) actions in the eyes of the public. The average person has no idea how LLMs actually work and think it’s plausible that an “agent” could go rogue without any human instruction. Terms like agent, thinking, reasoning, etc reinforce the misconception that the LLM has a mind of its own.
Yes, it is, for the reasons I stated in my comment, and you only need look at any OAI/Anthropic press release to see evidence of this in the language they use.
The LLM now reasons better! Set the thinking level! It learns!
All of these phrases are designed to give the impression that the LLM is an autonomous entity, when it is no such thing.
I am not arguing that any of these terms are novel, so this doesn’t address my argument.
Even if I agree that LLM makers are using these terms in the way they were originally defined (which I don’t), my point is that they’re specifically being used to help falsely attribute agency to the algorithm when there is none, and especially to convince members of the general public who aren’t familiar with computer science papers from 70 years ago.
> You are ascribing intent where you have no evidence or proof
As I said already, the evidence is in the language they use, unless you think that OpenAI employees are dumb enough to genuinely believe that an LLM is “thinking.” (By the way, I’d love to see an historical, academic use of that term, which you’ve conveniently neglected to mention.) Anthropomorphizing their product benefits them.
> Those terms continue to be used in the community. They weren't used just once, 70 years ago.
I never said they weren’t used anymore or that they were used once. Once again, you’re not actually engaging with my argument, which is that the language they’re using is chosen specifically to fool people outside the community.
This language has been used in this way for 70 years. These are the words that are used to discuss these things. Are you suggesting this plan has been in the works for 70 years?
And no, your theories do not make for actual evidence.
The fact that they use the word "learning" does not imply they are trying to deceive the public. Sorry. It doesn't follow. AGAIN - these are the words that have been used for 70 years.
I have a question - if I made mechanical teeth and described its actions as "chewing", would I be trying to deceive you? Or would I just be using language in a new way, to explain an analogous situation, as has done with language for all time.
But... I get the feeling we may just have to agree to disagree here.
> This language has been used in this way for 70 years. These are the words that are used to discuss these things. Are you suggesting this plan has been in the works for 70 years?
No, I am stating that the term “machine learning” as used in the Samuel paper and continuously used by researchers and programmers in that context up until the present is distinctly different from the word “learning” as used in public-facing LLM chatbot product copy and press releases. And as far as I’m aware, “reasoning” and “thinking” have no historical analogues, they were just invented to describe something that is distinctly not reasoning or thinking in any prior sense of the words.
> I have a question - if I made mechanical teeth and described its actions as "chewing", would I be trying to deceive you?
No. If I designed an algorithm for mimicking grammatically-correct speech, which given a certain input produces (deterministically) a superficially plausible, fluent response, and described its actions as “thinking,” would I be trying to deceive you?
I do not agree to disagree, since I think your responses were either incorrect or not addressing my argument at all, but since you're not even attempting to engage anymore I'm happy to move on.
Ah, I see you're still misunderstanding what I say. If you'd like to come back and actually engage with what I'm saying, ask for clarifications, or answer the hypothetical I posed, I'd welcome it!
> Correction: OpenAI carried out an attack on RubyGems.
Your 'correction' is incorrect. A corporation did not carry out an attack. Humans did. And, as it happens, those humans were acting as agents to OpenAI, so the original title technically got it right. It is a poor title as anyone who doesn't give it much thought might mistake a human agent for an LLM agent so your symbolic effort to improve upon it is warranted, but sadly you missed the mark.
If we knew it was employees that did it then "OpenAI employees carried out an attack on RubyGems." would work, but since we don't know who did it "agent" is better in the sense that it also encompasses contractors, board members, etc. Of course, if we knew who did it then " carried out an attack on RubyGems" would be the way.
This article is RubyGems pointing fingers at OpenAI, not OpenAI taking responsibility for anything. We don't know what really happened from what I can tell.
Just ask your preferred AI tool if it can shrink the OP's code while keeping the same functionality; I suspect it could. At this point, LLMs are probably no worse than an average human at sizecoding or targeting resource-constrained platforms in general; https://news.ycombinator.com/item?id=49226923 is a recent example of how powerful they've become.
One of these things is not like the others. Your silicon valley bubble privilege is showing.
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