MurphyA/hacker-news huggingface dataset:
by mritchie712 | 2025-08-28 21:56:18+00:00
we[0] have a pretty complex agent[1] running on Pydantic AI. The team is very responsive to bugs / feature requests. If I had to do it over again, I'd pick Pydantic AI again.

0 - https://www.definite.app/

1 - https://pydantic.dev/articles/building-data-team-with-pydant...
by awesome_dude | 2025-08-28 21:56:46+00:00
I have a very similar (probably unoriginal) thought about some human mental illnesses.

So, we VALUE creativity, we claim that it helps us solve problems, improves our understanding of the universe, etc.

BUT people with some mental illnesses, their brain is so creative that they lose the understanding of where reality is and where their imagination/creativity takes over.

eg. Hearing voices? That's the brain conjuring up a voice - auditory and visual hallucinations are the easy example.

But it goes further, depression is where people's brains create scenarios where there is no hope, and there's no escape. Anxiety too, the brain is conjuring up fears of what's to come
by jeppester | 2025-08-28 21:56:50+00:00
In my company I feel that we getting totally overrun with code that's 90% good, 10% broken and almost exactly what was needed.

We are producing more code, but quality is definitely taking a hit now that no-one is able to keep up.

So instead of slowly inching towards the result we are getting 90% there in no time, and then spending lots and lots of time on getting to know the code and fixing and fine-tuning everything.

Maybe we ARE faster than before, but it wouldn't surprise me if the two approaches are closer than what one might think.

What bothers me the most is that I much prefer to build stuff rather than fixing code I'm not intimately familiar with.
by threetonesun | 2025-08-28 21:56:56+00:00
Many 60s/70s American muscle cars had racing pedigrees. It was a coupe with a V8, one could argue they were replaced by the JDM market with turbo 4s/I6s in the 90s early 2000s.

Maybe more importantly, either of the above had an appealing visual style (to some!) and had their own community around them. Teslas are pretty visually boring, you can't really modify them, but I suppose they have a community of their own who debates which version of software drives the car for you better.
by jibal | 2025-08-28 21:57:02+00:00
ALL of the rude behavior and trolling was yours (and you're still doing it) ... there's nothing rude about "Is a banana taped to a wall "art?" Your answer to that is the answer to your question.". And your behavior violates the site guidelines, whether it was "in kind" or not.

I need to bathe after reading your grossly dishonest excuses. Over and out.
by nmsmith | 2025-08-28 21:57:26+00:00
Hi there, I am the Nick whose design we're discussing. You raise some valid points: the blog post enumerates some limitations with Rust's model, but my design (as written) only resolves a subset of those limitations. We probably should have made that a bit clearer.

That said, there is still hope! I have been iterating on the design over the last 9 months and am fairly confident that I can model graphs, as long as a few restrictions are imposed, such as not being able to delete nodes. But I can't prove this will work yet, so we will need to wait and see what the next design iteration looks like. I'm fairly confident that the next iteration will be more powerful than the version presented in OP's blog post.
by kgwgk | 2025-08-28 21:57:44+00:00
The “paradox” may become apparent if you think the answer to all the questions below is the same (2/3). And if it’s not the same, why not?

——

You meet three people:

Alice has two children. You're told that at least one of them is a girl.

Bob has two children. You're told that at least one of them is a boy.

Csilla has two children. You're told that at least one of them is a lány. That clearly meant boy or girl because of the context, but you don’t know enough Hungarian to know what it is.

For each of them, what's the probability that they have a girl and a boy?

—-

You meet all the parents with two children in your neighborhood. Say there are 60 such families.

For 30 of them you’re told that at least one of them is a boy. What's the probability that they have a girl and a boy?

For the other 30 you’re told that at least one of them is a girl. What's the probability that they have a girl and a boy?
by jithinraj | 2025-08-28 21:57:44+00:00
Web Bot Auth solves authentication (“who is this bot?”) but not authorization/usage control. We still need a machine-readable policy layer so sites can express “what this bot may do, under which terms” (purpose limits, retention, attribution, optional pricing) at a well-known path, robots.txt-like, but enforceable via signatures.

