MurphyA/hacker-news huggingface dataset:
by SpicyLemonZest | 2025-07-03 14:45:16+00:00
I don't care if it's "productive" in some narrow sense. If I discover that someone works for or with ICE during the current administration, I am precommitting to lose my mind over it. I'll block them, undermine them, blacklist them, do whatever I can to punish them for their heinous actions. I understand and accept that this diminishes the incentives for ICE to behave incrementally better, because I don't think that behaving incrementally better is adequate. ICE has a lot of hiring coming up with their new budget, and I want every applicant to understand that taking the job will ruin their life.
by bumby | 2025-07-03 14:46:28+00:00
I might disagree on this. For a meeting that covers any moderately complex situation to be productive, the attendees need to understand the context. That sounds like what Bezos was after. Doing “homework” beforehand ensures that people aren’t sitting idly while one person is reading the report for the first time or otherwise trying to bring themselves up to speed on the context everyone else already knows. I don’t think that’s the best use of everyone’s time, unless you expect meetings to be the primary objective of those attendees. It sounds to me that leadership should be delegating decisions to people who understand the context rather than spending time at every meeting going over background. Of course, that only works well in high-trust environments.
by squigz | 2025-07-03 14:46:28+00:00
The amount of thought that can be put into writing as a function of total time thinking/communicating is probably nearly the same or less than talking. That is, if you spend a second figuring out what you're going to say, you can put more thought into your words.

> Writing also has the benefit of maintaining a record of what was said. The number of misunderstandings that could have been a avoided by writing is staggering.

Not everything needs to be recorded - and when it does, one can record the conversation, or take notes.

Not to mention, misunderstandings crop up in text all the time, often due to lack of tone being conveyed
by tmilard | 2025-07-03 14:47:16+00:00
I do agree with you. We have an natural eye (what you call a 'biological brain') automat that inconsciouly 'feels' the structure of a geometric of the places we enter to.

Once this layer of "natural eye automat" is programmed behind a camera, it will spit out this crude geometry : the Spacial-data-bulk (SDB). This SDB is small data.

From now on, our programs will only do reason, not on data froms camera(s) but only on this small SBD.

This is how I see it.
by SantalBlush | 2025-07-03 14:47:54+00:00
I feel like my understanding of politics dramatically improved once I considered that some voters are malevolent. Some voters consciously support inhumane policies, but due to social pressure, they feel that they can't be truthful about it.

So they will claim to be in favor of more socially acceptable policies, but vote against those policies giving some nonsensical reason, and it gives the appearance of stupidity.
by tashoecraft | 2025-07-03 14:49:07+00:00
I find it interesting you are blaming the NYT on this and not ChatGPT for keeping these logs in the first place. If openAI didn't keep logs, then there would be nothing to search, and a more harmful actor couldn't accomplish something far more nefarious. Saying that there could be confidential information in the logs, so that means we shouldn't access it, should also mean the logs shouldn't be kept.
by jumploops | 2025-07-03 14:49:43+00:00
We’re playing an endless cat and mouse game of capabilities between old and new right now.

Claude Code shows that the models can excel at using “old” programmatic interfaces (CLIs) to do Real Work™.

MCP is a way to dynamically provide “new” programmatic interfaces to the models.

At some point this will start to converge, or at least appear to do so, as the majority of tools a model needs will be in its pre-training set.

Then we’ll argue about MPPP (model pre-training protocol pipeline), and how to reduce knowledge pollution of all the LLM-generated tools we’re passing to the model.

Eventually we’ll publish the Merrium-Webster Model Tool Dictionary (MWMTD), surfacing all of the approved tools hidden in the pre-training set.

Then the kids will come up with Model Context Slang (MCS), in an attempt to use the models to dynamically choose unapproved tools, for much fun and enjoyment.

Ad infinitum.
by Swizec | 2025-07-03 14:49:51+00:00
I know the HTMX guy has opinions on this, but I also like how React (and similar frameworks) give you locality of behavior.

