skysight-inc/HackerNews huggingface dataset:
Well, I respect the scale and speed. My process was still working fine at ~5 per month. I have doubts it'd work with orders of magnitude more. There's a lot of intuition and finesse in there, that is probably difficult to blindly delegate. Plus, big companies have very strong internal forces to eliminate intuition in favour of repeatable, measurable processes.
SpaceX would be a shame, but it's not like any tesla news these days makes did productive discussion.
You are hard to impress. Running a 1/20x sized version locally that would be sci fi level 10 years ago.

For such small models I would recommend specialized models only. Like Deep Seek Coder. But I think that one is lagging behind the state of art now.
> An Eastern European solution

Made me chuckle. Funny 'cause it's true. About the trolley problem, if taken literally (people on tracks, etc.) pulling the lever exposes you to liability: you operated a mechanism you weren't authorized to use and for which you had no prior training, and you decided to kill one innocent person that was previously safe from harm.

Giving CPR is a very tame/safe version of the trolley problem and in some countries you're still liable for what happens after if you do it. Same when donating food to someone who might starve. Giving help has become a very spiny issue. But consciously harming someone when giving help in real life is a real minefield.

P.S. These philosophical problems are meant to force a decision from the options given. So assume the the problem is just a multiple choice one, 2 answers. You don't get to write a third.
There are a bunch of subtly different ways to perform a coding interview.

If the interviewer points you at a whiteboard and asks you how to reverse an array, most likely they're checking you know what a for loop is and how to index into an array, and how to be careful of off-by-one errors. Even if your language has a built-in library function for doing this, they'd probably like you to not use it.

If the interviewer hands you a laptop with a realistic codebase on it and asks you to implement e-mail address validation, they're going for a more real-world test. Probably they'll be fine with you googling for an e-mail address validation regex, what they want to see is that you do things like add unit tests and whatnot.
I stopped keeping a mobile number many years ago.

Phone is wifi only.

In particular, I do not use the contacts functionality built into the phone.

(This is /e/OS, which helps, but I'll be moving to Mobian as soon as it is viable.)
I do lots of technical interviews in Big Tech, and I would be open to candidates using AI tools in the open. I don't know why most companies ban it. IMO we should embrace them, or at least try to and see how it goes (maybe as a pilot program?).

I believe it won't change the outcomes that much. For example, on coding, an AI can't teach someone to program or reason in the spot, and the purpose of the interview never was to just answer the coding puzzle anyway.

To me it's always been about how someone reasons, how someone communicates, people understanding the foundations (data structure theory, how things scale, etc). If I give you a puzzle and you paste the most optimized answer with no reasoning or comment you're not going to pass the interview, no matter if it's done with AI, from memory or with stack overflow.

So what are we afraid of? That people are going to copy paste from AI outputs and we won't notice the difference with someone that really knows their stuff inside out? I don't think that's realistic.
In my case it went from a patchy 1mbps to a stable 20mbps right away, according to my router's admin page - right after resoldering the resistor and connecting the antenna.

Resoldering the 0 ohm resistor was like an adventure, but somehow managed to connect the correct pins. The end result looks like following:

https://imgur.com/a/LJflZ80
Doesn’t help against your cousin who shares your data.
not only is Verilog comparatively "niche"

the mind model behind it very different then that of "normal" programming languages, so less reuse of learned knowledge from other places ("knowledge" for a lack of better wording)
> In life there is no cheating

Oh, my sweet summer child
Bluesky now has 30 million users
The bigger advantage with analog is being able to use cheap repeaters to boost the signal back to home.

With digital, you can go from 30-50km with the proper equipment, noise free environment etc... It looks like the video for that has been taken down. But you can find the discussion here: https://greyarro.ws/t/digital-fpv-dji-vs-hdzero-vs-orqa-vs-w...

The "allowed regime" also differs based on where you live. Iirc 25 mW is the maximum permitted power in Europe. Have to double check. That gives you about 100-500 meter range in an open area.
>In life there is no cheating

Huh?

