skysight-inc/HackerNews huggingface dataset:
Yes! I think the name put a lot of people off, but it’s super good. Really makes you appreciate breakfast and the integral principles of the structural dynamics of flow as a nice bonus.
Relevant (and could probably have been a comment there): https://news.ycombinator.com/item?id=42909166
"Ask HN: What is interviewing like now with everyone using AI?"
Yes, it's called lying effectively.
Of course I see progress, but I feel like the bridge of "thinks" versus "regurgitates" is still far off, if it is still in the horizon with the current approach. IMHO.

edit: furthermore, LLMs probably tackle very little "real state" in the "make machines THINK" land. But a crucial piece on the overall puzzle.
We don't have unregulated environments.
I think the same kind of critical thinking that was required to reimplement and break algorithms must now be used to untangle AIs answers. In that way, it's a new skill, with its own muscle memory. Previously learnt skills like debugging segfaults slowly become less relevant.
You forgot a second sentence that completes the logic chain. Yes, "some tools are useful for some work", so what? That wasn't the original claim...
Not to mention that scientists spend a crazy amount of time writing grant proposals instead of doing science. Imagine if programmers spent 40% of their time writing documents asking for money to write code. Madness.
"Oops, I left the VM running. Again"
Stop the waste.
Real-time cost visibility in the cloud significantly reduces waste.
One-click install, Azure native. See what your wasting your cloud credits on...
Atmoz enhances the Azure Portal with live, real-time cost insights, recommendations, and scripts to fix it in one click.
Tell me what you think.
AI Isn't Cheating
>We don’t want to work with AI, we are going to pay the person for the persons time

If your interview problems are representative of the work that you actually do, and an AI can do it as well as a qualified candidate, then that means that eventually you'll be out-competed by a competitor that does want to work with AI, because it's much cheaper to hire an AI. If an AI could do great at your interview problems but still suck at the job, that means your interview questions aren't very good/representative.
Most arguments to standard library calls don't need to take ownership over memory, using a raw pointer or (const) reference is correct. Generally - smart pointers to designate ownership, raw pointers to "borrow".
The cursor auto complete? It's useful but the big thing is using sonnet with it.
It's as if you didn't bother reading my previous comment. Incredible.
Thanks, I was waiting for something realistic like that
They still (mostly) aren't.

From an user perspective, photos aren't files. Music isn't files. Contacts aren't files. Apps aren't files. App data isn't files.

The only things that "walk like a file and quack like a file" are documents, downloads, contents of external storage, network drives and cloud drives, and some Airdrop transfers.

Yes, it's technically possible to use the files app to store photos, music etc, but if you do that, "you're holding it wrong."
> This might be true for developers that only work for companies and never in their own time maybe.

So most people with young kids then
Using local translation models on Android
> The harder part is answering why it does what it does, which is harder for code someone else wrote.

That's a vital part of writing software though.
It's not just uploading a video... you are right about there's a loot of high quality videos, those take more work then writing a blog post though, several hours of video is cut down to minutes of content.
But the platform takes most of the ad money, almost all professional Youtubers have sponsors.
I still argue that you would be better off publishing content on your own website, but one problem is people now a day don't actually search for content, we are mindless zombies fed by algoritms, where most videos are just "clickbait".
Don’t worry, it will be bodies of people everyone hated all along - thinkers, “woke”, and so on.
>> It is not possible to perform an interview in ~4 hours such that someone sufficiently engages in what the job “actually entails”.

>> ... leetcode interview are an imperfect but relatively decent proxy.

I think all this is just the status quo that should be challenged instead of being justified.

When I conduct interviews (environment: a FAANG company), I focus on (a) fundamental understanding and (b) practical problems. None of the coding problems I pose are more than O[N] in complexity. Yet, my hiring decisions have never gone wrong.
Highlighting research that's useful is probably too difficult, but highlighting research that definitely isn't should be well within the bounds of the best existing reasoning LLMs.

There are a lot of common patterns in papers that you learn to look for after a while, and it's now absolutely within reach of automation. For example, papers whose conclusions section doesn't match the conclusions in the abstract are a common problem, likewise papers that contain fake citations (the cited document doesn't support the claim, or has nothing to do with the claim, or sometimes is even retracted).

For that matter you can get a long way with pre-neural NLP. This database tracks suspicious papers using hand-crafted heuristics:

https://dbrech.irit.fr/pls/apex/f?p=9999:1::::::

What you'll quickly realize though is that none of this matters. Detection happens every day, the problem is that the people who run grant-funded science itself just don't care. At all. Not even a little bit. You can literally send them 100% bulletproof evidence of scientific fraud and they'll just ignore it unless it goes viral and the sort of media they like to read begins asking questions. If it merely goes viral on social media, or if it gets picked up by FOX News or whatever, then they'll not only ignore it but double down and defend or even reward the perpetrators.
I've been trying both deepseek-r1:8b and deepseek-r1:32b using ollama on a local desktop machine.

