MurphyA/hacker-news huggingface dataset:
by ewoodrich | 2025-08-07 23:33:03+00:00
I think the type of AI coding being used also has an effect on a person's perception of the prevalence of "hallucinations" vs other errors.

I usually use an agentic workflow and "hallucination" isn't the first word that comes to my mind when a model unloads a pile of error-ridden code slop for me to review. Despite it being entirely possible that hallucinating a non-existent parameter was what originally made it go off the rails and begin the classic loop of breaking things more with each attempt to fix it.

Whereas for AI autocomplete/suggestions, an invented method name or argument or whatever else clearly jumps out as a "hallucination" if you are familiar with what you're working on.
by stillsut | 2025-08-07 23:34:14+00:00
Yeah I suspect some of these providers will become Microsoft in the '90s type bully holdouts on implementing the emerging conventions. But ultimately with CLI interface you have workarounds to all the major providers read in your system guidelines. But in an IDE - e.g. like MS had with VisualStudio - you more lock-in potential for your config files.

Yesterday, I was writing about a way I found to pass the same guideline documents into Claude, Gemini, and Aider CLI-coders: https://github.com/sutt/agro/blob/master/docs/case-studies/a...
by godelski | 2025-08-07 23:34:22+00:00
You're right, but compounding effects get out of hand pretty quickly. There's a certain point where finite is not meaningfully different than infinite and that threshold is a lot lower than you're accounting for. There's only so much compression you can do, so even if that new information is not that large it'll be huge in no time. Compounding functions are a whole lot of fun... try running something super small like only 10GB of new information a day and see how quickly that grows. You're in the TB range before you're half way into the year...
by dragonwriter | 2025-08-07 23:34:55+00:00
> The 69.1 column has the same height as the 30.8 column. My guess is they just duplicated the 30.8 column and forgot to adjust the height to the number

Why, unless specifically for the purpose of making it possible to do inaccurate and misleading inconsistencies off this type, would you make charts for a professional presentation by a mechanism that involved separately manually creating the bars and the labels in the first place? I mean, maybe, if you were doing something artistic with the style that wasn't supported in charting software you might, but these are the most basic generic bar charts except for the inconsistencies.
by josephg | 2025-08-07 23:35:07+00:00
Thats not at all true though?

If you have a small dataset, yeah, memcpy will outperform a lot of indirect pointer lookups. But that doesn't stay true once you're memcpying around megabytes of data. The trick with indirect data structures on modern hardware is to tune the size of internal nodes and leaf nodes to make the cache misses worth it. For example, Binary trees are insanely inefficient on modern hardware because the internal nodes have a size of 2. If you give them a size of 64 or something, they perform much better. (Ie, make a b-tree). Likewise, a lot of bad tree implementations put just a single item in the leaf nodes. Its much better to have leaves store blocks of 128 items or something. And use memcpy to move data around within the block when needed.

This gets you the best of both worlds.

I spent about 18 months optimising a text based CRDT library (diamond types). We published a paper on it. By default, we store the editing history on disk. When you open a document, we reconstruct the document from scratch from a series of edits. After awhile, actually applying the stream of edits to a text document became the largest performance cost. Ropes were hugely useful. There's a stack of optimisations we made there to make that replay another 10x faster or so on top of most rope implementations. Using a linear data structure? Forget it. For nontrivial workloads, you 100% want indirect data structures. But you've gotta tune them for modern hardware.
by kranke155 | 2025-08-07 23:35:14+00:00
I doubt Elon had the time or the inclination to build yet another hardware stack, and he probably saw something that showed him he couldn’t quite catch up to Nvidia?

The scale of Nvidia manufacturing and RnD should be staggering atm. Google built the entire software and hardware stack for TPUs before the AI boom. I can’t even imagine how hard it would be to hire GPU hardware talent right now.
by Tadpole9181 | 2025-08-07 23:35:23+00:00
According to NASA, the Air and Space Museum, and Wikipedia: you are wrong. Nor does what you're a saying making any sense to anyone who has seen an airplane fly straight.

