MurphyA/hacker-news huggingface dataset:
by vidarh | 2025-08-09 22:30:51+00:00
> Which means you’re still giving untrusted content to the “parent” AI

Hence the need for a security boundary where you parse, validate, and filter the data without using AI before any of that data goes to the "parent".

That this data must be treated as untrusted is exactly the point. You need to treat it the same as you would if the person submitting the data was given direct API access to submit requests to the "parent" AI.

And that means e.g. you can't allow through fields you can't sanitise (and that means strict length restrictions and format restrictions - as Simon points out, trying to validate that e.g. a large unconstrained text field doesn't contain a prompt injection attack is not likely to work; you're then basically trying to solve the halting problem, because the attacker can adapt to failure)

So you need the narrowest possible API between the two agents, and one that you treat as if hackers can get direct access to, because odds are they can.

And, yes, you need to treat the first agent like that in terms of hardening against escapes as well. Ideally put them in a DMZ rather than inside your regular network, for example.
by bluefirebrand | 2025-08-09 22:31:22+00:00
> It's not good for the individuals, but in broader economic terms, an industry that delivered the same value with less people is effectively increasing productivity which is economically generally a good thing

Not if all (or the vast majority) of the extra value produced is captured by a vanishingly small portion of the population

That is the trend we are following and it is exceptionally bad
by godelski | 2025-08-09 22:31:25+00:00
Sure. This was the paper[0]. Here's a few more you might find these interesting. Google's Transformer GAN[1] (not a transformer at all resolutions). Diffusion-GAN[2] is a hybrid architecture. Remember that technically the GAN process can use any underlying architecture. Arguably you could say some of the training steps in LLMs are GANs. And I think this one is also interesting in a similar respect[3]. Before PWC went down, StyleSAN[4] was the SOTA on FFHQ, but IIRC this doesn't change the architecture so it should probably work on all the other architectures too (comes with compute costs, but I think only training. It's been a bit since I read it)

[0] https://arxiv.org/abs/2211.05770

[1] https://arxiv.org/abs/2106.07631

[2] https://arxiv.org/abs/2206.02262

[3] https://arxiv.org/abs/2212.04473

[4] https://arxiv.org/abs/2301.12811
by ShakataGaNai | 2025-08-09 22:31:40+00:00
I tried and was unable to replicate.

Me: How many R's in strawberry ChatGPT said: 3

Me: How many B's in blueberry? ChatGPT said: 2

Me: How many C's in coconut? ChatGPT said: 2

Me: How many D's in Diamond? ChatGPT said: 2

Me: How many A's in Banana? ChatGPT said: 3

https://chatgpt.com/share/6897cc40-6650-8006-aae3-ea2b8278d5...
by dragonwriter | 2025-08-09 22:32:14+00:00
> i mean isnt all this stuff up to the mcp author

Mostly, no. Whether its the client sending (statically) bad data or the server returning (statically) bad data, schema validation on the other end (assuming somehow it is allowed by the toolchain on the sending end) should reject it before it gets to the custom code of the MCP server or MCP client.

For arguments that are the right type but wrong because of the state of the universe, yes, the server receiving it should send a useful error message back to the client. But that's a different issue.
by corimaith | 2025-08-09 22:33:04+00:00
>This is an unrelated point, is your contention that the US is better off with unserious students?

It's that America has the capacity to fully absorb it's talent so it's not a problem. The reason why other countries have more is because they don't have the capacity to absorb them due to less opportunities so the competition is higher. Many of those "serious" students in China or India will still end working in factory jobs and delivery drivers because they weren't good enough.

>It's a big reason those students immigrant to the US and companies here hire those people in masses

Eh, if they were hiring domestic students I wouldn't say there would be much of difference. Unless if you are running a startup, most of these "serious" students will be just writing basic CRUD apps. Value comes from experience here, not talent. Well, if I was American though, I wouldn't bother competing againt millions of desperate Chinese or Indians for opportunity cost anyways, I'd be going more into law or finance. And those fields are less diverse.
by bdangubic | 2025-08-09 22:33:11+00:00
Switzerland ….

Switzerland has mandatory universal health insurance where everyone must purchase basic coverage. The government provides premium reduction subsidies for lower-income individuals and families to ensure affordability.

The unemployment insurance system provides benefits for up to 400 days (about 18 months) for those who lose their jobs, with the amount based on previous earnings. There are also programs for job retraining and placement assistance.

Switzerland’s public pension system that provides retirement benefits starting at age 64 for women and 65 for men. It also includes survivor benefits for spouses and children.

Comprehensive coverage for people with disabilities, including rehabilitation services, vocational training, and financial support for those unable to work.

Monthly child allowances are provided to families for each child until age 16 (or 25 if in education or training). Additional birth and adoption allowances are also available.

