MurphyA/hacker-news huggingface dataset:
by pama | 2025-08-09 22:02:33+00:00
Agreed on all points.

What should one make of the orthogonal risk that the pretraining data of the LLM could leak corporate secrets under some rare condition even without direct input from the outside world? I doubt we have rigorous ways to prove that training data are safe from such an attack vector even if we trained our own LLMs. Doesn't that mean that running in-house agents on sensitive data should be isolated from any interactions with the outside world?

So in the end we could have LLMs run in containers using shareable corporate data that address outside world queries/data, and LLMs run in complete isolation to handle sensitive corporate data. But do we need humans to connect/update the two types of environments or is there a mathematically safe way to bridge the two?
by andrewmcwatters | 2025-08-09 22:02:45+00:00
I think that's supposed to be the idea of reasoning functionality, but in practice, it just seems to allow responses to continue longer than that would have otherwise by bisecting the output into warming an output and then using maybe what we would consider cached tokens to assist with further contextual lookups.

That is to say, you can obtain the same process by talking to "non-reasoning" models.
by milesrout | 2025-08-09 22:03:04+00:00
There is a huge difference in the quality of workers in fast food. Some people are slow. They are inefficient. They let things burn, they count change slowly, they are clumsy. They can't multi-task.

It is cognitively simple for you, because you aren't thick. But for people of well-below average intelligence, flipping burgers and doing something else at the time is just not possible.
by omoikane | 2025-08-09 22:03:32+00:00
> One trick you can use is to prefix a file with some JSON or other readable value, then dump the binary afterwards.

The GLB container (binary glTF) works almost exactly as you described, except there is a fixed size header before the JSON part.

https://registry.khronos.org/glTF/specs/2.0/glTF-2.0.html#bi...
by tyre | 2025-08-09 22:03:36+00:00
I think if you look at polling, people’s feelings on admissions is heavily influenced by whether the criteria helps/hurts them. Especially when it comes to students and parents.

Which makes sense. If it came to your kid, would you give up their spot at an Ivy for the “common good” (assuming you saw it that way)?

Or would your definition of what’s right/wrong change to fit the practicals of the circumstances?
by wongarsu | 2025-08-09 22:05:13+00:00
It can spell the word (writing each letter in uppercase followed by a whitespace, which should turn each letter with its whitespace into a separate token). It also has reasoning tokens to use as scratch space, and previous models have demonstrated knowledge of the fact that spelling words is a useful step to counting letters.

Tokenization makes the problem difficult, but not solving it is still a reasoning/intelligence issue
by lucb1e | 2025-08-09 22:05:29+00:00
> "trixie" includes numerous updated software packages (over 63% of all packages from the previous release)

Wow, I'm amazed a third of packages haven't seen an update in, ehm checks

> After 2 years, 1 month, and 30 days of development, the Debian project is proud to present its new stable version

I'm a fan of old software myself, in the sense that I find it cool to see F-Droid having a (usually tiny) package that is over 10 years old but it does exactly what I want with no bugs and it works perfectly on Android 10. I wonder if those 30% more commonly fall in the "it's fine as it is" category or in the "no maintainers available" category
by Fade_Dance | 2025-08-09 22:05:34+00:00
This is a very minor annoyance of mine, but is anyone else mildly annoyed at the increasing saturation of cool, interesting blog and post titles turn out to be software commentary?

Nothing against the posts themselves, but it's sometimes a bit absurd, like I'll click "the raging river, a metaphor for extra dimensional exploration", and get a guide for Claude Code. No it's usually a fine guide, but not quite the "awesome science fact or philosophical discussion of the day" I may have been expecting.

Although I have to admit it's clearly a great algorithm/attention hack, and it has precedent, much like those online ads for mobile games with titles and descriptions that have absolutely no resemblance to the actual game.
by CommenterPerson | 2025-08-09 22:05:36+00:00
"Relative to employment in the fast food sector elsewhere in the United States" .. could drive a truck through that "elsewhere".

In 1992, New Jersey made just such an increase in minimum wage at fast food restaurants. Card & Kreuger ("Myth and Measurement") analyzed data in adjacent areas in NJ & PA. They found that employment in the NJ area actually increased. Take a look at the first chapter of "Economics in America" by Angus Deaton (Nobel 2015).