Symmetric airfoils do not generate lift without a positive angle of attack. Cambered airfoils do, precisely because the camber itself creates lift via Bernoulli.
by sysmax | 2025-08-07 23:36:06+00:00
Want a good use case?

I am playing around with interactive workflow where the model suggests what can be wrong with a particular chunk of code, then the user selects one of the options, and the model immediately implements the fix.

Biggest problem? Total Wild West in terms of what the models try to suggest. Some models suggest short sentences, others spew out huge chunks at a time. GPT-OSS really likes using tables everywhere. Llama occasionally gets stuck in the loop of "memcpy() could be not what it seems and work differently than expected" followed by a handful of similar suggestions for other well-known library functions.

I mostly got it to work with some creative prompt engineering and cross-validation, but having a model fine-tuned for giving reasonable suggestions that are easy to understand from a quick glance, would be way better.
by neuronexmachina | 2025-08-07 23:36:20+00:00
I really like the idea of standardizing on AGENT.md, although it's too bad it doesn't really work with the .cursor/rules/ approach of having several rules files that get included based on matching the descriptions or file globs in frontmatter. Then again, I'm not sure if any other agents support an approach like that, and in my experience Cursor isn't entirely predictable about which rules files it ends up including in the context.

I guess having links to supplementary rules files is an option, but I'm not sure which agents (if any) would work well with that.
by gruez | 2025-08-07 23:36:32+00:00
>Crime rates are largely inaccurate since 2021: https://www.themarshallproject.org/2023/07/13/fbi-crime-rate...

That's why I specifically said "prior to covid". Moreover what's your point here? People were wrong for 3 decades, but because they turned out to be right eventually it's fine? Seems dubious. After all, even a broken clock is right twice a day.
by morleytj | 2025-08-07 23:36:43+00:00
Comment I'm replying to poses the following scenario:

"If you could just ask GPT to create a startup that'll be guaranteed to be worth $1B on a $1k investment within one year"

I think if the situation is that I do this by just asking it to make a startup, it seems unlikely that no one else would be aware that they could just ask it to make a startup
by simoncion | 2025-08-07 23:36:51+00:00
I'm not sure how you got the impression that I had the impression that you're unwilling to use a browser plugin. I have absolutely no idea whether or not you're willing to use a browser plugin.

I was mentioning how auto-type worked because it's useful information for those who either are unwilling to use a browser plugin, or are like myself and simply have no need for one.
by godelski | 2025-08-07 23:37:26+00:00
I think that makes a lot of assumptions about the size of data and what can be efficiently packed into prompts. Even if we're assuming all info in a prompt is equal while in context and that it compresses information into the prompts before it falls out of context, then you're going to run into the compounding effects pretty quickly.

You're right, you don't technically need infinite, but we are still talking about exponential growth and I don't think that effectively changes anything.
by jMyles | 2025-08-07 23:37:53+00:00
...I'd like to see evidence for that claim.

Much more likely is that the opacity of encryption lends advantage to the unsophisticated bad actors (ie, the 'official' ones).

I think most of us, at least in the USA, are far more ready to take our chances with these hypothetical sophisticated bad actors than to reduce the real-time transparency of verified ones.
by mindslight | 2025-08-07 23:38:15+00:00
That's a low pass filter. And I suppose in the type of highly-resilient slow changing signals like OP mentioned in a different comment, it makes sense to do that and even to refer to it as "debouncing". But for general consumer electronic devices with basic local buttons, the standard algorithm is something more like act on the first close, then ignore the next 10 samples. When there is no other reason for a switch to read as closed, the first close means the button has definitely been pushed. The point of debouncing is to avoid seeing the open-close-open-close oscillation afterwards (contacts settling) as their own release-press combos.
by unicorn_chaser | 2025-08-07 23:38:18+00:00
At first glance, gold mining and Bitcoin mining look like opposites, especially from the physical vs. digital aspect. But at the economic level, they share the same basic architecture:

1. Both require significant upfront capital before producing anything. 2. Both have measurable and increasing extraction difficulty (declining ore grades vs. algorithmic difficulty adjustments). 3. Both are constrained by scarcity (finite deposits vs. Bitcoin’s 21M cap). 4. Both convert energy + expertise into a durable store of value. 5. Both are highly sensitive to market cycles and price volatility. 6. Different tools (excavators vs. ASICs) but similar incentive structures, similar risk profiles, and similar reliance on efficiency and timing.