A practical flow:

1. Bot self-identifies (Web Bot Auth)

2. Fetch policy

3. Accept terms or negotiate (HTTP 402 exists)

4. Present a signed receipt proving consent/payment

5. Origin/CDN verifies receipt and grants access

That keeps things decentralized: identity is transport; policy stays with the site; receipts provide auditability, no single gatekeeper required. There’s ongoing work in this direction (e.g., PEAC using /.well-known/peac.txt) that aims to pair Web Bot Auth with site-controlled terms and verifiable receipts.

Disclosure: I work on PEAC, but the pattern applies regardless of implementation.
by jacurtis | 2025-08-28 21:57:49+00:00
In a recent episode of Hard Fork podcast, the hosts discussed an on-the-record conversation they had with Sam Altman from OpenAI. They asked him about profitability and he claimed that they are losing money mostly because of the cost of training. But as the model advances, they will train less and less. Once you take training out of the equation he claimed they were profitable based on the cost of serving the trained foundation models to users at current prices.

Now, when he said that, his CFO corrected him and said they aren't profitable, but said "it's close".

Take that with a grain of salt, but thats a conversation from one of the big AI companies that is only a few weeks old. I suspect that it is pretty accurate that pricing is currently reasonable if you ignore training. But training is very expensive and the reason most AI companies are losing money right now.
by PaulHoule | 2025-08-28 21:57:55+00:00
Don't forgot to lay some of the blame on trucks, SUVs, and the chicken tax. [1] American car manufacturers aren't interested in making anything that can't be classified as a "light truck" because then they'd have to compete on a level playing field with foreign brands. So every kind of "car" has disappeared.

[1] https://en.wikipedia.org/wiki/Chicken_tax
by harikb | 2025-08-28 21:58:08+00:00
> Flow-Sensitive Type-Inference

imho, I don't consider Type-inference as a good thing when it happens from 50 lines ahead/below. How would regular people follow along?

Good case

x = "hello" // infer type as string - good thing.

Bad case

var/declare x;

50 lines later

if (....)

x = "world" // infer type as string - this is bad
by meatmanek | 2025-08-28 21:58:19+00:00
That would change my intuition quite a bit. Even assuming 100 kids were feasible in a human lifespan, the odds of 99 girls or 100 girls happening is (1 [arrangement where all the kids are girls] + 100 [arrangements where there are 99 girls and 1 boy]) / 2^100, or about 8e-29. Practically zero.

If we assume that each child really did have a 50/50 chance of being boy or girl, then the result would be that there's a 1/101 chance that it's 100 girls.

Given what I know about the world and genetics and such, I think it's much more likely that there's some predisposition by the couple to have girls.

If we think it's, say, 90/10, then the prior probability of the 100-girls case would be 0.9 ^ 100, and the prior probability of each of the 99-girls cases would be 0.9^990.1 -- i.e. the all-girls case is 9x more likely. 0.9^100 / (100 0.9^990.1 + 0.9^100) = 0.9 / (1000.1 + 0.9) = 0.9/10.9 = about 8% probability of having 100 girls, 92% probability of having 99 girls and 1 boy.

If we think the couple has 99:1 odds of girl:boy on each birth, then it's 0.99^100 / (100 * 0.99^990.01 + 0.99^100) or about 50/50 on whether they have 99 girls or 100 girls.

If we think the odds are 999:1, then it's 0.999^100 / (100 0.999^99*0.001 + 0.999^100) = around 90% chance they have 100 girls.

Someone else can do the math assuming an uninformative prior on the couple's girl:boy odds and calculating the posterior distribution given that we know there are 99 girls.
by bdangubic | 2025-08-28 21:58:24+00:00
I dont understand the need for this at all. I use the git. Inside one CC session on average there will be 80-160 commits. I can revert back whatever I want whenever I want. Whenever context gets hairy I clear and ask CC to review specific commits to continue or whatever. I must be missing something here completely what is the need for jj at all…
by pstuart | 2025-08-28 21:58:28+00:00
I think there will always be a desire for the "vroom vroom" factor, as well as the ability to work on it without an EE degree.

I don't think it's ever been logical but it ticks important emotional boxes so that makes sense.

