skysight-inc/HackerNews huggingface dataset:
> AI made your homework? Guess what, the homework is a proxy for your talent, and it didn't make your talent.

Well, no. Homework is an aid to learning and LLM output is a shortcut for doing the thinking and typing yourself.

Copy and pasting some ChatGPT slop into your GCSE CS assignment (as I caught my 14yo doing last night…) isn’t learning (he hadn’t even read it) - it’s just chucking some text that might be passable at the examiner to see if you can get away with it.

Likewise, recruitment is a numbers game for under qualified applicants. Using the same shortcuts to increase the number of jobs you apply for will ultimately “pay off” but you’re only getting a short term advantage. You still haven’t really got the chops to do the job.
I am in germany, so by far not the same situation as in other areas of the world. If I would get such an assignment myself and I have the feeling that this will help the company and also me to verify, if it is a fit, I will do that 1 to 3 hour task very happily.
I've been arguing for not being too trusting in the code LLMs generate. I've seen deepseek-r1 and multiple chatgpt models try to solve a genuinely trivial issue in code by deleting the unit test. And that was a well established language. Sure, it did compile. But it didn't solve the runtime bug. You cannot replace logic and experience with the statistics of just things that already exist, especially when creating something new and innovative.
- high wages are not evenly spread geographically in the USA

- high wages are not evenly spread demographically in the USA

- the wage distribution seems to me to be unusual in that it has a very long fat tail whereas the UK's is very clustered (I've forgotten the right term) on the median.

- modern industry can be highly automated

- modern logistics mean that industry can be decentralised

I believe that the last two are new since the USA and Europe outsourced large amounts of their industry to China. However the bigger issue is that competitive industries require very significant capitalisation because on the one hand modern products are staggeringly well engineered (with the trade offs of cheap, good and sophisticated taken into account) and on the other hand the processes used to make them require lots of tools, infrastructure, and robots.
I think when it comes to Naval Power the US's grand strategy throughout the modern era has mostly been based on the fact that the continental US is, de facto, a (very) big island when it comes to the connections with the rest of the world.

So, in the event of a new world war they would have two options: one, maintain naval power superiority and thus ensure that the things that the US needs to come from over-seas still come through, or two, return to autarky and economic isolationism (which, up to a point, they could sustain based on their home resources) and hope for the best. It's interesting that the current US administration is doing a combination of the two, see the debacle for the Panama Canal when it comes to my first point, and the return to economic isolationism and even hints of wanting to incorporate Canada when it comes to my second point.

On the other hand Air Power has never ever won a big war all by itself. The only war that let's say was won via said Air Power alone was the 1999 war against Milosevic's Yugoslavia, and, possibly, the First Gulf War. But the US won't be able to win a conventional war against China or/and Russia based on Air Power alone, never.
You’ve been given the chance to show that your previous success wasn’t just a function of the domain you were in and team you were on.

Taking a flailing org and being visibly a part of turning them around will open a lot of doors in your current company. Notably those open doors won’t really translate if you switch jobs. If you switch jobs you’ll have to rebuild the trust that senior middle-management have in you.

At the end of the day if you want to find a small niche and stay in it then senior staff+ is likely not for you unless your technical area is in demand and very complex.
Google removed 2.36M apps from Google Play using AI threat detection
Django Updates: January 2025
But how likely is that?
> You can't ask people to not use AI when careful, responsible use is undetectable.

You can't make a rule, if people can cheat undetectably?
I generally trust Anthropic vs others, I think Claude (beyond obligatory censorship) ticks all the right boxes and strikes the right balance
Right now, my goto is signalhire
How did I never know this existed? Are there more secret pages like this??
Seems its "not politics" when the topic is inconvenient.
If you believe your catch rate is 100%, just because you've managed to identify a couple of people who were really bad at it, you might want to check your priors.
Both jets and birds fly but do it in a completely different way. Who said that there's only one way to achieve reasoning?
tl;dr

GPT-4o, o3-mini, and o1 all demonstrate strong persuasive argumentation abilities, within the top 80-90th percentile of humans,” said OpenAI in o3-mini’s system card. “Currently, we do not witness models performing far better than humans, or clear superhuman performance.
EU kicks off landmark AI law enforcement
> how many industries that trade in real goods have margins in excess of 25%?

Key point here is "real goods". Services in general, digital or financial especially, i could see it, but i guess those aren't concerned.
I don't think such a system does or can exist. e.g. nl-NL is distinct from nl-BE which is distinct from fr-BE. Using a country flag doesn't work if a country uses multiple languages. Languages themselves don't have icons to go with them like countries do, but even if they did it wouldn't distinguish between the same language spoken in different countries, which can matter a lot for how things get localized. nl-NL uses way more words with french roots than nl-BE for example.