If you strip away the “old vs. new” narrative, they’re not enemies. They’re two implementations of the same idea: using work and energy to escape the limitations of fiat.
by 1vuio0pswjnm7 | 2025-08-07 23:38:52+00:00
"type of wrench for tight spaces"

Basin_wrench is #3 result

Delete preposition: "of"

"type wrench for tight spaces"

Basin_wrench is #2 result

Delete preposition: "for"

"type of wrench tight spaces"

Basin_wrench is #2 result

Delete prepositions: "of", "for"

"type wrench tight spaces"

Basin_wrench is #2 result

Delete unnecessary noun "type" and preposition "of"

"wrench for tight spaces"

Basin_wrench is #1 result

Delete preposition "for"

"wrench tight spaces"

Basin_wrench is #1 result

"tight spaces wrench"

Basin_wrench is #1 result

"tight wrench spaces"

Basin_wrench is #1 result

Much less typing, no unnecessary nouns and prepositions

I like it, others might not

I also tried a number of less popular search engines with a non-AI search from the command line

Query string "type of wrench for tight spaces"

For several of them the #1 result was for star-plumbing.com

https://star-plumbing.com/what-kind-of-wrench-is-used-in-tig...
by Bluestein | 2025-08-07 23:38:54+00:00
I've got to say - and this in a way makes sense: The model seems to be very "URL-oriented" ...

... as in (at least in the demo, the search one) if you ask it to visit a site by name (ie. "Go go Altavista and ...," ...

... it will complain "no URL" has been provided.-

It probably has to do with the "special instructions" given to the AI for this one program/demo ...

... still.-
by techpineapple | 2025-08-07 23:39:22+00:00
It’s a stark number: 212,000. That’s how many women ages 20 and over have left the workforce since January, according to the most recent jobs numbers released Aug. 1 by the Bureau of Labor Statistics. (By contrast, 44,000 men have entered the workforce since January.)

The use of “entered” and “left” is confusing to me, are they comparing apples and oranges or net job gains and losses. Presumably some women entered the workforce during this time and some men left right?
by p_l | 2025-08-07 23:39:57+00:00
For PDP-10, because it operated only on word values, you can easily assume that every bus and memory operation passes a full 36 bit word every time.

In fact, recent-ish x86 CPUs have similar instructions, and as of Zen4 they are fast not just on Intel but also on AMD (previously they were microcoded as a bunch of shifts AFAIK with pretty lousy latency)
by aeve890 | 2025-08-07 23:40:11+00:00
It is in the face of naive, overoptimistic arguments that straight up ignore the negative impacts, that IMO vastly outweigh the positive ones. We will have the cure of cancer, but everyone loses their jobs. This happened before, with nuclear energy. The utopia of clean, too cheap to meter nuclear energy never came, though we have enough nukes to glass the planet ten times over.

Stop pretending that the people behind this technology is genuinely motivated by what's best for humanity.
by throwanem | 2025-08-07 23:40:27+00:00
Well, I haven't been willing to take you at your word when you showed up to tell me how wrong I am based on nothing but your say-so. Sure, I'll give you that.

Were you not expecting to have to convince anyone? If that really is so, then again I have to ask, do you imagine this sort of thing normal? Are you in the habit of letting harangue stand in for conversation in ordinary life also, or is this a special occasion?
by DaveZale | 2025-08-07 23:41:10+00:00
and extreme wealth in the hands of a few. You can look it up easily, the Federal Reserve has all the numbers

here is one table

https://www.federalreserve.gov/releases/z1/dataviz/dfa/distr...