Trying to get it to generate some pretty simple verilog code with extensive prompting.

It seems really bad?

Like specify what the module interface should be in the prompt and it ignores it and makes something up bad. Utterly rubbish code beyond that. Specify a calculation to be performed yet it calculates something very different.

What am I missing? Why is everyone so excited? Seems significantly worse to me than llama. Both o1-mini and claude haiku imperfect, sure, but way ahead. Both follow the same prompt and get the interface and calculation as specified. Am I doing it all wrong somehow (more than likely)?

After fixing up my open-webui install I tried "testing 1 2 3, testing. Respond with ok if you see this." Deepseek-r1:8b started trying to prove a number theory result.

Is there a chance this thing is heavily optimised for benchmarking not actual use?
> his claim was that the trolley problem isn't about real humans

Is it though? Let's look at the comment [0] written 8h before your reply:

> the trolley problem isn’t really about real humans in that situation

As in "don't take things absolutely literally like you were doing, because you'll absolutely be wrong". You found a way to compound the mistake by dropping the critical information then taking absolutely literally what was left.

[0] https://news.ycombinator.com/item?id=42907977
Depends the kind of website you are looking at. But yes, my personal preference is to use the translation icon (it looks similar to the one used for Google and Apple translate apps), and next to it, the currently selected iso code. Then in the dropdown, as a list, what I mentioned above.
just 27.5 Million params!
> It's a requirement that vessels which operate between US ports must be made in the US, crewed by the US, and flagged to the US.

The everything-bagel approach. One of those requirements incentivises US shipbuilding, the other two incentivise other things. Seems like the net effect was less US shipbuilding and a smaller US-flagged fleet. Given those effects, it doesn't seem likely to have increased the number of US merchant seamen either.
>> And I buy this stuff. Every time I need customer service and I'm getting stonewalled I just go onto a marketplace, find an exec and buy their details for pennies and call them up on their cellphone.

I find it funny how easy it is to find scammy websites which promise to remove your data (right...), but how hard it is to find the actual marketplaces where people trade this data. It also makes you think about what other systems have similar asymmetric interfaces for the public and the ones in the know (yes, I know there are plenty).
It sounds like corrosion in metals. There are many different damage mechanisms and protective effects, but at the end of the day you see weakened, oxidised metal.
Iteratively improving in previously released features does not imply fixing issues caused by those features.

Constexpr and auto have nothing to do with macros.
Incentives are themselves dangerous. We should treat incentives like guns. Instead we apply incentives to all manner of problems and are surprised they backfire and destroy everything.

You have to give people less incentives and more just time to do their basic job.
The effort involved, and legal risk is exactly the same as for any Copyleft license. If you don't know what your stack is doing, that is the problem -- not the license.
I also can't tell whether Stanford is joking, but the notion that he's a good fit for the job of biology professor is definitely funny!
I think you may have misunderstood the guidance from your legal team on this.

There is literally no way to prevent a candidate from disclosing a protected characteristic during an interview. Some obvious examples: they might show up to the interview in a wheelchair, they might be wearing a religious garment, they might be visibly pregnant, and so on...

What legal doesn't want, is you asking questions directly intended to elicit that kind information when the candidate didn't volunteer it. Asking the candidate a direct question like "are you planning to have kids?" makes it sound like that information will be used in the hiring decision.
No, I don’t.

I do think it might be conceptually possible and intellectually funny to come with flags that are generated from some pattern that some corpus of languages exhibit. Be it sui generis through some LLM, or relying more on scholar lexical/syntactic categorizations, or even something really more trivial like using a language-code[1] as entry.

On the other hand, with such an approach I’m afraid that chances are low that we can gain any adherence and a large recognition of the resulting flags from their speakers.

To my mind the best approaches as of today where already exposed in this thread: something best effort to propose the most likely user recognizable language and a clearly visible option to open a locale selector. If iconography seems a must have in the UI, showing something like a A/あ icon is rather usual by now.

[1] https://en.wikipedia.org/wiki/Language_code
Full Stack AI Agents – Solving the Decision Problem
It doesn't seems a very efficient way of doing things, for an efficiency department. I mean they should plan things out and hear arguments for what is effective or not rather than just stopping payments arbitrarily.
> something to be learned searching through the chapter as well

Learning to mentally sort through and find links between concepts is probably the primary benefit of homework
Is it advantageous? The AI generated responses to this question are prone to be dull.

It might even give the honest people an advantage by giving them a tip to answer on their own.
There are less horrible places than the one you apparently occupy. FYI.
There's a lot of sunk cost in programming. How you think about problems and solutions. Learning new ways to think about abstraction and synthesis of a solution takes time.