Social Assistance via means-tested program that provides financial support for basic living needs when other social insurance benefits are insufficient. This serves as the ultimate safety net.

Mandatory coverage for all employees that covers medical costs and income replacement for work-related and non-work-related accidents.

Paid maternity leave for 14 weeks at 80% of salary, along with job protection during this period.

Switzerland’s system is notable for combining mandatory insurance schemes with income-based contributions and government subsidies to ensure broad coverage while maintaining work incentives.

So maybe not mention Switzerland… Any of the examples would be called “far-left” (or worse) in the US of A
by jonahx | 2025-08-09 22:35:01+00:00
This is the "confused deputy problem". [0]

And capabilities [1] is the long-known, and sadly rarely implemented, solution.

Using the trifecta framing, we can't take away the untrusted user input. The system then should not have both the "private data" and "public communication" capabilities.

The thing is, if you want a secure system, the idea that system can have those capabilities but still be restricted by some kind of smart intent filtering, where "only the reasonable requests get through", must be thrown out entirely.

This is a political problem. Because that kind of filtering, were it possible, would be convenient and desirable. Therefore, there will always be a market for it, and a market for those who, by corruption or ignorance, will say they can make it safe.

[0] https://en.wikipedia.org/wiki/Confused_deputy_problem

[1] https://en.wikipedia.org/wiki/Capability-based_security
by regularfry | 2025-08-09 22:35:22+00:00
One idea I've had floating about in my head is to see if we can control-vector our way out of this. If we can identify an "instruction following" vector and specifically suppress it while we're feeding in untrusted data, then the LLM might be aware of the information but not act on it directly. Knowing when to switch the suppression on and off would be the job of a pre-processor which just parses out appropriate quote marks. Or, more robustly, you could use prepared statements, with placeholders to switch mode without relying on a parser. Big if: if that works, it undercuts a different leg of the trifecta, because while the AI is still exposed to untrusted data, it's no longer going to act on it in an untrustworthy way.
by magicmicah85 | 2025-08-09 22:35:48+00:00
I think Trump wants Tan out. Publicly calling him out puts pressure on him more than a private behind the scenes process that will take weeks/months versus a few days. Tan might be able to supplicate Trump by presenting a golden egg, though.

The public pressure puts Tan on defense which gives Trump leverage in negotiating with him. Not sure what Tan/Intel will need to give up to address any potential conflicts but remains to be seen what happens.
by runako | 2025-08-09 22:35:58+00:00
As I understand matters, it started in the 70s and 80s as states pulled back from funding public institutions. This funding was the mechanism which allowed public institutions to be affordable to families such that a person could pay for a year of public college by working in a grocery store over the summer.

MIT + the more expensive private colleges are effectively a rounding error in terms of number of students matriculating, but they do play in the same market and will price accordingly. But the big driver of what they can get away with is that a college like University of Tennessee is $35,000 annually, for a total ticket likely north of $150k. (Not picking on them, just chose a state at random.)

Worth noting that this is a deliberate political choice. At any time, a state could choose to return to subsidizing in-state college at its public institutions, perhaps in exchange for working in the state after graduation.
by Bowes-Lyon | 2025-08-09 22:36:01+00:00
I strongly dislike the spin of the headline – „Linus told a Google engineer that…” as opposed to „Linus told a developer that…”.

What is the headline implying? That Google engineers are gods? That Google engineers don’t make mistakes?

Also, reading through the code, Linus does have a point. I’m with Linus on this one.
by rayiner | 2025-08-09 22:36:14+00:00
It’s critical to distinguish between being open to outsiders when you have the power to exclude them, versus advocating in your own interest to be included. Everyone advocates for their own inclusion when they have no power—that’s just human self interest. But such advocacy can’t create a fair system, by definition. Minorities and immigrants exist everywhere and advocate for themselves. But most societies don’t allow them to advance. Uyghurs in China can say whatever they want, but it won’t make a difference.

WASPs were unusual in creating systems that saw openness to outsiders as a virtue, and then actually giving up their own power to allow others into the institutions they built. The first black Harvard student was admitted in 1847. Two Japanese students got a degree from Harvard law school in 1874. But if you look at societies where African and Asian people have the power to exclude, those places aren’t very open to outsiders.
by AIPedant | 2025-08-09 22:36:44+00:00
I know ACM Queue is a non-peer-reviewed magazine for practitioners but this still feels like too much of an advertisement, without any attempt whatsoever to discuss downsides or limitations. This really doesn't inspire confidence:

While this may seem like a whimsical example, it is not intrinsically easier or harder for an AI model compared to solving a real-world problem from a human perspective. The model processes both simple and complex problems using the same underlying mechanism. To lessen the cognitive load for the human reader, however, we will stick to simple targeted examples in this article.