>You're just optimizing for the wrong thing. AI made your homework? Guess what, the homework is a proxy for your talent, and it didn't make your talent.

Isn't that the definition of cheating? Presenting a false level of talent you don't possess?
Complete opposite experience for me on archlinux. Consider reporting your problems to fix them for others too.
I think it's a nice first step in running web browsers from the keyboard. Well, beyond built-in functionality.

You push 'f' to get link hints, if there's few they'll be things like 'a', 'c', 'j', 'l', if many it'll build up algorithmically, most I've seen is triples, like 'ade'. You push those keys and it opens the linked page. 'H' to go backwards, 'd' and 'u' to scroll down and up, 'yf' and then a link hint to copy a link URL, 'x' to close a page and 'X' to open the last closed, and so on.

Some people want more, like vim motions in input fields and so on, so they opt for more complex tools.
Azure/AWS biggest competitor is going to be LIDL, not Hetzner. Hetzner competes with Digitalocean et al.
I've read all the twilight books. Not because they were good, not because I was engaged the entire time, but for the simple fact that I wanted to know how it would end.

Why not just read the last chapter?

Because I wanted the ending to make sense, and the series kept throwing in new characters to cover up its faults, like how Christopher Nolan throws an entire orchestra to cover up lack of drama or meaningful dialogue.

Sometimes you just know you're in for a bad time, but the starting premise is interesting enough for you to want to know how it all wraps up.
Seems pretty clear that if you want someone to do work for you (e.g. recommend you books you will like) they might need paying somehow.
Let's talk about a task tracking system for AI agents
DeepMind has made some really amazing stuff.

The UK will need to be an AI hotspot if we want to continue being a financial centre.
The Startup Drake Equation
https://cdn.bsky.app/img/feed_fullsize/plain/did:plc:th64qrg...
I can even feel it in my own coding. I've been coding almost my entire life all the way back to C64 Basic and ever since I am relying on Copilot for most of my regular work I can feel my non AI assisted coding skills get rusty.

That's a scary thing
Am I the only one worried on the poster's behalf that their entire office is gonna know about this post, first thing in the morning?

Or are they playing some 3D chess, and that was the plan all along?

Not that they are saying inherently bad things about the company, but the various doubts they express may not be seen as a strength (not that I wholeheartedly subscribe to that view).
If your test can be done by an LLM maybe you shouldn't be hiring a human being based on that test...
The author was using Gnome, which is meant to be the most mature Wayland implementation given its developed by Redhat which is also the same company that is the biggest driver of Wayland protocol.
Just check https://ipinfo.io/ to see how close your IP points to your location. For most targeted content the city is good enough. And honestly if I'm one of 1 million people it's ok.
Maybe you could allow using AI, but only through the interviewer-provided interface. That interface would allow using any model the candidate likes, but before sending the response it will inject errors into the code (either randomly or through another AI prompt).
Yes, the helo pilot accepted responsibility for tracking the 'CRJ' traffic via the visual separation callout, but unfortunately identifying AA 5342 in this way is not a clear or unique way to do so. They are a common plane type and come in several sizes/configurations.

That last second call from ATC should have been more than a confirmation that they had the traffic in sight. They were less than 1000ft apart in that moment. It should have been to tell them that the Collision Avoidance ('CA') system was alerting and that they had to "pull up". Even if 'pull up' was all that was said, it would have been better than asking for a confirmation of visual separation.
Using language like "thinking" doesn't bother me. I'm not a stickler for precision language in colloquial speech.

I do think it's important to deflate the hype and give context to what you mean by "thinking" in products, technologies and so on. Calling it a "stochastic parrot" is a bit pithy but not unreasonable. Plus it's memorable.
How did racist mass texts bypass some anti-spam guardrails?
Create Dynamic Wallpapers on Windows
> The marxist perspective for example based in isolation and collectivism, with the assumptions of the static unchanging individual.

