MurphyA/hacker-news huggingface dataset:
by marcellus23 | 2025-05-15 18:48:01+00:00
Which ChatGPT model was this? Was web search enabled? Reasoning? Those will make a big difference in results, I imagine, and not mentioning them makes the article almost meaningless.

> How are you suppose do data analysis with “intelligent” software that can’t nail something so basic?

It is really interesting how there seems to be a camp of people that tries one of these tools for something it's not very good at, then declares the tool is useless. No, it's not AGI, and yes, it has a lot of weak spots. But like any tool, you do have to know how to use it. And it's clearly creating a lot of value for the people who do know where its strengths and weaknesses are.
by sunrunner | 2025-05-15 18:48:13+00:00
Do the comparisons to PhD-level as a marker for some quantity of how 'smart' a system (by which I mean the current colloquial usage of 'AI') really make sense?

I thought a PhD was ultimately a representation of a body of work that a likely-smart person produced in order to a) learn the state of the art in a narrow domain, b) practice research methodology, c) hopefully push the boundary of human knowledge in that area. Which is not to say that PhD candidates and holders are not 'smart', just that PhD represented the work and not just the person after an IQ test.

Or is the comparison valid and the goal is for AI (again, current colloquial usage) to be able to push the boundaries of human knowledge? Or perhaps it would be human-machine-knowledge at that point?
by _jab | 2025-05-15 18:48:14+00:00
I think the reason the goalposts keep shifting is really that these AI labs are illustrating Goodhart's law in action: https://en.wikipedia.org/wiki/Goodhart%27s_law

We're at a point where AI labs are fairly reliably able to create AI systems that can achieve good performance on given benchmarks, via targeted training efforts. You argue that it's not reasonable to expect that performance to generalize across other domains. But given that these same companies are trumpeting that AGI is around the corner, I think that's a fair expectation for us to have, and AI has disappointed in that regard.
by Voultapher | 2025-05-15 18:48:18+00:00
What about noise? So far all we have gotten is companies trying to build planes that still are very loud and produce audible booms all the way along their travel path. Pitched to the empathetic heros that are billionaires. And to sway public opinion they fly test planes at slightly over mach one in specific weather and altitude setting that avoids having the sonic booms reach the ground. While marketing and selling the idea of not mach 1.1 but mach 2-3 supersonics. Which is AFAIK completely impossible without the boom issue, even if made less bad - but arguably still bad - by fancy wing shapes. So all I see is selfish people trying to build something at expense of everyone else, including the environment.
by rchaud | 2025-05-15 18:48:27+00:00
This doesn't get said enough. The widescreen desktop Internet (even at 800 x 600) was far more creative and fun than the modern transactional app world. The 2008-10 era iOS apps being a rare exception, but that too was snuffed out due to changing App Store guidelines that punished silly apps and favoured the recurring revenue cargo cult.
by enjoylife | 2025-05-15 18:48:45+00:00
“‘It’s still learning’ is a misnomer. The model isn’t learning—we are. LLMs are static after training; all improvement comes from human iteration in the outer loop: fine-tuning, prompt engineering, tool integration, retrieval. Until the outer loop itself becomes autonomous and self-improving, we’re nowhere near AGI. Current hype confuses capability with agency.
by davydog187 | 2025-05-15 18:48:48+00:00
Both the Lua library and Luerl predate Pythonx. I started this library nearly 2 years ago, its only now that I'm releasing a stable version.

However, Pythonx was originally created by a member of our team, Cocoa, who built it in her own free time. The Livebook team forked her project, conceptually, and released it.

https://github.com/cocoa-xu/pythonx
by karaterobot | 2025-05-15 18:48:58+00:00
Looking around, I don't see too many people exploring higher order skills using that spare brain power. I think at the margins, you've probably got really smart scientists/engineers/philosophers doing that, but what does the ordinary person in the street do? This is the grumpiest thing I'll say today, but it seems like they just scroll social media on their phones while streaming media plays in the background.
by anthk | 2025-05-15 18:48:59+00:00
This is fun too

https://github.com/howerj/subleq/

but you might need to edit subleq.fth and create a new image with some of the constants named opt.* settings set to 1 (enabled) in order to enable do...loop support and such. After you enabled them, try ./sublec ./sublrec.dec < ./sublec.fth > new.dec, wait a lot, and then run ./subleq sublec.dec .