I'm old and I drive a refurb'd Leaf and have never ever cared that my vehicle was not sexy. I've never been "normal" so never had the appeal but I understand it.
by mi12-root | 2025-08-28 21:58:29+00:00
Thanks for the feedback! When you say “custom,” do you mean additional integrations with LLM providers, or more documentation on how to build your own custom integration? If you mean the former, we’re currently focused on stabilizing the API and reaching feature parity with FoundationModels (e.g., adding streaming). After that, we plan to add more integrations, such as Claude, Gemini, and on-device LLMs from Hugging Face.
by machomaster | 2025-08-28 21:58:48+00:00
If it quacks like a duck...

There is no practical difference between an idiot on the internet and a smart troll role-playing an idiot 100% of the time.

Since youtube has been making a lot of objectively stupid decisions, it does not matter if they are actually stupid or this is some kind of meta commentary on the power elites running their way and ordinary folks not able to do anything about it. It's all the same in practice.
by leshenka | 2025-08-28 22:00:07+00:00
Wrong threat model. Solutions like mullvad/proton focus on privacy not breaking the blockade. They have well known entry points and therefore easily blocked. You can play cat and mouse game switching servers faster than censorship agency blocks them (e.g. Telegram vs Roskomnadzor circa 2018 [1]) but that gets expensive and not really focus of these companies.

What you need is open protocols and hundreds of thousands of small servers only known to their owners and their family/friends

1: https://archive.is/sxiha
by _dain_ | 2025-08-28 22:00:09+00:00
Booleans don't "remember" what they mean. They're just a `true` or a `false`, the association with the `is_authenticated` variable or whatever has to be maintained by programmer discipline. But when you have an enum variant like `Authenticated`, that's encoded in the value itself, helped by the type system. It can't be confused with some other state or condition.

Booleans beget more booleans. Once you have one or two argument flags, they tend to proliferate, as programmers try to cram more and more modalities into the same function signature. The set of possible inputs grows with 2^N, but usually not all of them are valid combinations. This is a source of bugs. Again, enums / sum-types solve this because you can make the cardinality of the input space precisely equal to the number of valid inputs.
by bbor | 2025-08-28 22:00:12+00:00
That's just a blatant misunderstanding of what diagnostic criteria are. They don't Actually ("ontologically") exist, they're Virtual constructs made for a purpose.

In particular, over half a century of personality research had supported the concept of personality “traits” or dimensions, rather than “disorders” or categories.

That is antithetical to the basic idea of a diagnosis. "You seem like an angry person" is not helpful for deciding which treatments to try.

Where does this leave us? We have to accept DSM-5 definitions from a legal and practical perspective. We have to use them for insurance forms, and to protect ourselves against lawsuits. But we don't have to believe in them.

Yes, that's the whole point of the book. I'm confident that it's covered in the intro.
by ACCount37 | 2025-08-28 22:01:03+00:00
"What's actually happening" is all your life you've been told that human intelligence is magical and special and unique. And now it turns out that it isn't. Cue the coping.

We've already found that LLMs implement the very same type of abstract thinking as humans do. Even with mechanistic interpretability being in the gutters, you can probe LLMs and find some of the concepts they think in.

But, of course, denying that is much less uncomfortable than the alternative. Another one falls victim to AI effect.
by MisterTea | 2025-08-28 22:01:14+00:00
I don't see loud cars dying off with muscle cars because I see more obnoxious BMW's along with a few Honda and Infinity with pop and gurgle tunes and open exhaust than Chargers, Mustangs, etc.

> There's just fewer and fewer people that need a loud noise maker to be happy,

Come to south Queens NYC and you'll find plenty of these people. There's a shop around the block from me that builds these noise makers and I get to hear them test drive them up and down the block.
Show HN: Security Test Framework – 16 automated security checks
by therealprwilo | 2025-08-28 22:01:19+00:00
I built a Security Test Framework for Node.js projects because most security tools are either too heavy, too expensive, or too scattered.

