skysight-inc/HackerNews huggingface dataset:
Generally meta features like macros are _far_ more useful to library authors that need to do some sort of "reflection" on your application code.

Serialization libraries are frequently the largest beneficiary.

In my ideal world I don't need to write macros or use language meta/reflection features while (only) writing code to solve business problems, but to get to that ideal often the libs you use do need reflection capabilities

I'd argue that it's entirely reasonable for the average application/service developer to not appreciate the usefulness of macros. Not everyone needs to be a foundational library author, honestly we probably need fewer (looking at you npm/cargo micropackages)
It’s definitely on purpose - but if the purpose was to help the users making good choices they could actually give information - and explain what is what - instead of hiding it.
It's interesting how ChatGPT is securing major deals with governments and large corporations, while DeepSeek is gaining support from smaller startups. The contrast is also intriguing from the perspective of the power dynamics between the U.S. and China.
DeepMind - the company owned by Google, but behind things like AlphaFold is based on London. And one of the fathers of modern AI - leading the resurgence of research into neural nets - Geoffrey Hinton is British-Canadian.

He moved from Britain originally due to the difficulty in getting his research funded.

So the issue isn't one of intellectual capital - and while it's obviously the case that well place monetary capital is an issue - it's not clear to me what the real underlying issue is.

Perhaps Europe needs a tech/industrial revolution again - where the power shifts from the old guard to the new. Perhaps too many people in charge in Europe are from a certain class that studied history at university.
> writing 1000s of lines of react frontend code

Maybe we just located the actual problem in this scenario.
Yes, it's common to pipe through a shell.
The closest you can really get to objectivity is to observe which patterns of attributes tend to correlate well to people saying that that piece of media is good. In the end, "good" or "bad" is just my emotional reaction to receiving a piece of art, and there's plenty of art that have all of the usual attributes I associate with good art that leave me completely cold.

I prefer to ask whether a piece of art is "effective" or not. An EDM club banger, a classical piano sonata, and a rap battle are all trying to achieve very different things with valued qualities coming from their various subcultures, so ask what the artist is trying to achieve (intricate composition, or shifting units etc) and judge it only in that context
I think you fail to realize that's not the utilization end goal that's the problem with regulations, but the fact that you need to put a lot of checks and bureaucrats overseeing the development process to make sure "the rules are being followed".

Regulation for building a house in Europe are also totally valid, and what kind of person wouldn't follow them, right?

But then you need to send a pre project for approval that takes 6 months (and pay for it), then during construction you need to get a local government worker to check the progress several times and see if the rules are being followed (and pay for it) and after you finish the house, you need to wait up to 12 months for a government official to come inspect the house and declare that your house follows all their rules (and pay for it) and you are finally allowed to live in it.

So no, let's not try and declare that these rules are obvious, and great, and we need them and what kind of people wouldn't want to follow them? When in fact, these rules mean that at every single step, you are going to wait for the government to bless what you tell them you want to do and then to make you wait again while they check if you did what they allowed you to do.

P.S. do you even have any idea of what kind of hurdles small and big companies in Europe have to go every time they need to do something just because of personal data protection rules?
I love it when the "contrarian view" is absolutely not the contrarian view :)
C# has already enough material for pub Quiz, and no, not all of them are syntatic sugar, and require deep knowledge of the .NET runtime, and the way it interacts with the host platforms.

I imagine you never went too deep into unsafe, cross language interop, lambda evolution since the delegate days, events infrastructure, pluggable GC, RCW/CCW, JIT monitoring, the new COM replacement, how the runtime and language features differ across .NET Framework, Core, .NET MicroFramework, UWP, AOT compilation, Mono, .NET standard versus Portable Class Libraries, CLS friendly libraries,...

On top of that, all the standard frameworks that are part of a full .NET install on Visual Studio, expected that most C# developers know to at least have some passing knowledge on how to use them.
I agree on the grades part. And I was just thinking that the university that I went to never gave us grades during the year (the only exception I can think of was when we did practice exam papers so we had an idea how we were doing).

I think homework is more than a guide to what you should review though. It's partly so that the teacher can find out what students have learned/understood so they can adapt their teaching appropriately. It's also because using class/contact time to do work that can be done independently isn't always the best use of that time (at least once students are willing and capable of doing that work independently).
Introduction to Persistent Homology
One of the primary features of fascist rhetoric is that the enemy is presented as both strong and weak at the same time. Remember many of these people believe Biden created COVID and orchestrated a vast conspiracy to steal the election in 2020, all while being a feeble old man riddled with dementia.