What I tend to do is have a dropdown with a country icon and language name localized to that language for each language. My pet peeve is trying to switch a website from a language I don't speak into one I do speak and the dropdown listing "Dutch" as "Néerlandais" or whatever instead of "Nederlands". I don't speak french, why would I know what dutch is called in french?
AI did my gym workout, still no muscles.
This got me recalling tutorials at university. (One-on-ones with a professor)

Sometimes I would reach this strange state where I could be asked something by the professor, and I would say something based on what I had read, and the prof would say "yes that's right".

But I knew that I didn't understand it. Somehow I was producing the right answer, but there was a dissatisfaction that was hard to explain. Whether it was math or economics, it sort of felt like I was regurgitating or just mechanically solving equations, without any feel for what was actually being done.

The opposite also happened, especially in math. Thinking that I understand something, but then getting stumped when an obviously related question proved impossible.

However the first case is the weirder case, because the latter is simply exposing that you actually don't know something via external input, whereas the former gives you external validation that you really shouldn't have.
Wittgenstein thought lots of philosophical arguments were semantic ones when he wrote the TLP. He would later abandon this idea after two world wars in Philosophical Investigations.
No, not everyone can really use AI to deliver something that works.

And ultimately, this is what this is about, right? Delivering working products.
Definitely tell the new director what you want, and firmly, without threatening to quit over it - leave that unsaid. If you are really valued, s/he will try to accomodate you. If not, then you know where you stand and then it's time to put up or shut up.

I have never found any value in merely airing my feeling. Just say what you want, that is much easier for a boss to deal with.
Can't disagree more. Talent is built and perfected upon thousands hours practice, LLMs just make you lazy. One thing people with seniority in the field don't realize, as I guess you are, is that LLMs don't help develop "muscle memory" in young practioners, it just make them miserable, often caged in an infinite feedback loop of bug fixing or trying to untangle a code mess. They may extract some value by using it for studying but I doubt it and only goes so far, when started I remember being able to extract so much knowledge just by reading a book about algorithms, try to reimplement things, break them, and so on. Today I can use an LLM because I'm wise enough and I can spot wrong answers, but still feel becoming a bit lazy.
This seems like temporal only without as much server and complexity. Maybe they ignore it or it really is that simple.

Overall really cool! There are some scalability concerns that are brought that I think are valid but maybe you have a Postgres server backing up every few servers that need this kind of execution. Also, every function shouldn't be its own step but needs to be divided into larger chunks where every request only generates <10 steps.
Very nice to have these modern setups under freer open source licenses. I have all my data synced to the client to work offline, so it's very nice having FSRS available on iOS & elsewhere (+ ability to run the rust one)
> Put the candidate at ease - nervous people don't interview well

This is great advice. I have great success with it. I give the same 60 second speech at the start of each interview. I tell candidates that I realise that tech interviews are stressful -- "In 202X, the 'tech universe' is infinitely wide and deep. We can always find something that you don't know. If you don't have experience in a topic that we raise, let us know. We will move to a new topic. All, yes, all people that we interviewed had at least one topic where they had no experience, or none recent." Also, it helps to do "interview ramp-up", where you start with some very quick wins to build up confidence with the candidate. It is OK to tell them "I will push a bit harder here" so they know you are not being a jerk... only trying to dig deeper on their knowledge.
Physical labor. A friend of mine has a job like this, in their parents' egg wholesaler business. It's a hard job, but has two major benefits: keeps him in good physical shape, and lets him listen to audiobooks pretty much the whole time. I sometimes find myself envying him that.

For one, I thought I read way too much sci-fi in my life, but it turns out he's listened to every single book I did, every one I have on my "to read" list (except maybe Greg Egan stuff), and then a couple dozen ones I never heard of.
Right now I use SignalHire most of the time
Very impressive but I don't follow how the author can license it under MIT terms when they've trained it using material only licensed for research purposes.

Wouldn't research purposes be non-commercial and therefore be incompatible with MIT terms?
PRQL contributor here:

That is a valid point and something I've also been thinking about lately. I can't speak for the others but in my case the Python string interpolation syntax was the one I was most familiar with, other than bash, so it was just the default. The big idea really is to have string interpolation and the syntax is somewhat secondary but we do aim for ergonomics with PRQL so it is a consideration.

Since then I've seen more alternatives like `Hello ${var}!` in JS/TS and $"Hello {var}!" in F#. Not sure that there's a clear way to prefer one approach over the others.

What would you consider to be factors that would make you prefer one over the others?
Go All the Way: Why Golang Is Your Swiss Army Knife for Modern Development
That's my sentiment as well. It seems you can actually go lower and it's so sad and I think at some point that will turn into dangerous as well... The amount of people that actually care what happens when you run code is miniscule. They don't understand that code is not some ideal abstraction. Code actually exists and executes in the real world on real hardware.