Comparing CA to elsewhere in the US (where? everywhere?) looks a bit shady. Given the government agencies are being led by political hacks these days, I don't trust it one bit.
by nxobject | 2025-08-09 22:05:42+00:00
Knowing nothing about how survival/durability testing is done in VLSI: how did you do the empirical tests?

For example, I know that thermal samples for the Pentium 5-era Xeon (Jayhawk) were produced, but I'd always wondered Intel went from the dummy to realizing "oh, shit, this is going to be way too hot in the long run."
by k310 | 2025-08-09 22:05:56+00:00
Anything but this image (imgbb.com link below) requires a login. I get the same deal with Facebook. I am not Don Quixote and prefer not to march into hell for a heavenly cause, nor any other.

https://i.ibb.co/Zz2VgY4C/Gx2-Vd6-DW4-AAogtn.jpg
by shadowjones | 2025-08-09 22:06:04+00:00
I think a lot of those trick questions outputting stupid stuff can be explained by simple economics.

It's just not sustainable for OpenAI to run GPT at the best of its abilities on every request. Their new router is not trying to give you the most accurate answer, but a balance of speed/accuracy/sustainable cost on their side.

(kind of) a similar thing happened when 4o came out, they often tinkered with it and the results were sometimes suddenly a lot worse, it's not that the model is bad, they're just doing all kind of optimizations/tricks because they can barely afford to run it for everyone.

When sama says he believe it to have a PhD level, I almost believe him, because he have full access and can use it at 100% of its power all the time.

Even OSS 20b gets it right the first time, I think the author was just mistakenly routed to the dumbest model because it seemed like an easy unimportant question.
by foresto | 2025-08-09 22:06:47+00:00
> I like dpkg, I like the Debian documentation even if Arch remains the best on that front.

That's curious, because when I was learning to make Debian packages, I found the official documentation to be far better than I had seen from any other distro. The Policy Manual in particular is very detailed, continually improving, and even documents incremental changes from each version to the next. (That last bit makes it easy for package maintainers to keep up with current best practices.)

Does Arch have something better in this department?

Are you perhaps comparing the Arch wiki to Debian's wiki? On that front I would agree with you.
by efilife | 2025-08-09 22:07:17+00:00
Sorry for copypasting from another comment but this is relevant

I can tell you what skills I possess. For example: programming, writing music. A LLM can not do this unless it's told what it knows. I could also tell you whether I studied thing X or attempted to do it and what success I had. So I'm pretty good at assessing my abilities. A LLM has no idea
by mikert89 | 2025-08-09 22:07:46+00:00
This isnt the correct comparison, since most people getting into the top schools are completely undifferentiated, all have maxed out GPAs and near perfect/perfect SATs. There are for more people with the profile to get into harvard, than there are admits. The breakdown is a composition of:

1. legacy admits

2. athletic admits

3. dei admits

4. actual brilliances admits

but even in the 4th bucket, they are allocating those spots based on alot of non performative criteria.

with sports, its more like, "who ran 40 meters the fastest"

I live in NYC, I meet the ivy types all the time. I have gotten very cynical about it
by throwdbaaway | 2025-08-09 22:07:51+00:00
https://llm-tracker.info/_TOORG/Strix-Halo has very comprehensive test results for running llama.cpp with Strix Halo. This one is particularly interesting:

> But when we switch to longer context, we see something interesting happen. WMMA + FA basically loses no performance at this longer context length!

> Vulkan + FA still has better pp but tg is significantly lower. More data points would be better, but seems like Vulkan performance may continue to decrease as context extends while the HIP+rocWMMA backend should perform better.

lhl has also been sharing these test results in https://forum.level1techs.com/t/strix-halo-ryzen-ai-max-395-..., and his latest comment provides a great summary of the current state:

> (What is bad is that basically every single model has a different optimal backend, and most of them have different optimal backends for pp (handling context) vs tg (new text)).