In order to save lots of time, clone the muxleq repo https://github.com/howerj/muxleq , edit muxleq.fth as always, and then run ./muxleq ./muxlec.dec < muxlec.fth > new.dec, and ./muxlec ./new.dec to run the new DEC EForth image.

Is not especially fast but it's a ready to run Forth and the Subleq machine can be compiled even under Windows XP and up with Min-C or any bundled C compiled on GNU/Linux BSD, from cproc to tcc, gcc or clang. If some of your code runs fast under Muxleq+EForth, it will fly under PForth and GForth.

https://minc.commandlinerevolution.nl/english/home.html

The speeds I get under an n270 atom with Muxleq are almost like a Forth machine under a boosted up 8 bit machine, kinda like an 8MHZ z80 with a native Forth, or a very low end M68k machine.
by zahlman | 2025-05-15 18:50:14+00:00
TFA keeps repeating "you can't use loops", but aren't they, like, merely less performant? I understand that there are going to be people out there doing complex algorithms (perhaps part of an ML system) where that performance is crucial and you might as well not be using NumPy in the first place if you skip any opportunities to do things in The Clever NumPy Way. But say I'm just, like, processing a video frame by frame, by using TCNW on each frame and iterating over the time dimension; surely that won't matter?

Also: TIL you can apparently use multi-dimensional NumPy arrays as NumPy array indexers, and they don't just collapse into 1-dimensional iterables. I expected `A[:,i,j,:]` not to work, or to be the same as if `j` were just `(0, 1)`. But instead, it apparently causes transposition with the previous dimension... ?
by sh34r | 2025-05-15 18:50:30+00:00
This is the song it's ~~hallucinating~~ bullshitting about: https://www.youtube.com/watch?v=a6NJitdq8Bk&t=1s&themeRefres...

It's like an Irish rebel song but with stomping. I'm not sure how you watch that and think racist thoughts, unless you're the kind of guy who Sieg Heils on national TV.
by skydhash | 2025-05-15 18:50:38+00:00
Sometimes learning means understanding, aka a deep dive on the domain. Only a few domains are worth that. For the others, it's only about placing landmark so you can quickly recognize a problem and find the relevant information before solving it. I believe the best use case of LLMs is when you have recognized the problem and know the general shape of the solution, but have no time to wrangle the specifics of the implementation. So you can provide the context and its constraint in order to guide the LLM's generation, as well as recognize wrong outputs.

But that's not learning or even problem's solving. It's just a time saving trick. And one that's not reliable.

And the fact is that there's a lot of information about pretty much anything. But I see people trying to skip the foundation (not glamorous enough, maybe) and go straight for the complicated stuff. And LLMs are good for providing the illusion that it can be the right workflow.
Ask HN: Is Substack the New Medium?
by behnamoh | 2025-05-15 18:50:44+00:00
So many articles appear on Substack but the quality isn't great all the time. the website keeps showing banners to subscribe. in fact, they black out the article as you scroll down so you enter your email first. subscribing to an author is not a one-click thing either—you will be bombarded with several questions afterwards because the website tries to get you to subscribe to several other authors as well, and it makes it hard to not pay for the said subscription.