For LLMs this is blatantly false - in fact asking about "used textbooks" instead of "apples" is measurably more likely to result in an error! Maybe the (deterministic, Prolog-style) Universalis language mitigates this. But since Automind (an LLM, I think) is responsible for pre/post validation, naively I would expect it to sometimes output incorrect Universalis code and incorrectly claim an assertion holds when it does not.

Maybe I am making a mountain out of a molehill but this bit about "lessen the cognitive load of the human reader" is kind of obnoxious. Show me how this handles a slightly nontrivial problem, don't assume I'm too stupid to understand it by trying to impress me with the happy path.
by jeroenhd | 2025-08-09 22:37:07+00:00
Having to activate their more complex "thinking" model every time they need to count letters is pretty silly, but I suppose it does hide the symptoms.

It's still easy to trip up. The model's tendency to respond positively to user impact will have it do stuff like this: https://chatgpt.com/share/6897cc42-ba34-8009-afc6-41986f5803...

Because apparently the model doesn't know about the actual verb (https://en.wiktionary.org/wiki/blueberry#English), it decides to treat the request as some kind of fantasy linguistics, making up its own definition on the fly. It provides grammatically incorrect examples inconsistent with the grammatically incorrect table of conjugations it generates next.
Thoughts on ChatGPT-5? Especially Around Accuracy, Critical Thinking, and Memory
by zyruh | 2025-08-09 22:37:23+00:00
For those who’ve been using ChatGPT-5, I’m curious how you feel about it—especially regarding three areas that seem to challenge current LLMs:

Hallucinations & Transparency – Still seeing confident but wrong or outdated answers? Does it better admit “I don’t know” or distinguish facts from speculation? How are citations and real-time knowledge?

Critical Thinking – Does it still feel overly agreeable, validating contradictions or avoiding pushback? Or does it challenge flawed ideas and act more objectively?

Context & Memory – Any improvement in holding long conversations, keeping project context, or indicating context limits? Does it handle long, iterative tasks without quality drop-offs?

Would love to hear your experiences—good, bad, or mixed.
by barchar | 2025-08-09 22:38:20+00:00
Also, you only really need to cover any increased taxes, everything else you pay them is someone else's income (fast food workers probably spend almost all their income). So your getting a big income increase to people very likely to spend it, this creating more employment.

Maybe here this will be offset by decreases in welfare program usage and the very, very high effective marginal tax rates that creates.
by jiggawatts | 2025-08-09 22:38:26+00:00
> As a human, if you give me a number on screen like 100000000, I can't be totally sure if that's 100 Million or 1 Billion without getting close and counting carefully.

I become mildly infuriated when computers show metrics (or any large number) without thousands separators.

Worse still, I often see systems that mix units, don’t right-align, and occasionally blend in a few numbers with decimals together with whole numbers! Then, update everything every second to make things extra spicy.
by mh- | 2025-08-09 22:38:33+00:00
Yeah, I have mixed feelings about CT (certificate transparency) for this reason. Folks are just consuming the firehose and scanning.

And in this case, if the thing you're funnel'ing is on your residential connection, it basically amounts to you summoning a DDoS.

One (obvious?) tip I'd offer is to put your stuff on high non-standard ports if you can. It'll reduce the amount of connections you get dramatically.
by Jensson | 2025-08-09 22:38:38+00:00
> And looking at the "achivements" of this so-called "meritocratic elite" this last century (especially in enshittification) leaves alot to be desired.

That wasn't created by the meritocratic elite, that was created by the "preexisting patronage systems" where rich pays to get their kids influential credential so that they can continue to have outsized influence on the country...

> They don't have the ability to solve the coordination problem, the housing crisis, involution, climate change and Donald Trump.

The current system is what caused those, why do you think that is much better?
by simonw | 2025-08-09 22:39:31+00:00
I'm beginning to suspect robust automated tests may be one of the single strongest indicators for if you're going to have a good time with LLM coding agents or not.

If there's a test suite for the thing to run it's SO much less likely to break other features when it's working. Plus it can read the tests and use them to get a good idea about how everything is supposed to work already.

Telling Claude to write the test first, then execute it and watch it fail, then write the implementation has been giving me really great results.
by andrewmcwatters | 2025-08-09 22:40:51+00:00
Can we not downvote this, please? It's a good question.

There's prior art for formal logic and knowledge representation systems dating back several decades, but transformers don't use those designs. A transformer is more like a search algorithm by comparison, not a logic one.

That's one issue, but the other is that reasoning comes from logic, and the act of reasoning is considered a qualifier of consciousness. But various definitions of consciousness require awareness, which large language models are not capable of.