<button onClick={() => fetch(‘/clicked’)}>

To me that feels like less magic to remember than

<button hx-get=“/clicked”>

But ultimately let’s be honest: Experienced engineers can write good code in anything and inexperienced engineers can write bad code in anything. Simplicity takes time.
by schveiguy | 2025-07-03 14:50:27+00:00
> Why "a"

`a` is a parameter in the lambda function `a => a.idup`.

> Why "map!"

This is definitely something that can trip up new users or casual users. D does not use <> for template/generic instantiation, we use !. So `map!(a => a.idup)` means, instantiate the map template with this lambda.

What map is doing is transforming each element of a range into something else using a transformation function (this should be familiar I think?)

FWIW, I've been using D for nearly 20 years, and the template instantiation syntax is one of those things that is so much better, but you have to experience it to understand.

> "idup" seems arbitrary

Yes, but a lot of things are arbitrary in any language.

This name is a product of legacy. The original D incarnation (called D1) did not have immutable data as a language feature. To duplicate an array, you used the property `dup`, which I think is pretty well understood.

So when D2 came along, and you might want to duplicate an array into an immutable array, we got `idup`.

Yes, you have to read some documentation, not everything can be immediately obvious. There are a lot of obvious parts of D, and I think the learning curve is low.
by throwway120385 | 2025-07-03 14:51:16+00:00
Go find water and then try to follow where it flows. Look at the scenery and try to determine whether you're in a valley or on a plateau or in the mountains.

Compasses are pretty useless without a map or a terrestrial view of some sort, as all you can do with them is shoot a bearing relative to magnetic north, or if your compass includes a declination adjustment a bearing to true north, provided you know the declination beforehand. It's often printed on topographical maps for this reason.

If you're on top of something then you can use the compass to get somewhere you can do dead reckoning. Usually there's little landmarks every 10 or 20 feet that you can stay on a bearing to. But if you can't see any topography from where you're at you'll have to infer it somehow. So another strategy might be to head uphill if you can ascertain there will be some kind of view there.

A lot of what you'd do depends on the terrain you find yourself in.
by zhobbs | 2025-07-03 14:51:34+00:00
I think another generalization people make here is around complexity. Many developers work on apps that just aren't that complex. Glorified CMS's mostly doing CRUD with well established code patterns.

Sure, LLMs might create slop on novel problems, but a non-tech company that needs to "create a new CRUD route" and an accompanying form, LLMs are smart enough.
by taylodl | 2025-07-03 14:51:38+00:00
I'm thinking you're looking at this all wrong: it doesn't matter how many employees you have, what matters is the impact you have.

ARM? Their devices are running everywhere.

Spotify? They have 1/3 of the world's streaming music business.

The fact they're able to do so much with so few employees tells me they're more efficient.

Oh, and let's not forget that Linux came from Europe.
by JyB | 2025-07-03 14:51:58+00:00
> It demands too much context.

This is solved trivially by having default initial prompts. All majors tools like Claude Code or Gemini CLI have ways to set them up.

> You pass all your tools to an LLM and ask it to filter it down based on the task at hand. So far, there hasn't been much better approaches proposed.

Why is a "better" approach needed? If modern LLMs can properly figure it out? It's not like LLMs don't keep getting better with larger and larger context length. I never had a problem with an LLM struggling to use the appropriate MCP function on it's own.

> But you run into three problems: cost, speed, and general reliability

- cost: They keep getting cheaper and cheaper. It's ridiculously inexpensive for what those tools provide.

- speed: That seem extremely short sighted. No one is sitting idle looking at Claude Code in their terminal. And you can have more than one working on unrelated topics. That defeats the purpose. No matter how long it takes the time spent is purely bonus. You don't have to spend time in the loop when asking well defined tasks.

- reliability: Seem very prompt correlated ATM. I guess some people don't know what to ask which is the main issue.

Having LLMS being able to complete tedious tasks involving so many external tools at once is simply amazing thanks to MCP. Anecdotal but just today it did a task flawlessly involving: Notion pages, Linear Ticket, git, GitHub PR, GitHub CI logs. Being in the loop was just submitting one review on the PR. All the while I was busy doing something else. And for what, ~1$?
by benreesman | 2025-07-03 14:51:58+00:00
What we call an LLM today (by which almost everyone means an autogressive language model from the Generative Pretrained Transformer family tree, and BERTs are still doing important eork, believe that) is actually an offshoot of neural machine translation.