Anyway, for me, the greatest thing about the Strix Halo + llama.cpp combo is that we can throw one or more egpu into the mix, as echoed by level1tech video (https://youtu.be/ziZDzrDI7AM?t=485), which should help a lot with PP performance.
by exasperaited | 2025-08-09 22:08:06+00:00
The extraordinary, beautiful, perfect thing about this is the way it poetically underscores several things about the LLM world:

1) these people think so little of everyone else's areas of expertise they are willing to claim their technology has PhD-level expertise in them, apparently unironically.

2) actually in LLM world, PhDs are what you have if you're too stupid not to take the FAANG money in your second year when the quick wins are done, you've done a couple of posters and now you realise you're papering over the cracks with them: worthless. So why would anyone else want a PhD when PhDs are so worthless based on their bubble experience? We can just replace them with GPT-5.

3) their PhD-level-intelligent system is incapable of absorbing corrections, which is a crucial part of acquiring an actual PhD

4) GPT-5 continues to have the asshole-confidence of a tech bro mainsplaining someone else's area of expertise on his personal blog.

We're now at the point where marketing is celebrating software that has had so much effort spent on crushing hallucination that in fact it has become delusionally confident.

I love everything about this.

ETA: at the end of this article is this paragraph, which really is a thing of beauty:

I don’t think you get to have it both ways. That is, you don’t get to, as it were, borrow charisma from all the hype and then disavow every failure to live up to it as someone else’s naive mistake for believing the hype.

Bravo.
by luismedel | 2025-08-09 22:08:13+00:00
Kudos to the team.

My first contact with Linux was with Debian 2.1. Exactly with this distro CDs https://archive.org/details/linux-actual-06-2/LinuxActual_01...

To be honest, it was a miserable experience to install it on your main computer without anything else available to look for help in case of problems. It was also hard to really try it due to lack of drivers for current (at that moment) ADSL modems.

But here I am a crapload of years later, still loving it :-)
by _mlbt | 2025-08-09 22:08:28+00:00
I've read The Communist Manifesto. There are indeed parts of it that are sensible in isolation. The problem is that taken as a whole, Marxism, Leninism, Maoism, etc. are deeply flawed ideologies doomed to catastrophic failure and devastating results. History has shown us this repeatedly.

To Quote Ronald Reagan...

“How do you tell a Communist? Well, it’s someone who reads Marx and Lenin. And how do you tell an anti-Communist? It’s someone who understands Marx and Lenin.”
by __d | 2025-08-09 22:08:31+00:00
And yet, many other countries have managed to transition to metric measurements without too much issue.

My parents were in their 30’s when Australia switched. They instinctively think in feet/inches, pounds for body weight (especially babies), but oddly miles hasn’t lasted.

I was educated in metric, but learned imperial lengths doing woodwork with my dad. I don’t have any intuition in pounds or miles, but feet (up to maybe 10) and inches are ok.

My son is purely metric. He can do the arithmetic, but has no intuitive sense in any imperial units.

So .. my anecdata is that it takes two generations to really switch.
by jncfhnb | 2025-08-09 22:09:13+00:00
I don’t find the explanation about tokenization to be very compelling.

I don’t see any particular reason the LLM shouldn’t be able to extract the implications about spelling just because its tokens of “straw” and “berry”

Frankly I think that’s probably misleading. Ultimately the problem is that the LLM doesn’t do meta analysis of the text itself. That problem probably still exists in various forms even if its character level tokenization. Best case it manages to go down a reasoning chain of explicit string analysis.
by jongjong | 2025-08-09 22:09:27+00:00
I think this is unwise. There are a lot of things that clients need to take into account which cannot be described by WSDLs (e.g. timing related or language specific considerations which require careful thinking through).

I don't buy this idea that code should be generated automatically without a human involved (at least as a reviewer).

I also don't buy the idea that clients should validate their requests before sending to the server. The client's code should trust itself. I object to any idea of code (or any entity) not trusting itself. That is a flawed trust model.
by simonw | 2025-08-09 22:09:49+00:00
If you fine-tune a model on corporate data (and you can actually get that to work, I've seen very few success stories there) then yes, a prompt injection attack against that model could exfiltrate sensitive data too.