articles written on Substack are often too lengthy, and the website doesn't support all markdown features, which reminds me of Medium. on Medium, people asked for years to be able to include code blocks in their articles, but Medium only added that feature when it was too late. before that, we literally had to make Github gists for every piece of code we wanted to add to our article.
by quantadev | 2025-05-15 18:51:03+00:00
Interestingly, this algo has absolutely nothing whatsoever to do with "Wavelets" or even waves. The name "wavelet" stuck to it mostly only because it uses a recursive decomposition approach which happens to be something that Wavelet does in actual wave processing. It got collectively labeled "Wavelet" when what was really meant was just "Recursive".
by 542354234235 | 2025-05-15 18:51:26+00:00
I think what they are talking when they say visible homeless is people that are “chronically homeless” which is people “experiencing homelessness for longer than a year with a serious mental illness, substance use disorder, or physical disability”. [1] These are not people losing their home due to medical bills. Drug addiction motivates panhandling, a way to obtain cash for drugs over social support systems that provide non-cash assistance. Serious mental illness often leads to very visible erratic behavior, either directed to “their own world” or at other people. I can’t speak to you experience, but a small percent of homeless people do harass people for money, or scream nonsense, and end up arrested or in the hospital far more than the vast majority of other homeless people. [2]

I guess I find it hard to believe that you never encounter panhandlers or mentally ill homeless people acting erratically, aggressively, or both. I don’t really understand what you mean by “people who seem homeless are no different than other people, except they are vulnerable and don't dress as well”. Most homeless people dress as well as any other lower income housed person, unless you just mean anyone who looks kind of poor. The people sleeping on park benches in filthy clothes are rarely “no different” than other people, because again, they are almost all dealing with serious physical, mental, or substance abuse problems.

[1] https://www.healthaffairs.org/content/forefront/precision-pe...

[2] “Participants averaged five hospitalizations, 20 visits to the emergency department, five to psychiatric emergency services, and three to jail in the two years prior to being enrolled. While these are the homeless people who are the most visible to the general public, and to many health care workers, researchers said they represent only about 5 percent to 10 percent of chronically homeless individuals.” https://www.ucsf.edu/news/2020/09/418546/study-finds-permane...
by sigmaisaletter | 2025-05-15 18:52:24+00:00
Looks great. Not sure how big the market is between "need max privacy, need on-prem" and "don't care, just use what is cheap/popular" tho.

Can you talk about how this relates to / is different / is differentiated from what Apple claimed to do during their last WWDC? They called it "private cloud compute". (To be clear, after 11 months, this is still "announced", with no implementation anywhere, as far as I can see.)

Here is their blog post on Apple Security, dated June 10: https://security.apple.com/blog/private-cloud-compute/

EDIT: JUST found the tinfoil blog post on exactly this topic. https://tinfoil.sh/blog/2025-01-30-how-do-we-compare
by Voultapher | 2025-05-15 18:52:27+00:00
Seeing this thread pains me. I recall reading the Foreigner series by C. J. Cherryh and in it they had an alien politician mention cars in passing, stating that it would be stupid to give their citizens this selfish way of transportation and rather invested in train infrastructure. And boy does it seem stupid looking back. Something like 30% by area of US cities are taken up by parking space and it get's so much worse once think about what a city would look like if built for people and not cars.
by lo_zamoyski | 2025-05-15 18:52:32+00:00
What we call "power" is not a property of a person, but a function of networks of relationships. A king is only "powerful" insofar as his authority is recognized. The moment his perceived authority is lost, the moment no one or few recognize it, is the moment he no longer has "power".

In other words, it only works if there is enough social support for it. It requires our complicity.

Most people with ASPD (what you call sociopathy) are not able to build these sorts of networks. They're impulsive. They are over-represented among the homeless. They are poor at planning or foreseeing the consequences of their actions. These are not exactly conducive to building these social networks. A sociopath is more the street thug or the gangbanger and less the CEO of a corporation.
by nayuki | 2025-05-15 18:52:45+00:00
I skimmed the article and agree with it at a high level, though I haven't faced most of those problems personally.

I have several gripes with NumPy, or more broadly the notion of using Python to call a C/asm library that vectorizes math operations. A lot of people speak of NumPy like the solution to all your high-performance math needs in Python, which I think is disingenuous. The more custom logic you do, the less suitable the tools get. Pure Python numeric code is incredibly slow - like 1/30× compared to Java - and as you find parts that can't be vectorized, you have to drop back down to pure Python.