I go to syntax very quickly as well. To a literate fp person the syntax makes sense. To a neophyte its deeply confusing. I've asked Haskell programmers to speak lines of Haskell and the visible effort they go to, to use English to speak the syntax distinct from articulate the abstractions (which may well be simpler) is immense.

The "can program in the imperative mode" thing is however important. You can. We should teach more people to do this.
Yeah but I don't use that type in 100s of places.
Crypto finding takers outside crypto bros
Trump lost the 2020 election and Trump's kooks didn't accept that. Instead they engaged in violence at the request of Trump, while he was still president, on the basis of Trump's election denialism.

Peaceful transition also isn't the law. It was a norm. Until Trump pissed on it.

Trump ordered the vice president to overturn an election, and when Mike Pence refused that order, Trump sent a mob to have the VPOTUS assassinated.

And then, in possibly something like mass hysteria, they vote for Trump again. Or maybe it's an addiction to depravity, anger and drama. Like drug addiction.

Trump voters voted for a rapist, for president. This how low and desperate they've become. They kicked Mike Pence to the curb - all the boilerplate Republican policies they claim to want, but Pence wasn't good enough. It's pretty clear the right wanted an abusive personality.

Don't expect reasonable people to become docile about that.
100% of those warnings are state or federal government initiatives. Diageo isn’t doing that without coercion
And start treating the alliances as vital part of the whole, and stop betraying the fragile trust they are built on. Use Korean industry until the industry at home can catch up.
> Hmm, that is interesting; reading is harder?

Much, much harder. Sure, you can skim large volumes of code very quickly. But the type of close reading that is required to spot logic bugs in the small is quite taxing - which is the reason that we generally don't expect code review processes to catch trivial errors, and instead invest in testing.
Just to confirm, Ollama's naming is very confusing on this. Only the `deepseek-r1:671b` model on Ollama is actually deepseek-r1. The other smaller quants are a distilled version based on llama.

https://ollama.com/library/deepseek-r1
How to think about LLM Model Size
Would a plumber get in trouble if Mario, the owner, called it Super Mario?
If you really need to test them / check that they haven't used an LLM or hired someone else to do it for them (which was how people "cheated" on take-home tests before), ask them to implement a feature live; it's their code, it should be straightforward if they wrote it themselves.
So, you're saying you can recall a 2 week period in executive branch history that could hold a candle to what we've just witnessed? This idea of just keeping track of it all is real.

I marvel at the project management task that Trump & crew are maintaining in this flood-the-zone period, just to prevent duplication of effort and running into each other. There's already been a lot done to the DoJ, but its just started at the FBI.

Follow the firings -- and just hope you can keep up with who they're being replaced with. That's the real encroachment. We could be on the edge of real abuse when our law enforcement agencies fall under fascist control like this.
freestanding maybe? Embedded apps often don't shy away from using something like printf, yet they don't like unnecessary allocations.
> the trolley problem isn’t about really people

My actual words quoted below give one extra detail that makes all the difference, one that I see people silently dropped in a rush to reply. The words were aimed at someone taking these problems in a too literal sense, as extra evidence that they are not to be taken as such but as food for though that has real life applicability.

> the trolley problem isn’t really about real humans in that situation
The press and news are talking about R1 while what you've been testing is the "distilled" version.

Sadly, Ollama has a bit of a confusing messaging about this, and it isn't super obvious you're not actually testing the model that "comes close to GPT-4o" or whatever the tagline is, but instead testing basically completely different models. I think this can explain the mismatch in expectation vs reality here.
This insistence of using only human intelligence reminds me of the quest for low-background steel.
But you don't care about immaturity. You voted for Trump. The guy who said he can "grab them by the pussy, they let you do it".

It's just lockeroom talk. Right?

The entire Republican chorus backed up this juvenile locker room talk excuse. Trotted it out for the whole world to see. Not very mature. Did you love it?
You sound like the sort of person of old who “Why would you use the internet. Look in an encyclopaedia. ‘Google it’ is just lazy”

This trope is unbecoming of anyone sensible.
How do you guys do coding assessments nowadays with AI?

I don’t mind if applicants use it in our tech round but if they do I question them on the generated code and potential performance or design issues (if I spot any) - but not sure if it’s the best approach (I mostly hire SDETs so do a ‘easy’ dev round with a few easy/very easy leet code questions that don’t require prep)
The claim was that it's lazy to use a tool as a substitute for learning how to do something yourself. But when the tool entirely obviates the need for doing the task yourself, you don't need to be able to do it yourself to do the job. It doesn't matter if a forklift driver isn't strong enough to manually carry a load, similarly once AI is good enough it won't matter if a developer doesn't know how to write all the code an AI wrote for them, what matters is that they can produce code that fulfills requirements, regardless of how that code is produced.
What similar devices don't fight their own users wanting to access their own data ?
> AI gives super powers because it saves you an insane amount of typing

I feel like I'm going a little bit more insane whenever folks say this, because one of the primary roles of a software engineer is to develop tools and abstractions to reduce or eliminate boilerplate.