Maybe i'm reading the synatx wrong here, but if you are implying that marxism has a static unchaning view of the individual then this is the complete opposite of marxism. Dialectial materialsim (marxism) has the never ending change (movement) of everything in it's very core of it's philosophical understanding. There is literally nothing more distilled for a marxist that everything in the universe changes, let alone the individual.

Not sure how you arrived at that rationale.
Judging by this analysis one simple approach would be to search for control-flow desynchronizations, ARM is easier since instructions are aligned on 2/4-bytes but the variable instruction format for x86/x64 is used here to make the life of the decompiler harder.

However, you can store a map of how instructions are placed and detecting cases where instructions overlap to different sequences should be a big red flag for an AV tool (that said, it's not impossible to disguise instruction targets enough that an analyser would need to be nearly Turing Complete to find even this).
Yeah, I know. I think maybe there are interested. Thanks for the comment and link
What data sets do you use when testing this or other open source models?
> The type of p is char[] which decays into a pointer and the type of (p+1) is char . Because it is char and not char * restrict, any assignment through such a pointer can be assumed to modify any and all data in a program.

Out of bounds access is classic UB. The compiler is allowed to assume that you never access an array out of bounds. Since you never access p out of bounds, the effects of any write to p will not affect any "object" that is not p.

>Therefore, the assumption that p[0] does not change and can be swapped out is not somehow surprisingly wrong, but simply entirely unfounded.

I hope you notice your small mistake. It's print(q[0]), not print(p[0]), there is no "p" in the print. It's q[0] and q[0] is not p. The write to p did not affect q, because that would be UB.

>It is up to the compiler to prove for itself that assignment through pointers does not change data it's interested in from before to after the assignment. (except, of course, in the case of restrict pointers, where the programmer makes this guarantee). This is not very difficult, at least conceptually.

The code accesses q[0], not iq. You might say that if you did print(*iq), that the compiler should definitively know that iq and ip are the same and therefore a write to ip would also be a write to iq, but the code uses q[0], which is a memory address that is not proven to be identical to ip.

Then again, what you're hoping for here is that the compiler fixes the UB for you, which is not the point of UB. You're supposed to rely on your godly C programmer instincts to never write code with UB in the first place.
>allowing to be taken over by culture of lazy (and lazy cultures) are all fixable

Please wait a bit until I've leveled up to the capitalist class. I'll be there any day now. Thank you.
If everybody wanted to work on the easy problems / already successful products / coolest new tech, we wouldn't be able to run any companies at all. If you are as good as you think you are, you should be able to take this unsuccessful team, turn it around and make it a winning story that will propel you even higher in your org+career.
As was said above, don't just add a number from 1 to 6. You want your ciphertext to be indistinguishable from random, so in this case (assuming only letters and no punctuation nor space), you need to add a number from 0 to 26. And you need a uniform distribution, or again, statistical analysis will screw you.

Now one does not simply generate a uniform random distribution from a d6. You can't throw the die 5 times and add the results for instance. First, you'll get a number between 5 and 30. Not only the range falls short one letter (25 possibilities instead of 26), what you get is a binomial distribution, heavily skewed towards the middle numbers (5 and 30 are very improbable in comparison).

My recommendation here would be to throw the die once, subtract 1, multiply by 6, throw it a second time, add it, subtract 1. This will give you a uniform distribution between 0 and 35 (assuming your die is perfectly fair, which, spoiler alert, it isn't). Think of it of a 2-digit base 6 number. Assign a number to each letter of the alphabet (and now you can even support spaces & punctuations, or numbers), add (modulo 35) the result of your die throw, do not translate the result to an encoding with less than 36 symbols, and now you have a proper one time pad.

