MurphyA/hacker-news huggingface dataset:
by KerrAvon | 2025-07-17 22:58:35+00:00
> They basically immediately regretted using pascal and started a march towards C and basically gave up on pascal before the powerpc.

Nonsense. MPW Pascal and Think Pascal were well supported developer tools, and a lot of third-party developer code was written in them during the 80's. Photoshop (1987) was originally written in Pascal! Apple's Pascal dialect had object extensions that made OOP simpler than with C or standard Pascal.

Pascal started to leave the building circa 1991, when C++ became viable for OOP. Even then, Metrowerks CodeWarrior supported native Pascal compilation for PowerPC in 1993/4.
by adamtaylor_13 | 2025-07-17 22:59:21+00:00
That’s funny I literally started the $200/month plan this week because I routinely spend $300+/month on API tokens.

And I was thinking to myself, “How does this make any sense financially for Anthropic to let me have all of this for $200/month?”

And then I kept getting hit with those overloaded api errors so I canceled my plan and went back to API tokens.

I still have no idea what they’re doing over there but I’ll happily pay for access. Just stop dangling that damn $200/month in my face if you’re not going to honor it with reasonable access.
by Dylan16807 | 2025-07-17 23:00:05+00:00
> The people getting their money and accounts stolen care.

> People who care about the success of the web care because it makes the web more risky than people using mobile apps.

The main comparison here is whether a middleman injected it or the blog inserted it server-side. The level of risk is similar either way.

> The blog owner cares about the reputational hit.

If the blog hasn't been updated in ages, they probably don't.
by samsartor | 2025-07-17 23:00:34+00:00
I have mixed feelings about this interpretation: that diffusion models approximately produce moseics from patches of training data. It does a good job helping people understand why diffusion models are able to work. I used it myself in talk almost 3 years ago! And it isn't a lie exactly, the linked paper is totally sound. It's just that it only works if you assume your model is an absolute optimal minimization of the loss (under some inductive biases). It isn't. No machine learning more complicated than OLS holds up to that standard.

_And that's the actual reason they work._ Undefit models don't just approximate, they interpolate, extrapolate, generalize a bit, and ideally smooth out the occasional total garbage mixed in with your data. In fact, diffusion models work so well because they can correct their own garbage! If extra fingers start to show up in step 5, then steps 6 and 7 still have a chance to reinterpret that as noise and correct back into distribution.

And then there's all the stuff you can do with diffusion models. In my research I hack into the model and use it to decompose images into the surface material properties and lighting! That doesn't make much sense as averaging of memorized patches.

Given all that, it is a very useful interpretation. But I wouldn't take it too literally.
by sandy_coyote | 2025-07-17 23:01:17+00:00
I appreciate nuance and depth in art, but I've also become addicted to YouTube explainer channels like Heavy Spoilers. I've concurrently watched multiple explainer channels for all the memorable TV shows I've watched lately, and... I really enjoy this new media age.

I still silently and slowly read novels, but as of now, that's a different media experience. Its slow pace is also enjoyable in a different way.
by oehpr | 2025-07-17 23:02:43+00:00
I've been looking for a tool like this that can publish. I was thinking of some way to create a help doc system for end users, but interleaved with technical information and discussion for devs. IE to make the help documentation a single source of truth for application behaviour.

All this needs to work is the ability to mark blocks of the document as "public" so only that gets published properly. Any possibility of doing this currently or interest in supporting in the future?
by acdha | 2025-07-17 23:03:11+00:00
Now, why are the jobs there? Is it because everyone wants to pay tons more for housing, or is it because people with higher incomes are willing to pay for better living conditions and everyone else is pulled along? Tech didn’t used to be anywhere near this concentrated but over the decades people moved out of declining cities and that produced the current hyper-concentration. That cycle is brutal - you have cities like Rochester which have a lot of comparatively cheap real estate but until the senior management want to live there, they won’t have enough businesses for any skilled workers not to think they’d be screwed if their current employment changes because there aren’t many alternatives.
by linkjuice4all | 2025-07-17 23:05:43+00:00
I agree - but technology is just a tool here. The Stasi famously had a network of human informants to notice and collect information.

