MurphyA/hacker-news huggingface dataset:
by bryant | 2025-08-06 13:06:27+00:00
This feels best summarized as:

• Product A has limited features but does them well. If the customer is okay with the features the product has, the reviewer can recommend it for this customer.

• Product B has more features but is impacted by QA issues as well as product design decisions that make those features harder to use. This impacts the ability of the customer to use features they might've paid for to use the product, and it may even impact their ability to use features core to other products. This potentially makes Product B less desirable for comparable use cases.

With this in mind, I'm inclined to agree with Wired's decision.
by sillyfluke | 2025-08-06 13:07:09+00:00
As Orwell has stated ages ago, there is a group of people who will only accept the truth when it confronts them on the battlefield. The unshakeable belief in previous priors leads many people to only face certain truths when forced to through lived experience.

There is la video circulating of a business owner making fun of the Amazon concept of showing thd amount tariffs add to the final price to the consumer. This guy in this video says that number is going to be 0 on his website because his product and the stuff used to make it is "Made in America". The next video is literally him bitching about how some of the Made in America stuff he needs to make his product increased by a grand in just one month. And he like, "why in the fuck are these Made in America affected? Something's messed up here."

At the end of the day, this is a business owner who was aware that the biggest online retailer in America said tariffs are going to affect the price of products the American consumer buys. If this guy can't be bothered to dig a little deeper to save his business, it's hard to expect other people that are a couple degrees removed from the action to do so as well.
by coffeefirst | 2025-08-06 13:07:27+00:00
"Ludite" "low-IQ" "meat LLM" "you will be left behind"

The behavior of the boosters is basically the opposite of how to make friends and influence people. I've been through plenty of hype cycles, and this is the first one where they seem to need to insult and threaten everyone.

I don't get it. And I don't feel any need to entertain it.
by thimabi | 2025-08-06 13:07:28+00:00
Oh, no, I do understand the value of long-form and deep human communication. I’m an avid book reader, for instance, and I actually prefer longer narratives.

What I don’t agree with is being needlessly verbose in circumstances in which the opposite is more valuable. Unfortunately, humans have a tendency to use flowery language even when that comes at the expense of message clarity.

Think, for example, of the countless self-help books that can be converted to short blog posts. Or think about legal or academic writing, which often stands in the way of readers actually understanding what is being said.

There’s so much writing like this out there that even LLMs were notorious for taking this over-elaborate language to a whole new level. And in my opinion that’s the kind of thing that we can (and should) avoid.
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Ask HN: Do you struggle with flow state when using AI assisted coding tools?
by rasca | 2025-08-06 13:08:01+00:00
It's been extremely difficult for me to achieve a flow state while using tools like `claude code` because I have to wait after every interaction. I get easily distracted, my mind wonders and I find myself reading HN and browsing the internet.

I'm more productive in most of the tasks I need to do but in some of these detours I loose long periods of times without even noticing. I've tried keeping the console open and reading through the AI agent process but that gets me nervous after a few interactions.

I also don't enjoy it as much. I don't get the feeling of accomplishment after finishing a new feature and everything feels fragmented.

Even using multiple sessions doesn't do the trick for me because I need to change task context every time. Does this happen to anyone else? Any recommendations?

How do you think we can achieve flow state while in this transition period while AI coding still needs constant hand holding and reviews?
by afavour | 2025-08-06 13:08:04+00:00
They specifically created a "spicy" mode, I'm quite sure they know what they're doing. I'm sure we'll get a shocked pikachu face statement soon saying they couldn't possibly have predicted this would happen and they'll make double triple sure it never happens again.

It is... interesting to see xAI's moves lately. Other AI companies seem very determined to show themselves with a publicly acceptable face, xAI seem to be tacking for the gap in the market around adult content. If you browsed Reddit's /r/grok a couple of months ago it looked a lot like /r/openai. Now it's full of people talking about the "Ani" AI companion and the various adult things you can get her to do.