One thing that's crucial when attempting anything cryptographic: make sure you've got the maths down. Ideally you should be able to construct a rigorous (even machine verified) proof that your stuff works as intended. For the one time pad it's relatively easy. But you need to do it, that's how you'll notice that if you encrypt "aaaaaaaaa" your result will only yield letters between B and G, which you'll agree doesn't hide your plaintext nearly as well as you intended.
If I had to do real world on-job coding while someone looks over my shoulder at all times (i.e. screensharing), I'd be flipping burgers.
the biggest change I've seen as a remote dev is considerably less replies to my non-AI made cv, I think the competition for cheap labor got much harsher
But that latitude and longitude might still be the middle of some city or country and not an exact location. It's not really clear how close it is.
YC Application Tips
A nitpick, but should they really call it a clash of titans? Maybe rather David versus Goliath?
For me, getting what's in my head out onto the screen as fast as possible increases my productivity immensely.

Maybe it's because I'm used to working with constant interruptions, but until what I want is on the screen, I can't start thinking about the next thing. E.g. if I'm making a new class, I'm not thinking about the implementation of the inner functions until I've got the skeleton of the class in place. The faster I get each stage done, the faster I work.

It's why I devoted a lot of time getting efficient at vim, setting up snippets for my languages, etc. AI is the next stage of that in my mind.

Maybe you can keep thinking about next steps while stuff is "solved" in your head but not on the screen. It also depends on the type of work you're doing. I've spent many hours to delete a few lines and change one, obviously AI doesn't help there.
Anyone feeling like not learning much anymore?
Show HN: Free Crunchbase Alternative with Semantic Startup Search
I struggled to find other startups doing similar things because keyword searches missed so much. Only to come across a startup doing the exact same thing a week later. So, as a side project, I built a semantic search engine that allows people to search based on descriptions rather than exact words. It’s been incredibly helpful for me, and I hope it can help others too!
Ollama is "taking flak" for the confusion because it's entirely created by them. If they renamed/split what they provide into deepseek-r1 and deepseek-distilled-r1, way less people would probably be confused about this.
C# has a lot of features but most of them feel like simple syntactic sugar that make the language a joy to use and they interact nicely together.

C++ has lots of features that interact with each other in unexpected ways that could leak memory or access freed memory etc.
I can't say I've interviewed someone to which this applies - unfortunately! Probably just doesn't get surfaced by my channels.

I would definitely not expect someone out of work for a while to have any meaningful side projects. I mean, if they do, that's cool, but I bet the sheer stress of not having a job kills a lot of creativity and productivity. Haven't been there, so I can only imagine.

For such a candidate, I'd probably want to offer them a time limited freelance gig rather quickly, so I can just see what they work like. For people who are already in a job, it's more important to ensure fit before they quit there, but your scenario opens the door to not putting that much pressure on the interview process.
Interview problems are never representative of the work that software developers do.
It's true that small businesses and craftsmanship are not efficient, but that's not usually the main reason why houses are expensive. They are usually expensive because of planning controls. Look at the price of land: in places where houses are expensive, land with planning permission is by far the largest component of the cost of a house. Building work being expensive is usually a consequence of this.

Having said that, I've no idea where you live so it could be completely different in your area
> and also faster than it takes me to verify the answer given by the machine.

I always thought there was a kind of NP-flavor to the problems for which LLMs-like AI are helpful in practice, in the sense that solving the problem may be hard but checking the solution must be fast.

Unless the domain can accomodate errors/hallucination, checking the solution (by a human) should be exponentially faster than finding it (by some AI) otherwise there's little practical gain.
I know that, but I’m not replying to a comment about caffeine, rather the opposite.
Rustsec-2025-0004: OpenSSL: SSL:select_next_proto use after free
I think this hits the nail on the head. Academics have been treated like assembly line workers for decades now. So they’ve collectively learned how to consistently place assembled product on the conveyor belt.

The idea that scientific output is a stack of publications is pretty absurd if you think about it for a few minutes. But try telling that to the MBA types who now run universities.
Did you try: https://chat.deepseek.com/
The interesting thing about audio chains is that they do NOT follow the "as bad as the weakest link" principle. A poor quality MP3 will be much more listenable on an overall crappy setup than on a high-end setup, mostly because the crappy setup will cut out both the lows and highs and leave you with an OK "background music, more or less".