Going forward it would be nice if we stopped letting these mobs grab power but it's too late, so maybe the effort should be focused on using tools like this to our advantage. Surely there must be some value to the populous to track their oppressors and those that control them - have you considered building a citizen-powered system so you can watch the watchers?
by tengwar2 | 2025-07-17 23:05:50+00:00
I may be misremembering, but I think we had simple topology, linear programming (mainly just 2D, but I remember a 5D problem at the end of the section), matrices with eigenvalues and eigenvectors, set theory, and a bit of group theory. No programming, though there was some in the text book. It was pretty good fun. I don't remember anyone finding it conceptually difficult.

It would also be worth mentioning Nuffield Physics. I thought that was a really great course for learning how to do physics. Very oriented towards finding solutions, devising experiments.
by pembrook | 2025-07-17 23:06:33+00:00
The funny thing is Claude 4.0 isn't even that 'smart' from a raw intelligence perspective compared to the other flagship models.

They've just done the work to tailor it specifically for proper tool using during coding. Once other models catch up, they will not be able to be so stingy on limits.

Google has the advantage here given they're running on their own silicon; can optimize for it; and have nearly unlimited cashflows they can burn.

I find it amusing nobody here in the comments can understand the scaling laws of compute. It seems like people have a mental model of Uber burned into their head thinking that at some point the price has to go up. AI is not human labor.

Over time the price of compute will fall, not rise. Losing money in the short term betting this will happen is not a dumb strategy given it's the most likely scenario.

I know everybody really wants this bubble to pop so they can make themselves feel smart for "calling it" (and feel less jealous of the people who got in early) and I'm sure there will be a pop, but in the long term this is all correct.
by hypeatei | 2025-07-17 23:07:32+00:00
Definitely. I think that would be very hard to carry out for various reasons, though. Intelligence agencies generally want minimal oversight and more power so you'd be fighting that at every corner which includes:

1) Vague threats to leak/expose Congress members' personal matters who craft legislation against them. Chuck Schumer (a sitting US senator) admitted on live TV that the intel community has "six ways from Sunday" to get back at you.

2) Blatant disregard for the law by "just following orders", see anecdotes about Michael Hayden, a former CIA director.

3) Data storage, backup, and classified systems. Decades of collection probably means this data is scattered in many places which could give these agencies a chance to retain data "accidentally" or put up roadblocks due to high level clearances being required to work with these systems.
by kindkang2024 | 2025-07-17 23:07:38+00:00
If we could help gorillas or elephants (both highly intelligent) learn to name things and use symbols — in a form they can comprehend and create to express their will — enabling them to pass down their experiences and wisdom across generations, I believe they could quietly be as smart as we are.

Ps. I am excited about Google’s Gemma dolphin project (https://blog.google/technology/ai/dolphingemma/), but I would prefer if they chose elephants instead of dolphins as the subject, since we live on land, not in water. This way, more emphasis could be placed on core research, and immediate communication feedback would be possible.
by graphememes | 2025-07-17 23:07:49+00:00
It's great for me. I have a claude.md at the root of every folder generally, outlined in piped text for minimal context addition about the rulesets for that folder, it always creates tests for what it's doing and is set to do so in a very specific folder in a very specific way otherwise it tries to create debug files instead. I also have set rules for re-use so that way it doesn't proliferate with "enhanced" class variants or structures and always tries to leverage what exists instead of bringing in new things unless absolutely necessary. The way I talk to it is very specific as well, I don't write huge prose, I don't set up huge PRDs and often I will only do planning if its something that I am myself unsure about. The only time I will do large text input is when I know that the LLM won't have context (it's newer than it's knowledge window).