Their window of awareness, if you can call it that, begins and ends during processing tokens, and outputting them. As if a conscious thing could be conscious for moments, then dormant again.

That is to say, conscious reasoning comes from awareness. But in tech, severing the humanities here would allow one to suggest that one, or a thing, can reason without consciousness.
by search_facility | 2025-08-09 22:41:09+00:00
They definitely does not aware of soviet reality that “roof over head” usually is not in the place where human want to live, same with job. if student after university decided (not by student, by state distributing workforce) to go work at city on polar circle - that means that student will go live and work here, without sunlight for the rest of his life! not joking, personal story with soviet collapse as happy ending (moved to normal place after that)
by kcartlidge | 2025-08-09 22:41:49+00:00
- Some mentions of Lazarus and FreePascal (so basically a cross-platform open source Delphi equivalent). And I'd agree with them.

- For C# I like AOT assemblies using Uno or Avalonia.

- For Go I like TCell (which does cross-platform console mode text GUIs [with cursor positioning, colours, mouse, etc]).

- If you're doing vibe coding I find it tends to work best with Electron.

- The big omission here is anything Python; I don't do desktop apps in Python so can offer nothing. Same for Ruby, though Hotwire Native looks interesting.
by smsm42 | 2025-08-09 22:41:55+00:00
> banking was non-existing in practice

There was a consumer bank (Sberbank) where you could store your money. Besides the risk of the state just keeping it (which also was real - the Soviet state never played fair) the problem was getting the money out would involve going to the office of the said bank, standing in a long line there, dealing with famously friendly (not) Soviet service, etc. So it was an option when you needed to store or retrieve a lot of money, not when you needed something day to day. And of course nothing like personal checks or personal credit or anything like that existed, so in day-to-day affairs, cash was always the only way.
by throwdbaaway | 2025-08-09 22:42:00+00:00
> use repomap tools on dependencies if creating new code that leverages those dependencies, and have that in context for that work.

It seems to me that currently there are 2 schools of thought:

1. Use repomap and/or LSP to help the models navigate the code base

2. Let the models figure things out with grep

Personally, I am 100% a grep guy, and my editor doesn't even have LSP enabled. So, it is very interesting to see how many of these agentic tools do exactly the same thing.

And Claude Code /init is a great feature that basically writes down the current mental model after the initial round of grep.
by bravesoul2 | 2025-08-09 22:42:05+00:00
The thing here is programming the job can be much more dull than programming the hobby. Occasionally (twice a decade) there can be a collision where you get to do something really cool like that at work. The higher ups want a realistic sky because their market research said it'll boost an OKR by 10 basis points. And then you are in luck!

That said there are niches where jobs let you do cool stuff all the time. Hard to find. Probably why gaming jobs are notoriously underpaid and overworked.
by antonvs | 2025-08-09 22:42:18+00:00
The English connotations of that are about a person who is overly loud, it wouldn't typically be used to describe someone

"Crier" is the closest if you're looking for a word along those lines, since it has historically been used in that way, although it's not a modern term.

There's a reason "herald" comes up here, though - it's actually a pretty close fit.

Your earlier suggestion of "announcer" works, though. "Reporter" might be even better, since it tends to imply a news context. You might say "telephone reporter" alone, for example, but you'd probably need to say "telephone news announcer" if you wanted to avoid it sounding like you were talking about someone who reads e.g. the time over the telephone.
by SkyPuncher | 2025-08-09 22:42:30+00:00
> Learning how to use LLMs in a coding workflow is trivial. There is no learning curve. You can safely ignore them if they don’t fit your workflows at the moment.

That's a wild statement. I'm now extremely productive with LLMs in my core codebases, but it took a lot of practice to get it right and repeatable. There's a lot of little contextual details you need to learn how to control so the LLM makes the right choices.

Whenever I start working in a new code base, it takes a a non-trivial amount of time to ramp back up to full LLM productivity.
by adastra22 | 2025-08-09 22:43:04+00:00
I’m afraid this is a case of “you’re doing it wrong.”

I use Claude Code with a dozen different hand tuned subagent specs and a comprehensive CLAUDE.md specifying how to use them. I review every line of code before committing (turning off the auto commit was the very first instruction). It is now the case that it is able to make a full PR that needs no major changes. Often just one or two follow up tweak requests.

With subagents it can sometimes be running for an hour or more before it is done, but I don’t have to babysit it anymore.
by barchar | 2025-08-09 22:43:12+00:00
It does really disfavor low productivity industries.

Actually, a core part of Sweden's original plan for social democracy was to have "solidaristic wage policy" where high wage workers would accept a lower wage in exchange for a higher one for low wage workers. The idea was you'd both squeeze low productivity businesses out _and_ provide a windfall to high productivity ones, who could expand faster.