If you are in the bottom 50% it's like being in the bottom caste of India
by mkipper | 2025-08-07 23:41:48+00:00
I’m incredibly confident that any professor of aerospace engineering would give a better response. Is it common for people with PhDs to fall for basic misconceptions in their field?

This seems like a reasonable standard to hold GPT-5 to given the way it’s being marketed. Nobody would care if OpenAI compared it to an enthusiastic high school student with a few hours to poke around Google and come up with an answer.
by whartung | 2025-08-07 23:42:02+00:00
> maybe a spotlight-like search

As I recall, XP had a background indexing process, to facilitate system wide search.

I distinctly recall having to turn it off as I had builds fail more than once because the indexer had a derivative file open that the build was trying to delete.

Locking open files has been a Windows pet peeve of mine for decades.
by famouswaffles | 2025-08-07 23:42:08+00:00
>Really though, why put all your eggs in one basket? That's what I've been confused about for awhile.

I mean that's easy lol. People don't like to invest in thin air, which is what you get when you look at non-LLM alternatives to General Intelligence.

This isn't meant as a jab or snide remark or anything like that. There's literally nothing else that will get you GPT-2 level performance, never-mind an IMO Gold Medalist. Invest in what else exactly? People are putting their eggs in one basket because it's the only basket that exists.

>I think the big question is if/when investors will start giving money to those who have been predicting this (with evidence) and trying other avenues.

Because those people have still not been proven right. Does "It's an incremental improvement over the model we released a few months ago, and blows away the model we released 2 years ago." really scream, "See!, those people were wrong all along!" to you ?
by mindcrime | 2025-08-07 23:42:43+00:00
Some transmitters have such a distinct sound that you can identify them with just your unassisted human hearing. Back in my firefighting days, I remember that certain trucks or stations had transmitters where you could identify them from the half second or so of "hum" between the time somebody keyed up the mic and the time they started talking. Using ML / signal processing stuff on a computer, yeah, you can probably get pretty fine grained at discriminating these things.
by didibus | 2025-08-07 23:44:04+00:00
I'm actually starting to think the opposite.

If Cursor can build the better UX for all the use-cases, mobile/desktop chatbot, assistant, in IDE coding agent, CLI coding agent, web-based container coding agent, etc.

In theory, they can spend all their resourcing on this, so you could assume they could have those be more polished.

If they win the market-share here, than the models are just commodity, Cursor lets you pick which ever is best at any given time.

In a sense, "users" are going to get locked in on the tooling. They learn the commands, configuration, and so on of Cursor, it's a higher cost for them to re-learn a different UX. Uninstalling and re-installing another app, plugin, etc. is annoying.
by anothernewdude | 2025-08-07 23:45:09+00:00
My use case has been trying to remove the damn "apologies for this" and extraneous language that just waste tokens for no reason. GPT has always always always been so quick to waffle.

And removing the chat interface as much as possible. Many benchmarks are better with text completion models, but they keep insisting on this horrible interface for their models.

Fine tuning is there to ensure you get the output format you want without the extra garbage. I swear they have tuned their models to waste tokens.
by nicce | 2025-08-07 23:46:16+00:00
It also scares me how good they are in appealing and social engineering. They have made me feel good about poor judgment and bad decision at least twice (which I noticed later on, still in time). New, strict system prompt and they give the opposite opinion and recommend against their previous suggestion. They are so good at arguing that they can justify almost anything and make you believe that this is what you should do unless you are among the 1% experts in the topic.
by serf | 2025-08-07 23:46:20+00:00
Honda/Acura/Toyota have used similar systems for years; this is one of the reasons why cloning a key costs less flagged hours than making a new one for an owner that lost all of them : when you lose all of them you need to get the actual computer out and pair it with the ecm directly, when you clone them there is a ritual that can be done with the other keys+ the new one.
by igor47 | 2025-08-07 23:46:31+00:00
This is basically what happened during Trump's first term. He was always announcing crazy shit, and then all the people working for him tried to keep it from happening. This was used in the last election as evidence the Trump's policies aren't so bad.