I generally get great 1-shot (one input and the final output after all tasks are done) comments. I have moved past claude code though I am using the CLI itself with another model although I was using claude code and my reason for switching isn't that claude was a bad model it's just that it was expensive and I have access to larger models for cheaper. The CLI is the real power not the model itself per-se. Opus does perform a little better than others.

It's totally made it so I can do the code that I like to do while it works on other things during that time. I have about 60-70 different agent streams going at a time atm. Codebases sizes vary, the largest one right now is about 200m tokens (react, typescript, golang) in total and it does a good job. I've only had to tell it twice to do something differently.
by kcplate | 2025-07-17 23:07:50+00:00
I am not 100% sure that your implication really tracks with conservative behaviors. I would say it would be more likely that non-empathetic conservatives would work pretty relentlessly to relocate homeless out of their communities rather than just ignore and co-exist with it.

I am not saying they would solve it, but they would make it some other community's problem.
by quonn | 2025-07-17 23:09:26+00:00
I‘m trying to find something resembling a reasoned argument in your comment, but there‘s nothing except profanity.

I did not point out exceptions and the chicken example is merely an illustration of one of my points.

And who says we are talking about the west? Plenty of comments in this thread are talking about pandemics, something that is not known to originate from western agriculture.

You know what‘s a caveman take? Thinking that there is any chance to convince a meaningful number of people to reduce meat consumption globally in the required time window (20-50 years) in a way that has any bearing on climate change (as opposed to the many steps being taken that actually work). That‘s a caveman take.

But now some facts:

https://interactive.carbonbrief.org/what-is-the-climate-impa...

As you can see, the type of meat matters a lot. Cheese is doing worse than pork in this example (not sure I even believe this without more evidence yet). Non-meat sources of protein don‘t do very well: Tofu is just 2x better than poultry. Compare this to the giant bar for beef.

Better chart, apparently same source:

https://ichef.bbci.co.uk/news/1536/cpsprodpb/0477/production...

In short, yes, it would be theoretically possible to eliminate about 10% of global emissions if everyone everywhere stopped eating meat and replaced it with a balanced non-meat diet.

But such an outcome is not realistic.

This is my last comment on HN. It is sad what this corner of the internet has become.
by cdrini | 2025-07-17 23:09:56+00:00
I would say there's a difference between abstract and complex. A complex topic would take a lot of time to communicate mainly because you have to go through all the prerequisites. By abstract I mean something like "communicate" or "loss" or "zero"! The primitives of complex thought.

And if we're saying the lion can speak human, then I think it follows that they're capable of this abstract thought, which is what I think is making the premise confusing for me. Maybe if I change my thinking and let's just say the lion is speaking... But if they're speaking a "language" that's capable of communicating concrete and abstract concepts, then that's a human-style language! And because we share many concrete concepts in our shared life experience, I think we would be able to communicate concrete concepts, and then use those as proxies to communicate abstract concepts and hence all concepts?
by ggm | 2025-07-17 23:10:03+00:00
For the non cogniscenti could somebody translate those jargon ridden X snips into coherent everyday English, the problem is they are using arcane terms of art.

If I understand it right, the system has produced a playscript, a fictional text of psychotic, paranoid delusions about a "deep non state actor", to somebody who presumably fed it a French metric tonne of paranoid aligned prompts. Is that it?

Why erase the name? Is that because they are (false, defamatory) accusations about a real world individual?
by A_D_E_P_T | 2025-07-17 23:10:11+00:00
Serious questions, then:

Why is slavery wrong? Does human life have no innate (non-relative, not bestowed) dignity, in your view?

When judges refer (as they frequently do) to uncodified notions of "fair play" or "good faith and fair dealing," what are they basing those notions on? Is it not a continuation of the ancient Natural Law inclination towards promise-keeping, reflected in many human societies as the oath-breaking taboo?
by Arathorn | 2025-07-17 23:10:30+00:00
Dev on EXI has been focused on:

* event cache, to speed up room load and provide offline support. this was a huge amount of “invisible” work.