I would like to give the simple example of the sieve of Eratosthenes:

def sieve_primeness(limit): result = [False] + [True] * limit for i in range(2, len(result)): if result[i]: for j in range(i * i, len(result), i): result[j] = False

This code is scalar, and porting it to a language like C/C++/Rust/Java gives decent performance straight out of the box. Performance in Python is about 1/30× the speed, which is not acceptable.

People pretend that you can hand-wave the performance problem away by using NumPy. Please tell me how to vectorize this Python code. Go on, I'm waiting.

You can't vectorize the `if result[i]` because that controls whether the inner for-loop executes; so it must execute in pure Python. For the inner loop, you can vectorize that by creating a huge temporary array and then AND it with the result array, but that is extremely memory-inefficient compared to flipping bits of the result array in place, and probably messes up the cache too.

Alternatively, you can run the code in PyPy, but that usually gives a speed-up of maybe 3×, which is nowhere near enough to recover the 30× speed penalty.

Another example is that NumPy is not going to help you implement your own bigint library, because that also requires a lot of custom logic that executes between loop iterations. Meanwhile, I've implemented bigint in pure Java with acceptable performance and without issues.

Again, my point is that anytime you venture into custom numerical/logical code that is not the simple `C = A + B`, you enter a world of pain when it comes to Python performance or vectorization.
by shrx | 2025-05-15 18:52:50+00:00
Question to the author: Why are the images in the "Solution 2: Genuine HDR Displays" section actually videos? E.g.

<video src="https://www.lux.camera/content/media/2025/03/new-york-skyline-hdr.mp4" poster="https://img.spacergif.org/v1/4032x3024/0a/spacer.png" width="4032" height="3024" loop="" autoplay="" muted="" playsinline="" preload="metadata" style="background: transparent url('https://www.lux.camera/content/media/2025/03/new-york-skyline-hdr_thumb.jpg') 50% 50% / cover no-repeat;"></video>
by viridian | 2025-05-15 18:52:59+00:00
True. And I agree with it in terms of cardinality (bad stuff incoming), just not magnitude.

The starvation thing that appears throughout this larger thread is exceptionally odd to me, how does a planet where food is mostly harvested mechanically, encounter food shortages in the face of decreased population? Even if the labor force plummets, the machines sow, tend, and harvest most of the food, and the amount of required food is also going to down as the population does.
by delecti | 2025-05-15 18:53:01+00:00
Interject. When things are getting off topic (which is to say, as soon as one person interrupts another person's update with a question) just say "this might be better for post standup", or even just "post standup?" with a questioning inflection.

Most of the people who will mind are exactly the kind of person that you're trying to keep from wasting everyone's time.
by jzb | 2025-05-15 18:53:20+00:00
What's "fun" is when companies try to be different and schedule meetings at :05 or :10 past the hour, so if you have any regular meetings with people outside the company that do the :50 or :55 thing, it's complete chaos.

FWIW I've never seen top-down efforts to make meetings more efficient stick. Humans are humans, not automatons. They're chatty. They're messy and unorganized. And attempts to build "culture" that curbs those things isn't going to stick when people constantly change jobs because it no longer pays to stay at the same company for decades. (You know, assuming they don't just lay people off because that's the way the wind is blowing...)
by mrguyorama | 2025-05-15 18:53:22+00:00
>Once upon a time, the price of a product was often a good indicator of its quality. If you saw two products side by side on the shelf and one was more expensive, then you might assume that it was less likely to break or wear out soon.

I don't think this has ever actually been true. There was plenty of expensive snake oil in 1800s America. There were plenty of expensive shit things. There always has been. Christ, that ancient tablet of that guy complaining about copper quality is one of the oldest written documents we have, and I can assure you that copper was not cheap.

Price has never been a signal of quality because it wouldn't make any sense. The price is set by the seller. That's the only signal it can convey; what the seller expects you to pay. There's never been a perfectly efficient market where a seller is forced to set the price of something to match it's value or quality. There has always been information asymmetry. There has always been a difficulty in finding out whether that thing for sale is actually worth it.
by 93po | 2025-05-15 18:53:54+00:00
1. https://www.doge.gov/savings this seems like incredibly transparency for a brand new government initiative that's like 100 days old. and in the ways it doesn't provide enough info, it acknowledges that, and says they're working on it, which i believe.