What kind of software are you writing, where generating boilerplate is the limiting factor (and why haven't you fixed that)?
There's a chance that the 8b and 32b models are not meant to work like chatgpt.. deepseek on the web chat is 671b as far as I know
Yeah in the example it was obvious.

Of course in a real life program, it may be lost in other code logic and, most importantly, the function performing the clone may not be so explicit about it (e.g. an "update" function that returns a different copy of the object).
true ... afaiac it should be auto-flagged always. politics and also other stuff that belongs on reddit. i do like reddit, but i do like also that hn isn't like reddit. at least not yet. but it seems headed there.
yes, that sounds also reasonable. Like a good piece of art it allows a range of interpretations. At the same time it being Ben Stiller, i see his absurd comedy treatment of whatever serious interpretation we come up with, Space Force on [dark and heavy] steroids.
On the other hand, if 20 hours of leetcode practice is all that stands between you and half a million dollars a year, isn't that a pretty good indicator that the interview process isn't hiring based on your skills, talent and education, and instead on something you basically won't encounter in the workplace?
So if you were to do a transformation like that you'd cut the code and paste it into a new function. Then you'd modify that function to make the abstraction work. An LLM will rewrite the code in the new form. It's not cut/paste/edit. It's a rewrite every time with the old code as reference.

Each rewrite is a chance to add subtle bugs, so I take issue with the description of LLMs "working on existing code". They don't use text editors to manipulate code like we do (although it might be interesting if they did) and so will have different issues.
Um. The German word is Diminutiv.

Were you thinking of „Verkleinerungsform“? Do people still use those Germanized terms? It feels a little old-fashioned to me, like saying „besitzanzeigendes Fürwort“ instead of Possessivpronomen.
Even in the early days AI was heavily funded by the private sector. Symbolics machines were partly promoted as a way to do AI research, back in the logic era. And the AI winter was mostly a grant funding phenomenon. When it became unfashionable in universities the field rebranded as ML and became commercially driven by (mostly) different people. Companies like Google invested in advanced ML research from day one.

Nowadays it's been rebranded back to AI due to the switch to neural methods, but there's been funding for AI from the computer industry for as long as the field existed.

I'm pretty sure AI would exist as a field and be in a similar place to where it is now, even if governments had never funded it at all.
That's some fancy words friend.
Right, last offer I got required 7 (non-HR) steps over a 4-month period, where around a dozen technical people got involved.

I don't/won't cheat, as I am a rather anxious person who can't really handle "covert ops". But at this point I totally understand those who do.
Is that the LLM's fault or SQLAlchemy for having that API in the first place? Or was that a gap in your testing strategy, as (if I'm reading it right), flush() doesn't write anything to the database but is only intended as an intermediate step (and commit() calls flush() under water).

I think we're in a period similar to self-driving cars, where the LLMs are pretty good, but not perfect; it's those last few percent that break it.
This puzzles me. `arg => expression`, `(args, …) => expression`, `arg => { block }`, `(args, …) => { block }`… they’re not hard or long to type, and there are the different forms of argument list and body, so that I imagine you’d want more than one snippet (at least for expression versus block, considering some style guides say “always parenthesise argument lists”), and the entire thing seems not at all worth it.
Musk says he is working to shut down "beyond repair" USAID
You’re using slightly improved qwen and llama not r1. R1 only has 600b model
IMHO What you describe is mostly a tooling problem. Current tooling doesn't let users to see the referenced/abstracted code as simply as the local code (for example, expand function definitions). So people tend to avoid abstracting it.
Ted Lasso, Silo, Apple knows how to make television.
Full Stack AI Agents
The coding interview I designed back in 2022 is still out of reach of all LLMs on the market while still being good at selecting people (I hired 6 people with it, all of them where great fit, out of 30ish applications so it doesn't seem to have a high false-negative rate either).

The main takeaway is that if you make design your interview questions to match the actual skill you're looking for, AI won't be an issue because it doesn't have those skills yet. In short: ask questions that are straightforward in surface but deep beneath with trade-offs that must be weighted by asking questions to in interviewer.
There is also a skill in prompting the AI for the right things in the right way in the right situations. Just like everyone can use google and read documentation, but some people are a lot better at it than others.

You absolutely can be a great developer who can't use AI effectively, or a mediocre developer who is very good with AI.
>communicating effectively

AI may not yet be as good an engineer as most coders, but it's already absolutely much better at written communication than the average sotware engineer (or at least more willing to put effort into it).