Something I've been thinking about recently is a sort of air-gapped mechanism: an end user gets to run an LLM system that has no access to the outside world at all (like how ChatGPT Code Interpreter works) but IS able to access the data they've provided to it, and they can grant it access to multiple GBs of data for use with its code execution tools.

That cuts off the exfiltration vector leg of the trifecta while allowing complex operations to be performed against sensitive data.
by tyre | 2025-08-09 22:10:05+00:00
> they would not do things to jeopardize their reputation or standing. So I think it's just not the case that there are unqualified legacy admits

This is known to be false. Development cases, where donor’s buy admission, are real. They’re limited, but universities do them regularly.

If you look at Jared Kushner’s case, for example, his parents weren’t even legacies!

If they keep this number small, like five per year, would it really dilute Harvard’s brand? I doubt it.

https://en.wikipedia.org/wiki/Development_case
by exasperaited | 2025-08-09 22:10:42+00:00
This is not a demonstration of a trick question.

This is a demonstration of a system that delusionally refuses to accept correction and correct its misunderstanding (which is a thing that is fundamental to their claim of intelligence through reasoning).

Why would anyone believe these things can reason, that they are heading towards AGI, when halfway through a dialogue where you're trying to tell it that it is wrong it doubles down with a dementia-addled explanation about the two bs giving the word that extra bounce?

It's genuinely like the way people with dementia sadly shore up their confabulations with phrases like "I'll never forget", "I'll always remember", etc. (Which is something that... no never mind)

> Even OSS 20b gets it right the first time, I think the author was just mistakenly routed to the dumbest model because it seemed like an easy unimportant question.

Why would you offer up an easy out for them like this? You're not the PR guy for the firm swimming in money paying million dollar bonuses off what increasingly looks, at a fundamental level, like castles in the sand. Why do the labour?
by sofixa | 2025-08-09 22:10:47+00:00
> which would be Ubuntu's NIH syndrome

Red Hat do the same. They reinvented the wheel on multiple occasions (systemd and it's whole ecosystem like systemd-resolved and timed and the whole kitchen sink; podman, buildah, dnf, etc etc.)

They just have more success on getting their NIH babies accepted as the standard by everyone else. Canonical just fail at that (often for good reasons, Unity was downright crap for some time) and abandon stuff, which doesn't help their future causes.
by nickfromseattle | 2025-08-09 22:11:53+00:00
>What is the right amount of spending?

I am 'dumb money', but my understanding is the 'smart money' thinks the sustainable target deficit is 3% of GDP, and we're currently running at 6%. [0]

[0] https://time.com/7221862/ray-dalio-cut-the-budget-deficit/
by standardUser | 2025-08-09 22:11:59+00:00
I would hope so, since if it didn't everything we know about economics would be wrong. But this question only makes sense if you value all employment equally. If the state lost a tiny amount of jobs, and most of those were among the lowest paying, then I'd want to know A) what's been the impact on cost of living and B) what's been the impact on government welfare spending, before I could begin to assess if it was a positive overall for the state economy.
by singularity2001 | 2025-08-09 22:12:04+00:00
"LLMs won’t magically make you deliver production-ready code"

Either I'm extremely lucky or I was lucky to find the guy who said it must all be test driven and guided by the usual principles of DRY etc. Claude Code works absolutely fantastically nine out of 10 times and when it doesn't we just roll back the three hours of nonsense it did postpone this feature or give it extra guidance.
by WarOnPrivacy | 2025-08-09 22:12:18+00:00
> We should demand not to subsidize the richest companies in the world.

Not without overturning Dodge Bros vs Ford, I believe. The ruling created shareholder primacy, the privilege of shareholders to have maximum bites of the corporate apple. It rigidly protects shareholder (and by ext, executive) interests.

The never-ending wealth that flows from that - first buys politicians, then officials, judges and (eventually) every part of regulation & corporate oversight.

ref: https://en.wikipedia.org/wiki/Dodge_v._Ford_Motor_Co.
by creativeSlumber | 2025-08-09 22:12:19+00:00
> Is it... time for me to take another pass at this?

Yes please. I was very excited for Sandstorm when it first started. Sad to see it's current stage.