* media browsing - swiping between images, using the event cache

* fixing voip integration

* loads of trust & safety features

* threads (now in labs)

* spaces (in active dev)

* search (in active dev)

I agree that it feels like dev has slowed since the initial sprint to launch, but there’s another wave of features landing in the coming months.
by tomhow | 2025-07-17 23:10:31+00:00
> in your opinion things are going exactly as you think they should

I don't think that things are going "great" or "exactly as they should" on HN or in the world at large. It takes constant effort to keep political/ideological toxicity from both ends of the spectrum from poisoning this place. I would love it if HN could have a positive influence on politics and the broader world, but in reality we don't have much clout. My personal hope is for every person to have the greatest amount of freedom, opportunity, abundance and agency that can possibly be attained, including for the least privileged in society, and I'd happily have that be an ongoing topic of discussion on HN. But interesting new ideas about that are notably missing from the ragey politics-related discussions seem to happen here.

> 1. HN needs to be interesting to the majority of users.

Yes, otherwise the audience will leave and HN will die.

> 2. HN is not designed to serve majority opinion.

By that I mean we're not about catering to people's opinions about politics/ideology the way news media outlets cater to an ideological position (e.g., Fox News).

> 3. There is no minority of people flagging stories for disingenuous reasons

Dan and I have both been doing this job for years and we look at the flagging patterns every day. There are some users who do mis-use the flag feature, and when that happens we turn their flags off.

> 4. There is however a minority of people complaining about things being flagged despite repeated and almost daily evidence of the opposite happening.

The users complaining about "censorship" or "suppression" of a category of stories make up a relatively small cohort of people who want HN to be more focused on that category of stories, yes. But we look at their activity (submissions, comments) and see that what they want HN to be is different from what HN has always been intended to be, which is a site for curiosity, not rage.

If you can frame your arguments in these terms, we'll have a better discussion. I.e., if you can point out the evidence that we're doing a bad job of optimizing HN for curiosity rather than rage.
by imiric | 2025-07-17 23:10:31+00:00
Right. I do think that just the capability to find and generate interesting patterns from existing data can be very valuable. It has many applications in many fields, and can genuinely be transformative for society.

But, yeah, the question is whether that approach can be defined as intelligence, and whether it can be applicable to all problems and tasks. I'm highly skeptical of this, but it will be interesting to see how it plays out.

I'm more concerned about the problems and dangers of this tech today, than whatever some entrepreneurs are promising for the future.
by lsy | 2025-07-17 23:10:52+00:00
The example given for inverting an embedding back to text doesn't help the idea that this effect is reflecting some "shared statistical model of reality": What would be the plausible whalesong mapping of "Mage (foaled April 18, 2020) is an American Thoroughbred racehorse who won the 2023 Kentucky Derby"?

There isn't anything core to reality about Kentucky, its Derby, the Gregorian calendar, America, horse breeds, etc. These are all cultural inventions that happen to have particular importance in global human culture because of accidents of history, and are well-attested in training sets. At best we are seeing some statistical convergence on training sets because everyone is training on the same pile and scraping the barrel for any differences.
by Jtsummers | 2025-07-17 23:11:03+00:00
If I get bored with life I'll rewatch and take notes, that was the main one that made me chuckle and stuck with me. It was details around Lisp and a couple other things that were outside his explicit research scope (he specifically researched C++, Smalltalk, and Simula per his blog). Like claiming that everything in Lisp was based on lists (even in 1960 that wasn't true).

I'd just expect more from someone who takes 30+ minutes to debunk a claim that doesn't matter and most people have never heard to be more particular in getting details correct.