A week or so ago I gave a talk at a game jam discussing some of these topics and most of the audience being people in their 20's didn't understand or give weight to what I said at all. Only a few people from that big audience came after and expressed interest to learn more. Hope is not lost, but we have to actively push back and fight against the nonsense that comes from all sides.

I can't wait for the AI, AI bros and hype surrounding it to crash and burn in a few years. It's not that these new technologies are not useful - they are. And they have their place, but quality matters. DO NOT SURRENDER YOUR FACULTIES TO "AI". You get good by struggling! If you don't want to get good at this - then don't do it anymore. As another comment in another thread around code snippets said earlier - "No snippets, no LLMs, no autocomplete".
You wouldn't show up drunk to a job interview just because its at brewery, would you?
I thought the whole point of ranges is to solve problems created by iterators, move semantics to take care of scenarios where nrvo doesn't apply, constexpr and auto because we were hacking around it with macros (if you can even call it that)?
As someone with a pretty long career already, and who's comfortable talking about it, I was a bit surprised that in three interviews last year nobody asked a single thing about any of my previous work. One was live coding and tech trivia, the other two were extensive take-home challenges.

To their credit, I think they would have hired "the old guy" if I'd aced their take-homes, but I was a bit rusty and not super thrilled about their problem areas anyway so we didn't get that far. And honestly it seems like a decent system for hiring well-paid cogs in your well-oiled machine for the short term.

Your method sounds like what we were trying to do ten years ago, and it worked pretty well until our pipeline dried up. I wish you, and your candidates, continued success with it: a little humanity goes a long way these days.
doesn't sound much different than googling and finding a snippet that gets you unstuck. This might be a shortcut to the same thing.
I'm using SignalHire most of the time recently
I read a Dan Brown book once. I can’t recall which book it was, or any of the details about it, or even when I read it - but I remember it was the biggest “page turner” I’ve ever read. I don’t think there is any book I’ve read faster.

I used to look down on pop music. But then I realized how hard it actually is to write a catchy hit song.

Surely writing a book that people find so engaging that they can’t put it down must also require talent.
>AI made your homework? Guess what, the homework is a proxy for your talent, and it didn't make your talent.

There's a difference between knowing how to use a calculator and knowing how to do math. The same goes for AI. Being talented at giving AI prompts doesn't mean you are generally talented or have AI-unrelated talents desired by an employer.
IDK its funny but at the end of the day it comes off as a jealous cope by critically unacclaimed unrenowned author michael deacon masked behind comedy
> In my email I encouraged the candidate to teach me something unrelated to our work, or programming related if they preferred that.

What if I decide to teach you something about the Quran and you don't hire me?

Perhaps this is just urban legend but from the stories I've heard hiring for FAANG-type companies there are people out there interviewing with their only goal being baiting you into a topic they can sue you over.

Worst instance I have heard of is when an interviewer asked about the books the candidate liked to read (since the candidate said they're an avid reader in their resume) and he just said that he liked to read the Bible. After not getting hired for failing the interviews he accused the company of religious discrimination.

I'm by no means an expert in US law and don't know the people this happened to directly so maybe it's just one big fantasy story but it doesn't seem that far fetched that

- If you are a rich corporation then people will look to bait you into a lawsuit

- If you give software engineers (or any non-lawyers) free rein on how to conduct interviews then some of them can be baited into a situation that the company could be sued over way more easily than a rigid leetcode interview

I think nothing came of the fellow who liked reading the Bible but I would imagine the legal department has a say in what kind of interview process a rich company can and can not use.
As a personal rule, I don't "play" the market with shorts and such: I already have a full time job, and as they say in poker: If you look around the table and can't identify the "sucker", it's probably yourself.

Yet today... I'm definitely more-tempted than I have been in a long long time. (Part of that is subconscious political-identity motivation stuff, of course.)
It was the same way I think a lot of us used textbooks back in the day. Can’t figure out how to solve a problem, so look around for a similar setup in the chapter.

If AI is just a search over all information, this makes that process faster. I guess the downside is there was arguably something to be learned searching through the chapter as well.
You can, but it would be pointless since it would just filter out some honest people.
Garmin has nothing on Strava. If you integrate with Strava and the user revokes the link, you have to delete all the data that came from Strava or you risk losing access to the API.

> I don't know why they lock down their stuff so hard like this.

Same reason every other company locks down your data. You are the product and they want to keep you locked in, feeding them data.

They can't have you running off with all your data when a new device comes out from a competitor that is better; that would force them to compete more!

Garmin has a long history of being lazy as fuck unless someone's actually competing against them. The smartwatch market heated up and lo and behold features and better models coming out left and right. Their bike computers would go years between refreshes..until Wahoo, Bryton, Coros, and Hammerhead started beating on their door.