2. i agree that there is a lot of highlighting of stuff that is cut that is aligned with leftist ideology, e.g. money spent on programs that are gender affirming or involving trans/LGBTQ issues. i am LGBTQ/trans myself and I am massively in support of all initiatives to make the world a more loving, kind, accepting place. but i can also empathize that government attempts to do so are probably rampant with fraud and abuse and theft and waste, and it's not clear to me to what extent our government should be funding things surrounding social issues like this at all.

3. again i think this is a sentiment based on hyperbolic media reporting and is hard to substantiate with concrete evidence other than "MSNBC had an anonymous source that said so". it's also hard to know how much the claims, if true, are misaligned with "business as usual" in the government. if doge has access to personal information to help reduce social security fraud, is that really unusual? it seems like it's necessary if you're going to audit fraud and catch things like a 9 year old getting veteran benefits or whatever.

i think doge is definitely framing cuts in ideological ways for political points. and i believe they are specifically looking for and cutting DEI related stuff, because they've plainly stated as much. but problematic framing and motivations aside, i do think it's a massive net benefit, and especially if their work helps weed out and cut off people who systemically commit fraud and waste for years and for millions/billions of dollars.
by davydog187 | 2025-05-15 18:54:08+00:00
Elixir is not a sandboxed language, so you can't just accept arbitrary Elixir programs from users and execute them inside of your application without security concerns. Lua, on the other hand, can be executed in a sandboxed fashion, limiting and constraining the reach of user programs.

Check out Anthony Accomazzo's post about Mini-Elixir, which does a great job breaking this down much further https://blog.sequinstream.com/why-we-built-mini-elixir/
by brosco | 2025-05-15 18:54:48+00:00
Compared to Matlab (and to some extent Julia), my complaints about numpy are summed up in these two paragraphs:

> Some functions have axes arguments. Some have different versions with different names. Some have Conventions. Some have Conventions and axes arguments. And some don’t provide any vectorized version at all.

> But the biggest flaw of NumPy is this: Say you create a function that solves some problem with arrays of some given shape. Now, how do you apply it to particular dimensions of some larger arrays? The answer is: You re-write your function from scratch in a much more complex way. The basic principle of programming is abstraction—solving simple problems and then using the solutions as building blocks for more complex problems. NumPy doesn’t let you do that.

Usually when I write Matlab code, the vectorized version just works, and if there are any changes needed, they're pretty minor and intuitive. With numpy I feel like I have to look up the documentation for every single function, transposing and reshaping the array into whatever shape that particular function expects. It's not very consistent.
by savanaly | 2025-05-15 18:55:00+00:00
>I don't think open models will come to the rescue either. Mass market will want to use the best models with the least friction. The moment you have to do more than go to a website and start prompting, 90% of mass market is out.

I interpret this as you saying that we need saving from the eventual predations of the shopping AI agent industry on helpless consumers. Honest question, why won't competition come to the rescue? Any number of startups hungry for customers will be competing to provide the best version of the product that they can afford to provide, and will eventually settle into some fair equilibrium, absent the government picking some kind of winner or imposing binding price controls.

It's true that Uber used to offer outrageously good prices to acquire users, and nowadays charges what some people consider outrageously high prices ($80 to get me to the airport??). But a closer look at the economics of the situation reveals that the prices that rideshare services have settled on are the pretty-much-sane ones, accounting for the market value of the driver's time and uber's cost to develop and maintain the app. Why wouldn't the end result of the AI shopping agent market be the same?
by gojomo | 2025-05-15 18:55:34+00:00
Is there a frozen client that someone could audit for assurance, then repeatedly use with your TEE-hosted backend?

If instead users must use your web-served client code each time, you could subtly alter that over time or per-user, in ways unlikely to be detected by casual users – who'd then again be required to trust you (Tinfoil), rather than the goal on only having to trust the design & chip-manufacturer.