Run npx security-test auto — it auto-detects your project, runs 16 categories of security tests (XSS, SQL injection, CSRF, auth, headers, dependency vulns, etc.), and generates HTML/JSON/text reports. • GitHub: https://github.com/yourname/security-test-framework • NPM: https://www.npmjs.com/package/security-test-framework

Would love feedback from the HN community — especially on what tests or CI/CD integrations you’d want next.
by steveklabnik | 2025-08-28 22:01:41+00:00
> If gpt4 was basically free money at this point it's real weird that their first instinct was to cut it off after gpt5

People find the UX of choosing a model very confusing, the idea with 5 is that it would route things appropriately and so eliminate this confusion. That was the motivation for removing 4. But people were upset enough that they decided to bring it back for a while, at least.
by twoWhlsGud | 2025-08-28 22:02:15+00:00
This. If you are completely surrounded by light trucks as you grow up, then you are much less likely to ever think of actual cars (muscle or otherwise) at all. I grew up around 2000 lbs BMW 2002's (and the like) - a kind of vehicle that simply has vanished. So I could imagine lightweight sport sedans as a thing. If all you know are SUV's your concept of vehicle is going to be very different...
by fc417fc802 | 2025-08-28 22:02:40+00:00
And now you're being intentionally difficult. Please interpret things in the most plausible manner. Beyond common decency, it's part of the site guidelines.

By "not compromised" GP clearly meant a scenario where no malicious apps are present.

I agree that's a serious omission. I responded to your scenario (a nonzero number of malicious apps) in my earlier comment. Any Android device will defend against that regardless of the presence of attestation.

Any non-android device can still use online banking and thus attestation doesn't appear to accomplish anything legitimate. Building out proper support for hardware tokens would provide superior security in approximately all cases.

The specific "root on android" scenario isn't generally a concern. Typical implementations require explicitly granting the capability to a given app. A malicious app can't gain it without fooling the user, at which point it could more easily phish the credentials and possibly even proxy an entire session.
by hervature | 2025-08-28 22:02:59+00:00
> I’m currently going through an identity crisis (as a gearhead) as a result of this.

I would challenge you that it is your proclivity for logic that is causing your identity crisis. If you enjoy a certain aesthetic, the pursuit of that aesthetic is reason enough. You are already putting constraints on the concept of a car because strapping a rocket on wheels with wings is going to have much more performance than an EV. Redefine your pursuit to be the most performant muscle car and everything is squared. No identity crisis needed.
by chao- | 2025-08-28 22:04:09+00:00
Your answers are appreciated, but they beg further questions. Do you mind that I inquire further?

>1: Chase's business account wasn't appropriate for a tech startup; nor was it appropriate for the amount of money Mitchell was handling.

What properties make it inappropriate for a tech startup, specifically? What would be appropriate instead, and why?

>2: When your bank calls you after a very, very large money transfer, you should take the call.

He did take the call, but I take your answer to mean that Mitchell and Alex didn't have the right kind of conversation on the call. Is that correct? If so, what ought to occur on a call that follows a large transfer?
by epolanski | 2025-08-28 22:04:14+00:00
> It's an active engagement and best results are achieved when everything is planned and laid out in advance — which can also be done via vibe coding.

No.

The general assumed definition of vibe coding, hence the vibe word, is that coding becomes an iterative process guided by intuition rather than spec and processes.

What you describe is literally the opposite of vibe coding, it feels the term is being warped into "coding with an LLM".
by woah | 2025-08-28 22:04:49+00:00
> One of the consequences of this is that we should always consider asking the LLM the same question more than once, perhaps with some variation in the wording. Then we can compare answers, indeed perhaps ask the LLM to compare answers for us. The difference in the answers can be as useful as the answers themselves.

This is what LLM "reasoning" does. More than "reasoning" in the human sense, it just reduces variance from variations in the prompt and random next token prediction.
by Guthur | 2025-08-28 22:04:57+00:00
I just spent a good 2 hours trying to debug a SM6 Vulkan issue with unreal engine using an LLM, it had got me to good state but UE kept falling to load a project, it transpired that the specific error message would provide a fix as the top Google result, which I found when I eventually decided to look for myself.

LLM did help a lot to get some busy work out of the way, but it's difficult to know when you need to jump out of the LLM loop and go old skool.
by eqvinox | 2025-08-28 22:04:58+00:00
This is what IPsec TFS is for [https://datatracker.ietf.org/doc/rfc9347/]

> the focus in this document is to enhance IP Traffic Flow Security (IP-TFS) by adding Traffic Flow Confidentiality (TFC) to encrypted IP-encapsulated traffic. TFC is provided by obscuring the size and frequency of IP traffic using a fixed-size, constant-send-rate IPsec tunnel

(If they block a constant rate stream, that'll hit a whole ton of audio/video streaming setups)
by gck1 | 2025-08-28 22:04:59+00:00
I’m not in the US, but I had to order a bunch of hard drives from a US retailer. My country imports almost all electronics from the US through freight forwarding, and probably more than 90% of my online spending is with US retailers too.