Obviously Biden's administration was so terrible, so damaging, that the catastrophic reverberations of it will be felt for years to come. Drastic actions will need to be taken, and sacrifices will need to be made. That sort of thing.
A good answer in this situation would focus on demonstrating that you made a conscious decision based on the problem requirements and the approach that best suited the task. Here’s an example of a thoughtful response:

"I considered various approaches for solving this problem. Initially, I thought about using an LLM, as it's great for natural language processing and generating text-based solutions. However, for this particular challenge, I felt that a more algorithmic or structured approach was more appropriate, given the problem's nature (e.g., the need for performance optimization, a specific coding pattern, or better control over the output). While LLMs are powerful tools, they may not always provide the precision and control required for highly specific, performance-critical tasks, so I chose to solve the problem through a more traditional method. That said, if the problem had been more open-ended or involved unstructured data like text generation, I would definitely consider leveraging an LLM."

This answer reflects the candidate's ability to critically assess the problem and use the right tools for the job, showing maturity and sound judgment.

- GP, probably
that's different, they had location-dependent names at the time of this article too, the issue is specifically about the fact that even if you have location-dependent names you'd use the name that is commonly used in that location, not an arbitrary regulation name.
The UK is a financial (and legal) centre because of its regulations. They make the UK a trustworkthy broker for international companies to deal with. (Also its deregulations, making it easy to squirrel money away to tax havens.)

Not sure why AI would help there.
This is fascinating. The idea of leveling off in the learning curve is one that I hadn't considered before, although with hindsight it seems obvious. Based on your recollection (and without revealing too many personal details), do you recall any specific areas that caused the struggle? For example, was it a lack of understanding of the program architecture? Was it an issue of not understanding data structures? (or whatever) Thanks for your comment, it opened up a new set of questions for me.
You do need to incentivize something. If you incentivize nothing that's the same thing as an institution not existing and science being done purely as a hobby. You can get some distance that way - it's how science used to work - but the moment you want the structure and funding an institution can provide you must set incentives. Otherwise people could literally just stop turning up for work and still get paid, which is obviously not going to be acceptable to whoever is funding it.
You are reading that correctly, however, it is likely a limitation of the technology they used in the study.

Strangely, the didn't mention how they decided on stimulation volume, however, most studies will either set a fixed volume for the study, or measure the users hearing while they are awake, and then set a fixed volume for that person.

Our technology (and we're not the first to do this) adapts the volume based on brain response during sleep in real-time.

When you don't do this you risk either having the volume so low that it doesn't evoke a response, or so high that you decrease sleep depth, and don't get the correct response.

Therefore, anyone who did not get the appropriate volume would end up as a non-responder.

It is also more challenging for previously used algorithms to detect a slow-wave in older adults because the delta power is lower, so some of these participants may have had limited stimulation opportunities.

We've developed methods which improve on the state of the art, but we have not validated those in a study yet.
Primal Space: How Banks Magically Create Money [video]
Tools help us to put layers of abstraction between us and our goals. when things become too abstracted we lose sight of what we're really doing or why. Tools allow us to feel smart and productive while acting stupidly, and against our best interests. So we get fascism and catastrophic climate change, stuff like that. Tools create dependencies. We can't imagine life without our tools.

"We shape our tools and our tools in turn shape us" said Marshall McLuhan.
not a problem yet - we still start asking hard question first - on differences on TCP and UDP and which one is better and why - very deep rabbit whole I must say. Then simple questions - how do you manage k8s clusters and what you suggest for multi DC setups
Thoughts and knowledge are part of the illusion according to many schools of Indian philosophy. I last read it in Ramana Maharshi's book. I also read the same in Zen koans when Hofstadter wanted to push the same in GEB.

I think I also got the same impression from ZMM.
Like an 8 year old factoring large numbers it's not amazing how well it is done it's that it is done at all that amazes. Sure. Amazing but not at all useful and not something one would expect the kind of fuss we've seen.

Seems the explanation is the deepseek-r1 models I was using are not, in fact, deepseek-r1. Thanks all for the heads up.
How about that the Danish pharma giant Novo Nordisk, makers of Ozempic, is opening their AI/ML lab in London next to DeepMind and other tech giants, instead of in its back yard?

The only one close to UK in Europe is probably Switzerland and France but they too are mostly focused on research in universities rather than pushing out commercial products the way the US is exceeding at. Everyone else is not even in the game.
Ironically this is exactly how I am too. Even at work, if I'm talking through a problem on a presentation or with my boss, I'm much more scatterbrained, and I'll try to dodge those kinds of calls with "Just give me 30 minutes and I'll figure it out." which always goes better for me.

That said, now we're just talking about take home challenges for interviews and you always hear complaints about those too. And shorter, async timed challenges (something like "Here's a few hours to solve this problem, I'll check back in later") are now going to be way more difficult to judge since AI is now ubiquitous.