I'm sure they'll make an absolute ton of money from the male loneliness epidemic. All the while Musk decries falling birth rates.
by ricardobayes | 2025-08-06 13:08:09+00:00
I would say, any company who doesn't have their own AI developed. You always hear companies "mandating" AI usage, but for the most part it's companies developing their own solutions/agents. No self-respecting company with a tight opsec would allow a random "always-online" LLM that could just rip your codebase either piece by piece or the whole thing at once if it's a IDE addon (or at least I hope that's the case). So yeah, I'd say locally deployed LLM's/Agents are a gamechanger.
by somenameforme | 2025-08-06 13:08:26+00:00
I agree with you on almost everything. Where we differ is on the nature of money. I think the recent wars emphasize that the real bottleneck in war is no longer $$$, but the things those dollars represent. So for instance a million $1000 drones is, on paper, only a billion dollars. The bottleneck isn't the cost, but the production. And you can't just spin up production making millions per year, because you also need the raw resources - and you end up with this entire complex supply chain, all on top of finite raw materials, and then the logistics to organize everything. And in the case of a war scenario, this all needs to be organized in a disruption proof system. It's extremely complex and difficult, even if you have an infinite money machine.

And I think you would actually agree with this by taking a simple thought experiment. Imagine we have 1 soldier with a million dollars of training. And we give an opposing force the choice of eliminating that soldier, or eliminating 1,000 $1000 drones. Everybody is going to pick the drones, and it won't be even remotely close. In fact drop it down by an order of magnitude, 100 drones, and it's still not even close - even though the on paper value of that soldier is an order of magnitude higher. 10 drones is probably where it starts to get close, though I think it'd still lean heavily towards the drones.

---

I would add that when a war becomes a late stage war of attrition, the value of infantry goes up. I am speaking in more general terms in a war where manpower is nowhere near a critical issue. In any case by the time manpower does become a critical issue, a war is usually already lost, even if it might be able to drag on for many months yet.
by jerf | 2025-08-06 13:08:58+00:00
That makes it so that in absolute terms, Python is not as slow as you might naively expect.

But we don't measure programming language performance in absolute terms. We measure them in relative terms, generally against C. And while your Python code is speculating about how this Python object will be unboxed, where its methods are, how to unbox its parameters, what methods will be called on those, etc., compiled code is speculating on actual code the programmer has written, running that in parallel, such that by the time the Python interpreter is done speculating successfully on how some method call will resolve with actual objects the compiled code language is now done with ~50 lines of code of similar grammatical complexity. (Which is a sloppy term, since this is a bit of a sloppy conversation, but consider a series "p.x = y"-level statements in Python versus C as the case I'm looking at here.)

There's no way around it. You can spend your amazingly capable speculative parallel CPU on churning through Python interpretation or you can spend it on doing real work, but you can't do both.

After all, the interpreter is just C code too. It's not like it gets access to special speculation opcodes that no other program does.
by fzeroracer | 2025-08-06 13:09:01+00:00
As a counterpoint to your argument: in many places I've lived the police would refuse to do their job even for things such as property theft that was caught on camera. Or enforce basic road laws for things like speeding or driving without plates. This was especially annoying in Austin where the police would continually blame a lack of budget despite having an insanely bloated budget.

I've become more and more cynical as I've gotten older and convinced that the police are largely conditioned to never do their job and just collect a paycheck for free, because then they can leverage their refusal into even more pay. It's corruption and kickbacks all the way through, and it's been a consistent trend in multiple cities.
by cnst | 2025-08-06 13:09:06+00:00
> Through a friend of a friend, I found out that Anthropic had an open position in the team implementing the secret, unreleased feature of Claude Desktop using enigo. I wrote a cover letter and sent out my application. An automatic reply informed me that they might take some time to respond and that they only notify applicants if they made it to the next round. After a few weeks without an answer, I had assumed they chose other applicants.

I've mostly stopped applying to the big companies long time ago (10+ years) precisely because I'd never hear back regardless of the match or the credentials.

The only exception has been JaneStreet — they've contacted me almost immediately after a cold application with a small cover letter about my interests.

Yet going the referral route, it's relatively easy to get an interview almost anywhere, even Google or Apple.
by mythz | 2025-08-06 13:09:18+00:00
ok issue is with ollama as gpt-oss 20B runs much faster on 1x 5070 Ti with llama.cpp and LM Studio:

llama-server = ~181 tok/s LM Studio = ~46 tok/s (default) LM Studio Custom = ~158 tok/s (changed to offload to GPU and switch to CUDA llama.cpp engine)

and llama-server on my 3x A4000 GPU Server is getting 90 tok/s vs 46 tok/s on ollama
by jjani | 2025-08-06 13:09:28+00:00
I've done years of private 1:1 teaching and some class teaching though not class lecturing, which is presumably the material you're talking about.

> As a former teacher, I know you need to have a good grasp of the material you are using in order to help students understand it. The material should also be in a similarly structured form thoughout a course, which will reinforce the expectations of the students, making their mental load lesser. The only way to do this is to prepare the material yourself.