If you're not about playing your FLAC collection via either decent headphones and/or decent HiFi setup then pretty much the only thing you should care about is "is there noise?". Which probably isn't there. And if it is - start with your cables, then your PSU.

Also, check software. Maybe your old setup had some software shenanigans (or your new one has - like a "headphone" profile selected) and that's the difference you are perceiving.

In terms of caring about "quality" you do need to start with CD-level material, and then the rest of the chain should follow according to your needs and preferences; there is no point buying a $400 USB DAC and hooking it to a $15 headphones; and if 128kbps MP3s sound OK to you then congrats your audio needs are effectively non-existent, anything will do (and I do not say that disparagingly; it's _fine_).
Not really true anymore. Creators have talked about how youtube's incentive structure is pushing towards longer videos now. Not necessarily higher-quality ones, and posting more volume is still generally going to help, but because youtube's now optimising for watch time instead of views, long videos are pretty heavily rewarded. (In fact, as always, the high-effort but short content like animations are the least 'efficient' genre on youtube).
Which, according to the Ollama team, seems to be on purpose, to avoid people accidentally downloading the proper version. Verbatim quote from Ollama:

> Probably better for them to misunderstand and run 7b than run 671b. [...] if you don't like how things are done on Ollama, you can run your own object registry, like HF does.
You're right: Republican Senator Hawley introduced that bill Friday. https://www.hawley.senate.gov/wp-content/uploads/2025/01/Haw...
Late Sunday night, I gained access to OpenAI’s newly launched Deep Research and immediately tested it on a draft blog post about Uniform Electronic Transactions Act (UETA) compliance and AI-agent error handling [1]. Here’s what I found:

Within minutes, it generated a detailed, well-cited research report that significantly expanded my original analysis, covering:
* Legal precedents & case law interpretations (including a nuanced breakdown of UETA Section 10).
* Comparative international frameworks (EU, UK, Canada).
* Real-world technical implementations (Stripe’s AI-driven transaction handling).
* Industry perspectives & business impact (trust, risk allocation, compliance).
* Emerging regulatory standards (EU AI Act, FTC oversight, ISO/NIST AI governance).

What stood out most was its ability to:
- Synthesize complex legal, business, and technical concepts into clear, actionable insights.
- Connect legal frameworks, industry trends, and real-world case studies.
- Maintain a business-first focus, emphasizing practical benefits.
- Integrate 2024 developments with historical context for a deeper analysis.

The depth and coherence of the output were comparable to what I would expect from a team of domain experts—but delivered in a fraction of the time.

From the announcement: Deep Research leverages OpenAI’s next-generation model, optimized for multi-step research, reasoning, and synthesis. It has already set new performance benchmarks, achieving 26.6% accuracy on Humanity’s Last Exam (the highest of any OpenAI model) and a 72.57% average accuracy on the GAIA Benchmark, demonstrating advanced reasoning and research capabilities.

Currently available to Pro users (with up to 100 queries per month), it will soon expand to Plus and Team users. While OpenAI acknowledges limitations—such as occasional hallucinations and challenges in source verification—its iterative deployment strategy and continuous refinement approach are promising.

My key takeaway: This LLM agent-based tool has the potential to save hours of manual research while delivering high-quality, well-documented outputs. Automating tasks that traditionally require expert-level investigation, it can complete complex research in 5–30 minutes (just 6 minutes for my task), with citations and structured reasoning.

I don’t see any other comments yet from people who have actually used it, but it’s only been a few hours.I’d love to hear how it’s performing for others. What use cases have you explored? How did it do?

(Note: This review is based on a single use case. I’ll provide further updates as I conduct broader testing.)

[1] https://www.dazzagreenwood.com/p/ueta-and-llm-agents-a-deep-...