The problem now is that nobody - including retailers and shipping companies - really knows how returns will be handled if the drives need servicing under warranty. The transport companies here are saying everything has to be declared down to the molecular level, and no matter what it is - even a return - tariffs and broker fees still have to be paid.

So it looks like I’ll have to halt importing from the US anything that comes with a warranty. The funny thing is, with all the crazy taxation the EU already has, US tariffs make importing from the EU actually cheaper once you factor in potential returns.

Granted, I live in a tiny country, and for the US economy this is probably just a drop in the bucket. But I can’t help wondering how much unforeseen collateral damage this will cause - it has to add up.
by jacurtis | 2025-08-28 22:05:50+00:00
This is very true. ChatGPT has a very generous free tier. I used to pay for it, but realized I was never really hitting the limits of what is needed to pay for it.

However, at the same time, I was using Claude much less, really preferring the answers from it most of the time, and constantly being hit with limits. So guess what I did. I cancelled my OpenAI subscription and moved to Anthropic. Not only do i get Claude Code, which OpenAI really has no serious competitor for.

I still use both models but never run into problems with OpenAI, so i see no reason to pay for it.
by fzeroracer | 2025-08-28 22:05:56+00:00
> AI can do 80% of the work. I can review it later. And I spend much less time reviewing than I would have typing up everything manually

Are you sure you're actually reviewing the code? Deeply, properly reviewing and understanding it? Because from what I've seen people that say they do, don't. That's why they 'speed up' from using LLM-generated code.

The old adage that it's far harder to review code than to write it still holds true.
by winrid | 2025-08-28 22:06:02+00:00
They don't need to be that expensive. Allow people to opt into lower safety standards (you are comparing with a motorcycle after all) and add a carbon tax with a threshold so I can pay for less complicated emissions equipment.

Also, the loud sound != big. V8 != Loud, esp when many v6 motors are close in displacement to Ford's 5 liter V8.
by sssilver | 2025-08-28 22:06:47+00:00
As a person who owned multiple Teslas I really don’t understand the “poor build quality” sentiment. What other car at the same price point has better build quality? And if one or two do, does that make the Teslas build quality “poor”?

I had a MINI. That was a build quality disaster. Major engine issues after only three years. I now have a Silverado 1500 LTZ. It has obvious build quality issues. Interior isn’t as good as it used to be. Gearbox has a banging sound. My Teslas seem so much better than either of those or most other cars I interact with really. I sat in my friends Toyota Camry the other day. The interior seemed so much cheaper, the sound quality so much worse, the cabin was so much more loud than my humble Model 3. What about my car has poor build quality that I am oblivious to?
by mostlysimilar | 2025-08-28 22:06:54+00:00
> AI potentially solves many of those challenges

Isn't it exactly the opposite?

Language barriers: LLMs are language models and all of the major ones are built in English, speaking that language fluently is surely a prerequisite to interacting with them efficiently?

Knowledge: famously LLMs "know" nothing and are making things up all of the time and sometimes approximate "knowledge"
by stillsut | 2025-08-28 22:07:37+00:00
> we should always consider asking the LLM the same question more than once, perhaps with some variation in the wording. Then we can compare answers,

Yup, this matches my recommended workflow exactly. Why waste time trying to turn an initially bad answer into a passable one, when you could simply re-generate (possibly with different context)

I wrote up an example of this workflow here: https://github.com/sutt/agro/blob/master/docs/case-studies/a...
by dcre | 2025-08-28 22:07:54+00:00
Are you referring to the post where I listed 4 claims and marked one ridiculous, one wrong, one unlikely, and one plausible?

He is not wrong about everything. For example, after Sam Altman said in January that OpenAI would introduce a model picker, Zitron was able to predict in March that OpenAI would introduce a model picker. And he was right about that.