So I really don't think there's any perfect methodology out there right now. The best I can come up with is to get the candidate in front of you and talk through problems with them. The best barometer I found so far was to set up a small collection of files making up a tiny app and then have candidates debug it with me.
I tried it with Claude Sonnet 3.5 or whatever the name is, both tab-completed snippets and chat (to see what the workflow was like and to see if it gave access to something special).
That is part of "deliver working things".

A car hold together by duct tape is usually not considered a working car or road save.

Same with code.

"You also need to take into account how to judge if something is "working" or not — that's not necessarily a trivial task."

Indeed, and if the examiner cannot do that, he might be in a wrong position in the first place.

If I am presented with code, I can ask the person what it does. If the person does not have a clue - then this shows quickly.
Move 37.
Oh yes, they are!

You just need a small file, like a point file. Any gasheads remember those? And a single edge razor blade or the like to lift the reed.

To raise the pitch, you file the end of the reed, making it lighter so it vibrates faster.

To lower the pitch, you file near the attached end of the reed. I am not sure on the physics of this and would appreciate anyone's insight.

The specific tuning I've done many times is to convert a standard diatonic harp (the Richter tuning) to what is now called the Melody Maker tuning.

The Richter tuning was apparently designed for "campfire songs". You could just "blow, man, blow" and all the chords would sound OK.

Later, blues musicians discovered that you could emphasize the draw notes, the ones that are easy to bend to a flat note to get that bluesy sound. This is called "cross harp". For example, in a song in G you would use a C harp instead of one tuned in G.

The problem with cross harp is that the 7th is a minor 7th and you have no way to raise it up to a major 7th if that would fit your song. And the 2nd is completely missing! In fact you just have the tonic (G in this case) on both the draw and blow notes where you might hope to hit the 2nd (A). There is no A in this scale, only the G twice.

To imagine a song where this may be a problem, think of the first three notes of the Beatles song All My Loving. It starts with 3-2-1. Oops, I ain't got the 2. Just the 1 twice.

This is where the file comes in. You raise the blow 1st to a major 2nd. And you raise the minor 7th to a major 7th in both octaves.

Now you have a harp with that bluesy sound we all love, but in a major scale!
Recreating classic games with a bare microcontroller
> The burden of proof is on you, making the claim that the FAA chief and the crash are connected. What's your evidence?

I did not make this claim. I’ll restate my position so we’re clear: I have no idea whether they’re connected.

> I'm advancing the null hypothesis, that they have nothing to do with each other.

This is still a claim which requires evidence.

> I also don't believe the Eagles winning the NFC Championship 2 days earlier has anything do with the crash -- are you expecting me to provide evidence for that as well?

In general, evidence is required for any claim, yes. But in this case, something like “The Philadelphia Eagles are a football team, without any responsibility over airline safety” is probably enough evidence.
It's not that there's anything wrong with this in particular. It's just that the general market seems much more optimistic about AI impact, than the AI companies themselves.
> "Well it's not illegal"

What's good for the gander.... I promise you they will use AI to vet your application.
Designing Freedom (1973) [pdf]
I read, they don't merge PRs for Intel or AMD hardware, so it seems to be generally a bit of a shady project.
> 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.

Once AI is that good, the developer won't have a job any more.
It is very sensible position and I think the quote is a bit out of context, but the important part here is who it is coming from -- the company that makes money on both cheating in the job application process (which harms employers) and replacing said jobs with AI, or at least creating another excuse for layoffs (which harms the employees).

In a sense, they poisoned the well and don't want to drink from it now. Looking at it from this perspective justifies (in the eyes of some people at least) said cheating. Something something catalytic converter from the company truck.
Makes sense. I've never been asked to make such an exercise in real time, most of the time that would be a take home task - but I understand if someone wants to do that. Still it would be weird to demand that a candidate uses Google, wouldn't it?
Honesty is not something our modern societies optimize for, although I do wish things were different
First we need to rewrite the likes of LLVM, GCC, V8, CUDA,... into something else.

Which is not going to happen in our lifetime, even the mighty Rust depends on LLVM for its reference implementation.
I drove cars before the sat nav systems and when I visited somewhere, I'd learn how to drive to there. The second drive would be from memory. However, as soon as I started relying on sat navs, I became dependent on them. I can not drive to a lot of places that I visited more than once without a sat nav these days (and I'm getting older, that's a part of it too).

I wonder if the same thing will happen with coding and LLMs.
> I find that absolutely insane, if you cannot hold a basic conversation about your life without using AI then something is terribly wrong.