Also I think the world around has evolved quite a bit wrt containerization from when Sandstorm first started. I wonder how you would build it today, if you were to build from scratch. Could you utilize docker for most of the containerization?
by cameldrv | 2025-08-09 22:13:09+00:00
I think that's the trick. These university admissions committees are essentially choosing the ruling class for the next generation. What makes a good ruling class depends on more than just test scores and grades, so admissions committees look at other things the applicant has done, and at least they used to also do an interview with an alumnus. All of this is fairly gameable though, and the kind of person who would excessively game these metrics might not be person who they want to choose. Knowing that someone is the child of someone who already was admitted and indoctrinated into the values of the university is a pretty good signal that this person is more likely to be the kind of person they want to admit.

Now all of this runs into the same fundamental issue that any decision like this does, namely, that ideally you want everyone to have an equal chance, but also, you want them to do a good job in their role. Unfortunately, people, through no fault of their own, are born into different circumstances, and some are prepared, in many different ways, better or worse than others, and this strongly affects how well they will perform.
by lucb1e | 2025-08-09 22:13:29+00:00
The only complaint on a fresh install is that Cinnamon seems to use a ton of CPU when there's a little moving thingy anywhere on the screen (a browser tab that has a loading icon in the tab list is sufficient). This is most noticeable when you have a VM without graphics acceleration (don't ask why in the world my job requires that). Graphics without acceleration is always heavy, but this is an extra process doing whatever on top of the actual load

Then my private laptop has had a bunch of graphic issues after upgrading to 13 (it manifests differently in a lot of applications and it changes when you pick a different desktop theme, not even sure how to describe it). The new pipewire (pulseaudio replacement, idk why that needed replacing) does not work properly when the CPU is busy (so I currently play games without game sounds or music in the background). The latter then also sometimes (1 in 5 times maybe?) crashes when resuming from suspend, but instead of dying, spams systemd which diligently stores it all in a shitty binary file (that you can't selectively prune), runs completely out of disk space, and breaks various things on the rest of the system until you restart the pipewire process and purge any and all logs (remember, no selective pruning)... Tried various things I found in web searches and threw an LLM at it as well, but no dice. I assume these issues are from it not being a fresh install, so no blame/complaint here really, just annoying and I haven't had these issues when doing previous upgrades. Not yet sure how to resolve, perhaps I'll end up doing a completely new install and seeing what configs I can port until issues start showing up

Surely these things are not a Debian-specific issue, but I haven't noticed something like that with either 11 or 12

Edit: oh yeah, and the /tmp(fs) counter is at 1 so far. I wonder how many times I'll have run out of RAM by Debian 14, by forgetting I can't just dump temporary files into /tmp anymore without estimating the size correctly beforehand
by ponector | 2025-08-09 22:14:16+00:00
Yes. White male with Slavic face who speaks russian language without an accent because he knows no other language.

A friend of mine had a grandfather, who was born in central Asia (Samarkand) had Ukrainian parents, but also had written in his passport that he was a russian. Soviets erased his roots, history, ethnicity. He never spoke Ukrainian in his life.

Btw, that is what current russian government is doing. They have stolen thousands of Ukrainian kids and erased their identity. Few more years and some of them are ready to be sent to the frontline.
by dragonwriter | 2025-08-09 22:15:19+00:00
> Can you guarantee it will validate it every time ?

Yes, to the extent you can guarantee the behavior of third party software, you can (which you can't really guarantee no matter what spec the software supposedly implements, so the gaps aren't an MCP issue), because “the app enforces schema compliance before handing the results to the LLM” is deterministic behavior in the traditional app that provides the toolchain that provides the interface between tools (and the user) and the LLM, not non-deterministic behavior driven by the LLM. Hence, “before handing the results to the LLM”.

> The whole point of it is, whichever LLM you're using is already too dumb to not trip when lacing its own shoes. Why you'd trust it to reliably and properly parse input badly described by a terrible format is beyond me.

The toolchain is parsing, validating, and mapping the data into the format preferred by the chosen models promot template, the LLM has nothing to do with doing that, because that by definition has to happen before it can see the data.

You aren't trusting the LLM.