On the first part of the video, to be more constructive, it does not matter why a language or tool or whatever was made. The claim, that he debunks, is that OO languages were made to be good for working with teams. Whether it was made for that is immaterial, and no one needs 30 minutes of mostly historically correct video to get to The Truth(tm) of the matter. What's more interesting, and he never bothered to get into, is whether OO is actually good for working with teams (I can go either way, I've dealt with enough garbage OO programs to know that OO itself does not help things, but enough good OO programs to know that it can help things).

To anyone who has not yet watched the video, the second half is interesting, the first half is mostly a waste of time.
by abtinf | 2025-07-17 23:11:07+00:00
It doesn’t mention the number one most important reason: the output is absolute garbage.

I can spot AI writing very quickly now, after just a few sentences or paragraphs. It became a lot easier to spot after I tried to use it in my own writing.

Calling it “slop” is far too generous.

If you know what you want to say, you might think to yourself “I’ll have this write an outline or a first draft that I will then thoroughly edit.”

And every time, what you’ll find is that the LLM output is fundamentally unusable. Points a subtly missing. Points are subtly repeated. Points are miscategorized. Points don’t make sense at all. Points don’t flow in a logical order.

If you try to use an LLM and you don’t know what you want to say, then it’s hopeless. You absolutely will not see the defects. If anyone who knows the subjects reads it, they will instantly know you are a lying piece of shit.
by ants_everywhere | 2025-07-17 23:12:24+00:00
> They're amazing. But the moment you try to do the more "serious" work with them, it falls apart rapidly.

Sorry, but this is just not true.

I'm using agents with a totally idiosyncratic code base of Haskell + Bazel + Flutter. It's a stack that is so quirky and niche that even Google hasn't been able to make it work well despite all their developer talent and years of SWEs pushing for things like Haskell support internally.

With agents I'm easily 100x more productive than I would be otherwise.

I'm just starting on a C++ project, but I've already done at least 2 weeks worth of work in under a day.
by godelski | 2025-07-17 23:12:59+00:00
I don't know about a Lion, but I think Wittgenstein could have benefited from having a pet.

I train my cat and while I can't always understand her I think one of the most impressive features of the human mind is to be able to have such great understanding of others. We have theory of mind, joint attention, triadic awareness, and much more. My cat can understand me a bit but it's definitely asymmetric.

It's definitely not easy to understand other animals. As Wittgenstein suggests, their minds are alien to us. But we seem to be able to adapt. I'm much better at understanding my cat than my girlfriend (all the local street cats love me, and I teach many of them tricks) but I'm also nothing compared to experts I've seen.

Honestly, I think everyone studying AI could benefit by spending some more time studying animal cognition. While not like computer minds these are testable "alien minds" and can help us better understand the general nature of intelligence
by bsoles | 2025-07-17 23:13:07+00:00
As a professional software developer who also teaches CS at a university, my experience with successful engineers all comes down to interest and passion. Self-taught engineers are obviously interested in the subject, but among engineers with a degree, you have a mixed bag. Some of them have no interest whatsoever in the field other than a diploma, but they are familiar with the terms of the art, which makes it difficult to separate the good ones from the bad.
by edmundsauto | 2025-07-17 23:14:37+00:00
Yes, although this is expensive and harmful, there is little reason to think the bad experiments would adopt the winner, or that we can even measure the best outcome. Plus, for a lot of stuff - we don’t need experiments, we know what works!

As an example, is there any reason to think we need to do experiments on whether children are fed at school for free?
by adamtaylor_13 | 2025-07-17 23:16:18+00:00
Well said. People seem to be binary: I code with it or I don’t.

Very few folks are talking about using the LLMs to sharpen THE DEVELOPER.

Just today I troubleshot an issue that likely would’ve taken me 2-3 hours without additional input. I wrapped it up and put a bow on it in 15 minutes. Oh, and also wrote a CLI tool fix the issue for me next time. Oh and wrote a small write up for the README for anyone else who runs into it.

Like… if you’re not embracing these tools at SOME level, you’re just being willfully ignorant at this point. There’s no badge of honor for willfully staying stuck in the past.