It's absolutely necessary to have a good fundamental understanding of the material yourself. These teachers abusing AI and not even catching these obvious issues, clearly don't have such an understanding - or they're not using any of it, which is effectively the same. In fact, they're likely to have a much worse understanding than your average frontier LLM, especially given this post is about high school level teaching.

> The only way to do this is to prepare the material yourself.

As brought up in other comments, what is yourself? For decades teachers have been using premade lesson plans, either third-party, school supplied or otherwise obtained, with minor edits. All teachers? Of course not, but it's completely normalized. Are they doing it themselves? If not, then the remainder did it together with Google and Wikipedia. Were they also not doing it themselves? Especially given how awful modern Google is (and the worldwide number of high school teachers using something like Kagi will be <100 people), simply using a frontier model, especially with web search enabled, is simply a better version of doing that, if used in the same way.
by Twirrim | 2025-08-06 13:09:33+00:00
That would be a derivative work, and still be subject to the license terms and conditions, at best.

There are standard ways to approach this called clean room engineering.

https://en.m.wikipedia.org/wiki/Clean-room_design

One person reads the code and produces a detailed technical specification. Someone reviews it to ensure that there is nothing in there that could be classified as copyrighted material, then a third person (who has never seen the original code) implements the spec.

You could use an LLM at both stages, but you'd have to be able to prove that the LLM that does the implementation had no prior knowledge of the code in question... Which given how LLMs have been trained seems to me to be very dubious territory for now until that legal situation gets resolved.
by fidotron | 2025-08-06 13:09:35+00:00
Japan has a funny relationship with Apple. For example, the Felica ( https://en.wikipedia.org/wiki/FeliCa ) based ticket system is built into every iPhone globally, making life in Japan significantly easier for foreign iOS users. More surprisingly actually using the tickets does not require any app at all - you just use Apple Pay.

This is all narrowing the scope of what advantages native apps have (they do still have advantages), but it's hard to argue they simply aren't moving gatekeeping to other areas.
by EvanAnderson | 2025-08-06 13:09:45+00:00
> Why is it that it takes 1000 hours of study to cut people's hair...

Protectionism by a de facto trade guild was always my assumption.

There are a lot of activities where bad practitioners present significant danger to society and licensure makes sense. I never understood how cutting hair rises to that level. I'd love to know how licensure in the barber profession is anything other than a bald-faced attempt at building a moat. It seems like the market could correct for a bad practitioner in the barber space pretty easily, and with little risk to society.
by nu11ptr | 2025-08-06 13:09:46+00:00
The primary focus here is good and something I hadn't considered: python memory being so dynamic leads to poor cache locality. Makes sense. I will leave that to others to dig into.

That aside, I was expecting some level of a pedantic argument, and wasn't disappointed by this one:

"A compiler for C/C++/Rust could turn that kind of expression into three operations: load the value of x, multiply it by two, and then store the result. In Python, however, there is a long list of operations that have to be performed, starting with finding the type of p, calling its __getattribute__() method, through unboxing p.x and 2, to finally boxing the result, which requires memory allocation. None of that is dependent on whether Python is interpreted or not, those steps are required based on the language semantics."

The problem with this argument is the user isn't trying to do these things, they are trying to do multiplication, so the fact that the lang. has to do all things things in the end DOES mean it is slow. Why? Because if these things weren't done, the end result could still be achieved. They are pure overhead, for no value in this situation. Iow, if Python had a sufficiently intelligent compiler/JIT, these things could be optimized away (in this use case, but certainly not all). The argument is akin to: "Python isn't slow, it is just doing a lot of work". That might be true, but you can't leave it there. You have to ask if this work has value, and in this case, it does not.

By the same argument, someone could say that any interpreted language that is highly optimized is "fast" because the interpreter itself is optimized. But again, this is the wrong way to think about this. You always have to start by asking "What is the user trying to do? And (in comparison to what is considered a fast language) is it fast to compute?". If the answer is "no", then the language isn't fast, even if it meets the expected objectives. Playing games with things like this is why users get confused on "fast" vs "slow" languages. Slow isn't inherently "bad", but call a spade a spade. In this case, I would say the proper way to talk about this is to say: "It has a fast interpreter". The last word tells any developer with sufficient experience what they need to know (since they understand statically compiled/JIT and interpreted languages are in different speed classes and shouldn't be directly compared for execution speed).
by mmmllm | 2025-08-06 13:09:53+00:00
LLMs are not able to replace Excel in their current state. See this simple accounting test: https://accounting.penrose.com/ - errors compound over time. This is the case even with small datasets. For massive corporate datasets it's useless (try asking Gemini to summarise a Google Sheet).