Strava is much the same way. They were pretty free with access in and out, and tightened things down making it nearly impossible to export data.
There is ipex-llm support for Ollama on Intel GPU (https://github.com/intel/ipex-llm/blob/main/docs/mddocs/Quic...)
Much better approach is to ask the candidate about the limitations of AI assistants and the rakes you can step on while walking that path. And the rakes you have already stepped on with AI.
>This is truly dystopian and I imagine a backlash will get stronger as people realize it.

All it has to do for adoption to happen is to be incredibly convenient.
AI is a tool, and tool use is not lazy.
I've seen applicants use AI to answer questions during the 'behavioral' Q&A-style interviews. Those applicants are 'cheating', and it defeats the whole purpose as we want to understand the candidate and their experience, not what LLMs will regurgitate.

Thankfully it's usually pretty easy to spot this so it's basically an immediate rejection.
It's really worrying to me, even as a self proclaimed "LLM <-> AI" skeptic, to see what kind of stuff people pretend to get out from an LLM. Typewriter monkeys as a service almost.

Still useful for the odd task here and there, but not as useful as all the money being invested in this (except for the companies getting that money, that is).

edit: actual example of something I'd expect a real AI to be able to solve by itself, but currently LLMs fail miserably https://x.com/RadishHarmers/status/1885884032220643587
That is very debatable.
It depends on ones assessment on the risk of passively leaking a file on a poorly cleaned up "cloud" disk is lower or higher from an actual intruder getting access to environment variable.
Maybe it makes sense for you, however from their perspective, it's not an "irrelevant" part of the selection process, but the most important part.
I like good pixel dithering. The C64 demo scene has become really good at it. Just look at the girl picture in the frozen start pic. That shows really good taste in picking colors from the weird palette too.

https://www.youtube.com/watch?v=P5E6z7AMxIU
Unfortunately as you spend more time investigating this problem it becomes clear that replication studies aren't the answer. They're a bandage over the bleeding but don't address the root causes, and would have nearly no impact even if funded at a much larger scale. Because this suggestion comes up in every single HN thread about scientific fraud I eventually wrote an essay on why this is the case:

https://blog.plan99.net/replication-studies-cant-fix-science...

(press escape to dismiss the banner). If you're really interested in the topic please read it but here's a brief summary:

• Replication studies don't solve many of the most common types of scientific fraud. Instead, you just end up replicating the fraud itself. This is usually because the methodology is bad, but if you try to fix the methodology to be scientific the original authors just claim you didn't do a genuine replication.

• Many papers can't be replicated by design because the methodology either isn't actually described at all, or doesn't follow logically from the hypothesis. Any attempt would immediately fail after the first five minutes of reading the paper because you wouldn't know what to do. It's not clear what happens to the money if someone gets funded to replicate such a paper. Today it's not a problem because replicators choose which papers to replicate themselves, it's not a systematic requirement.

• The idea implicitly assumes that very few researchers are corrupt thus the replicators are unlikely to also be. This isn't the case because replication failures are often due to field-wide problems, meaning replications will be done by the same insiders who benefit from the status quo and who signed off on the bad papers in the first place. This isn't an issue today because the only people who do replication studies are genuinely interested in whether the claims are true, it's not just a procedural way to get grant monies.

• Many papers aren't worth replicating because they make trivial claims. If you punish non-replication without fixing the other incentive problems, you'll just pour accelerant on the problem of academics making obvious claims (e.g. the average man would like to be more muscular), and that just replaces one trust destroying problem with another.

Replication failure is a symptom not a cause. The cause is systematically bad incentives.
What's funny is that the exec I got on the phone was super supportive and helpful and was genuinely amused to hear from me and hear what was happening. He put me in touch with their "Executive Support Team" and it was after this that I guess someone realized they didn't like the route I had taken.

I feel somewhat vindicated after this announcement (though it does nothing to bring my account back):

https://www.engadget.com/cybersecurity/cfpb-fines-block-175m...

> Accessing any kind of customer service for Cash App was a challenge, too, according to the CFPB. Block included a customer service number on Cash App cards and in the app's Terms of Service, but calling it would it ultimately lead users to "a pre-recorded message directing consumers to contact customer support through the app."
I hope volunteers and others are able to save as much as possible
of the data.

Removing and altering of the information and data is one of the fundamental
threats in our digital world.

It probably makes the most sense to do this on a daily basis.
If something new, if published, grab it as soon as possible.

Data can also be redacted or altered for a variety of reasons,
being able to see the before and after states can be illuminating.

Something I feel is missing here are statistics for each administration.

Does this only happen under a Trump administration, or does it happen
to smaller or larger extent under other administrations?

I don't know how far back this federal goes so it might not be easy,