This isn't (intentionally at least) mere HN pedantry: they really do act like translation tools in a bunch of observable ways.

And while they have recently crossed the threshold into "yeah, I'm always going to have a gptel buffer open now" territory at the extreme high end, their utility outside of the really specific, totally non-generalizing code lookup gizmo usecase remains a claim unsupported by robust profits.

There is a hole in the ground where something between 100 billion and a trillion dollars in the ground that so far has about 20B in revenue (not profit) going into it annually.

AI is going to be big (it was big ten years ago).

LLMs? Look more and more like the Metaverse every day as concerns the economics.
by ben_w | 2025-07-03 14:52:05+00:00
> I'm reminded of https://qntm.org/mmacevedo

Mmm.

My inspiration was from Alastair Reynolds putting indoctrinal viruses into the Revelation Space series, listening to an audio book of that several years before mmacevedo was published. At the time, I was thinking of how AI might enforce group-think, rather than write the content itself directly: https://benwheatley.github.io/blog/2019/12/30-18.46.50.html

> Generally they can plagiarize in the style of any human artist you can name whose work is on the internet. Artists are, not unreasonably, upset about this.

Indeed, but so can LLMs of text styles. I meant more of the "voice" seems to be different between them — there seems to be more of a difference between getting SDXL and SD 3.5 (or DALL•E 2 and whatever it's called now it's baked into ChatGPT) to mimic, say, Hieronymus Bosch, than there is between getting GPT-4o and Claude Sonnet 4 to do a poem in the style of a Shakespeare soliloquy.

On the other hand, this may just be my limited appreciation for the arts, as per XKCD: https://xkcd.com/1015/
by phil21 | 2025-07-03 14:52:06+00:00
All bezos did was explicitly make the homework a required part of calling a meeting. Correctly putting the majority of the prep work on the person calling the meeting to begin with.

Then they simply moved the implied 20-30 minute prep time everyone should be doing anyways into the meeting block itself.

If a meeting isn’t important enough to prep materials or an agenda for the meeting should be canceled.

My theory is all standing scheduled regular meetings are basically useless. If I run a startup again they will be outright banned for my org. Meetings about a specific topic or issue are different.
by azath92 | 2025-07-03 14:52:17+00:00
yeah we see that a bit as well, i promise its not hardcoded in haha.

On the LLM side of things we are using Gemini 2.5 flash, mostly for speed, and found it to be reasonably good quality at a vibe level compared to something heavier like claude 4, probably because we've worked hard to keep the task very simple and explicit. But in saying that there are a bunch of comments on quality that really highlight that if we want to get serious about that we should put in some user feedback loops and evals.

Its all in JS/TS, using vercel ai for the LLM calls, storage is local, but in order to really dig into quality we might start saving things, but to do that well we'd have to add auth/users etc. and we wanted to keep it light for a demo. We have been recently exploring langfuse for tracing, and are really liking that, and will probably look at using them for first pass evals when we get to it for this project.

We also talked quite a bit about non-LLM recsys and aside from time to set up and do well, something I really like is the sense of transparency and agency. you can see your profile, and edit it if you like to see the change in your results. I almost think wed lean further into that rather than folding in some trad DS or recsys stuff even if that might make the results better. Just musings at this point though.
by aapeli | 2025-07-03 14:52:40+00:00
Part of it is the better UI and new tech, but there's a lot more too.