Until there is a fix for this (not clear there ever will be), Excel will be necessary.

Word will probably become a different, more collaborative product. Notion-esque.

Powerpoint...I would love if it disappeared but ultimately if you have to present something, you need to have done the work.
by TheDong | 2025-08-06 13:09:56+00:00
I admit I was wrong in my understanding of iMessages capabilities.

I remembered its search sucking, and also it not working on all my devices, so I quit using it and regurgitated a stale criticism.

Still, the search is useless to me if I can't do it on my linux desktop (like I can with email, discord, and every other chat service I use), so I'd still say iMessage has a laughably lacking search by nature of it only working on ios/macos, when all other chat apps I use offer at least some search on ios/android/linux
by William_BB | 2025-08-06 13:10:05+00:00
Interesting stuff. I'm a bit confused on several points though.

If your strategies care so much about performance, can you really achieve the same or comparable performance with Cython? At that point, wouldn't those strategies be better suited for a custom "re-implementation"?

I suppose I'm not exactly sure how "high performance" and "low latency" this project is. Are there any latency stats on this project?
by JumpCrisscross | 2025-08-06 13:10:35+00:00
> Only slightly better than 1800s snake oil

In the same vein folks were disputing the validity of vitamin C until WWII [1].

There is no shortcut to science. You have to weigh the evidence. Currently, the evidence in favour of GLP-1 agonists is overwhelmingly positive.

[1] https://pubmed.ncbi.nlm.nih.gov/23183299/
by shiomiru | 2025-08-06 13:11:21+00:00
> I don't get it either, because that has always been the case, thus most of his post is borderline non sense.

Yes, making software development cheaper has been the main priority of the industry for a long time. The new development is that there's now a magic "do what I want" button that obviously won't quite do what you want but it's so cheap (for corporations, not humanity...) that you might as well pretend it does. (Compared to paying professionals who might even care about doing a good job, that is.)
by tomrod | 2025-08-06 13:11:43+00:00
> Expensive food is expensive, but I would bet quality food is cheaper here than anywhere else.

Having lived in a few other countries with less industrialized distribution networks, no, this claim is dramatically incorrect. Fruits, vegetables, staples like rice, and basic forms of protein (fish, insects and sea critters, some chicken) are much, much cheaper relative to processed foods. Larger protein sources like beef, pork, or bushmeat is relatively more expensive, however, unless you opt for poor quality processing like cheap "corned beef" made from offal.

As an economist, I appreciate the difficulty of making apples-to-apples comparisons across countries for things like food prices, as even the acclaimed "Big Mac Index" assumes that a Big Mac has a similar relative status across countries (though the oft-misunderstood intent of the Big Mac Index is to more to compare consistent production costs). In some places a Big Mac is fancy, in the US it is considered fairly garbage but consistent.

For example, in a market in the Philippines, you have mostly cash transactions and informal capture for what the majority of people purchase. The purchasing is done more in these almost farmers-market style transfer versus grocery stores in the US. They _do_ have grocery stories, but almost uniformly for processed food distribution versus fresh food in the markets. It's much cheaper to eat healthier from the markets and through the informal distribution network of sari-sari stores versus equivalent nutrition from processed food from the grocery stores.

Also, consider the results of this recent study: https://arstechnica.com/health/2025/08/in-trial-people-lost-...
by mlinhares | 2025-08-06 13:11:48+00:00
Nah, if there was ever a time where making meaningful contributions to open source was important to land you a good paying job in a hot tech company, that died a long time ago. The people making these decisions don't care, unless you have someone inside to put your resume first it doesn't matter that you wrote all the code that makes their product even possible, the hiring manager won't care.

I might just be old but i really haven't felt like contributing to open source at all lately because i've bills to pay and kids to care for and taking time out of this just for the sake of enriching some billion dollar corp that will eat me and spit me out doesn't feel like a good investment for my time.

Sometimes i feel sad that it came to this but this is the place we're living in right now.
by codingdave | 2025-08-06 13:11:50+00:00
I share those concerns. Reddit is already 90% crap, with 10% decent info. People who rave about reddit focus on that 10%, and ignore the 90%. But how is AI going to properly filter that?

I also worry about the echo chamber effect. If people learn from AI, and AI is updated based on reddit... which is full of people talking about what they learned from AI.... you can see the echo chamber being built before our eyes.