The tarrif stuff is going to work out the same way. People are really bad at nuance, long term thinking, and connecting delayed effects to causes. The argument will be, well if the tarrifs were so bad why did it take 6 or 9 months or whatever to have any effect? Probably, it was all the Epstein talk that crashed the economy, or Obama did it to distract from his looming inditement over the Russia hoax. We live in insane times.
by imiric | 2025-08-07 23:47:00+00:00
Having the right to modify one part of the product is not the same as having the right to modify the entire product. Labeling such projects as open source in the full spirit of the definition is disingenuous.

This is similar to the approach taken by some video game studios: release the source code under a permissive license, but not the game assets. Which is better than a proprietary license, but it still presents a hurdle for the final product to be built from source.

The open weights approach is much more user hostile, however. Proprietary game assets can at least be purchased, and the final product can be built. With open weights, this is not possible. Nobody can realistically build the same model or similar models from weights alone. They can use the weights and self-host the prebuilt model, but not create revisions of it, which is the whole point of open source.

Weights are essentially the bytecode of language models. Sure, you can run and modify it with the right tools, but without the tools used to create it in the first place, the project is not much more useful than publishing binaries.
by thaumasiotes | 2025-08-07 23:47:23+00:00
> Had they followed it consistently, they would have excluded certain cultural-practice-based technologies like nixtamalization that made the list.

This is an interesting example. It's a technology that's very important for staying alive, but not one that you'd expect to contribute to any kind of progress. It's just something you have to do to corn before eating it.
by 1659447091 | 2025-08-07 23:48:41+00:00
> The issue here is United penny pinching for decades

United* was one of the first major airlines to embrace modern tech. Their phone app was lightyears ahead of anyone else (I haven't revisited others in the past couple years, maybe other airlines caught up, I dunno)

When I use to spend way too much time on frequent flyer boards it seemed United was the only one spending money and embracing their tech center to innovate and update old systems, both software and hardware. It takes time to modernize, some changes also have to happen in all the many airports they do business in, not to mention all of the other fragmented systems they were working to better integrate. Since they are not a tech company I don't expect -- or want -- them to "move fast and break things".

Singling them out as penny pinching on tech is simply disingenuous.

*United & the *A group are my preferred airlines; bias is likely as well as a keen interest in what they are doing.
by anitil | 2025-08-07 23:49:26+00:00
I'm not sure I understand your point, maybe we're talking at cross purposes? In the case of chopping off a thief's hand I see the _desire_ to steal as the moral failing. Preventing the physical theft in that case doesn't resolve the moral failing. In the alcohol case, (some) people who take naltrexone completely lose the desire to drink, so the internal _desire_ (or 'moral failing') has resolved, rather than just the symptom of drinking.

But we may be using different definitions of moral failing
by esseph | 2025-08-07 23:50:34+00:00
I am specifically talking about Linux, did you misread?

My experience is managing over a hundred thousand vms at once across multiple countries, and have managed large fleets of tens of thousands or hundreds thousand+ for decades. This is old hat.

My desktop runs Linux. My laptop runs Linux. My phone runs Linux. The phone is the only one without a running SSH server. I'm pretty sure the openssh server is also a default package in Fedora Workstation, it's just got the service disabled by default unless you flick on a check box in the Gnome window.

Windows Server also supports SSH, and has several shell options.

I couldn't answer for any Apple device.

I guess my experience is narrow, though.

Hey, how many git servers do you know not running Linux? That's an interesting question!

Edit: Curious what you think both GitLab and GitHub run on, and if those have ssh enabled or not.
by Telemakhos | 2025-08-07 23:51:31+00:00
I am thoroughly unimpressed by GPT-5. It still can't compose iambic trimeters in ancient Greek with a proper penthemimeral cæsura, and it insists on providing totally incorrect scansion of the flawed lines it does compose. I corrected its metrical sins twice, which sent it into "thinking" mode until it finally returned a "Reasoning failed" error.

There is no intelligence here: it's still just giving plausible output. That's why it can't metrically scan its own lines or put a cæsura in the right place.