I'm genuinely curious what questions you ask during the behavioral interview. Most companies ask questions like "recall a time when..." and I know people who struggle with these kinds of questions despite being good teammates, either because they find it difficult to explain the situation, or due to stress. And recruitment process is not a "basic conversation" — as a recruiter you're in far more comfortable position. I find it hard to believe anyone would use an LLM if you ask them question like "what were your responsibilities in your last role", and I do see how they might've primed the chat to help them communicate an answer to a question like "tell me about a situation when you had a conflict with your manager"
I think it’s an interesting feature of current culture that we take it as axiomatic that people need to be ‘incentivized’. I’m not sure I agree. To me that axiom seems to be at the root of a lot of the problems we’re talking about in this thread. (Yes, everyone is subject to incentives in some broad sense, but acknowledging that doesn’t mean that we have to engineer specific incentives as a means to desired outcomes.)
Write something on your own. When stuck, consult the docs, Google the error message, and ask on StackOverflow (in this order).

There's no royal road to learning.
AI for thee but not for me?
Maybe they are ahead of the curve at finding that hiring people based on ability to exploit AI-augmented reach produces catastrophically bad results.

If so, that's bad for their mission and marketing department, but it just puts them in the realm of a tobacco company, which can still be quite profitable so long as they don't offer health care insurance and free cigarettes to their employees :)

I see no conflict of interest in their reasoning. They're just trying to screen out people who trust their product, presumably because they've had more experience than most with such people. Who would be more likely to attract AI-augmented job applicants and trust their apparent augmented skill than an AI company? They would have far more experience with this than most, because they'd be ground zero for NOT rejecting the idea.
I tried it on a few things I was familiar with just to assess its reliability.

The first was on a topic with which I am deeply familiar -- myself -- and it made three factual errors in a 500-word report: https://news.ycombinator.com/item?id=42916899

The second was a task to do an industry analysis on a space in which I worked for about ten years. I think its overall synthesis was good (it accorded with my understanding of the space), but there were a number of errors in the statistics and supporting evidence it compiled, based upon my random review of the source material.

I think the product is cool and will definitely be helpful, but I would still recommend verifying its outputs. I think the process of verification is less time-consuming than the process of researching and writing, so that is likely an acceptable compromise in many cases.
> I don't find anything wrong with this

It’s not about being wrong, it’s about being ironic. We have LLMs shoved down our throats as this new way to communicate—we are encouraged to ask them to make our writing “friendlier” or “more professional”—and then one of the companies creating such a tool asks the very people most interested in it to not use it for the exact purpose we’ve been told it’s good at. They are asking you pretty please to not do the bad thing they allow and encourage everyone to do. They have no issue if you do it to others, but they don’t like it when it’s done to them. It is funny and hypocritical and pulls back the curtain a bit on these companies.

It reminded me of the time Roy Wood Jr visited a pro-gun rally where they argued guns make people safe, while simultaneously asking people to not carry guns because they were worried about safety. The cognitive dissonance is worth pointing out.

https://youtube.com/watch?v=m2v9z2S5XzQ&t=190
This is an excellent comment and it more-or-less changes my opinion on this issue. I approached it with an "AI bad" mentality which, if truth be told, I'm still going to hold. But you make a very good argument for why AI should be allowed and carefully monitored.

I think it was the spell-checker analogy that really sold me. And this ties in with the whole point that "AI" isn't one thing, it's a huge spectrum. I really don't think there's anything wrong with an interviewee using an editor that highlights their syntax, for example.

Where do you draw the line, though? Maybe you just don't. You conduct the interview and, if practical coding is a part of it, you observe the candidate using AI (or not) and assess them accordingly. If they just behave like a dumb proxy, they don't get the job. Beyond that, judge how dependant they are on AI and how well they can use it as a tool. Not easy, but probably better than just outright banning AI.
Is there truly a moat there? Is there truly some very secret sauce that one must learn? Or can the results be replicated in reasonable time when they are developed.

Does it make sense to burn lot of money now? Or more to wait the technology and field to mature and then buy it for commodity prices. Think back to solar and wind power for example.
That’s cool. My main job is being a research scientist but i also work at a computational science consultancy that essentially builds numerical simulations for hire along with other software consultancy jobs. I occasionally have been asked to serve as an outside consultant for hiring data science positions. I’ve been wondering how to grow that a bit into more regular work because I enjoy it. Any thoughts on that?
How is a globally-scoped closure not a global variable?
It's also not helping the confusion that the distills themselves were made and released by DeepSeek.

If you want the actual "lighter version" of the model the usual way, i.e. third-party quants, there's a bunch of "dynamic quants" of the bona fide (non-distilled) R1 here: https://unsloth.ai/blog/deepseekr1-dynamic. The smallest of them is just able to barely run on a beefy desktop, at less than 1 token per second.