Just on that point though: there's actually another open-source platform called Trustroots. They initally started as a rewrite of the BeWelcome frontend, but because of politics and such, BW never let them merge those big changes, so they spun off. Trustroots is a cool project but I think they swung too far into the realm of anarchism in their vibe both as a platform (they are very hitchhikey, so their moderation model is extremely hands off) and as a project (they have this things called a "do-ocracy"). We think there needs to be some planning and roadmapping and a healthy mix of dev + non-dev, as well as serious moderation to keep the platform safe.
by antirez | 2025-07-03 14:53:04+00:00
I have the feeling that's not really MCP specifically VS other ways, but it is pretty simply: at the current state of AI, to have a human in the loop is much better. LLMs are great at certain tasks but they often get trapped into local minima, if you do the back and forth via the web interface of LLMs, ask it to write a program, look at it, provide hints to improve it, test it, ..., you get much better results and you don't cut yourself out to find a 10k lines of code mess that could be 400 lines of clear code. That's the current state of affairs, but of course many will try very hard to replace programmers that is currently not possible. What it is possible is to accelerate the work of a programmer several times (but they must be good both at programming and LLM usage), or take a smart person that has a relatively low skill in some technology, and thanks to LLM make this person productive in this field without the long training otherwise needed. And many other things. But "agentic coding" right now does not work well. This will change, but right now the real gain is to use the LLM as a colleague.

It is not MCP: it is autonomous agents that don't get feedbacks from smart humans.
by x187463 | 2025-07-03 14:53:33+00:00
In that case, the reviewer seems to have completely misunderstood the subject of the review. That's a fine review (I guess) if the subject of the review is Amazon and the purchasing/delivery experience. Of course, it would be obvious from reading the review that it's not useful to somebody looking for book reviews and it should be (re)moved, but for whatever reason we have accepted platforms such as Amazon will simply fail to handle it properly.
by runjake | 2025-07-03 14:54:28+00:00
In 1992, I went from Amiga to a PC solely because of Wolfenstein 3D. I already felt like I was clinging to the Amiga platform. Most of my other friends in the Amiga world had moved on to other platforms. Doom came out about a year later, near Christmas 1993, IIRC.

The author bought their Amiga 500 in early 1992! It was already a "classic" by then.
by southernplaces7 | 2025-07-03 14:54:31+00:00
Sorry for the huge response to your passing comment but:

Not really. Statistically, the things that most often kill people lost in the wilderness are exposure and following that, accidents that outright kill or weaken the body's ability to deal with the weather and thus accelerate exposure effects. You do not need freezing temperatures to die of exposure. Even being exposed to mild cold, but continuously, and particularly if wet or partly submerged in water, will eventually bring your body down to hypothermic temperatures.

Hunger is barely a factor because you can go without food for an exceptionally long time before you weaken severely, let alone die, and though we need water to live quite soon, it's rarely impossible to find unless you're in a very arid place. In either case, if the weather is bad and you're under-dressed, that's what will kill you well before you need to worry about dropping from hunger or even thirst.

As for wild animals, they're your single lowest worry, despite being the things that tend to most scare people about the wilderness (thank our ancient hunter/gatherer instincts for this, since they led to us not immediately fearing things we'd adapted ourselves to handling well, like weather and sources of nutrition, but continuing to fear the things we couldn't easily control, like lurking beasts).

Generally, you'd have to be incredibly unlucky to be the victim of something like a bear or puma attack and forget completely about attacks from any other animal, since they're nearly unheard of.

Just to be clear, with most of the above i'm referring to North America or at least to some sort of northern or southern temperate region that may include deserts, forests, prairies, etc, and not tropical conditions or wildlife.

In tropical conditions, and especially jungles, the calculus changes quite a bit, with exposure being less of a risk (though one can be surprised by unexpected cold, as has happened to me in outright jungles deep inside central America where you wouldn't fucking expect to feel really cold, but holy shit!.) Certain kinds of wildlife also become much more of a danger in tropical places, though with few exceptions, the really problematic ones won't be the big predators. Instead you can genuinely worry about smaller things that sting or bite with venom.

Edited for way too many spelling mistakes.
by dist-epoch | 2025-07-03 14:54:40+00:00
I've been using a VM for a sandbox, just to make sure it won't delete my files if it goes insane.

With some host data directories mounted read only inside the VM.

This creates some friction though. Feels like a tool which runs the AI agent in a VM, but then copies it's output to the host machine after some checks would help, so that it would feel that you are running it natively on the host.
by RHSeeger | 2025-07-03 14:54:41+00:00
> To that end, I think it is fully appropriate for the society to collapse if individuals within it determine to forgo children. We shouldn't redistribute from some to others purely to ensure society's continuum. Instead, individuals should maximize their utility, and in doing so create society.

We have an entire system of laws we put in place to force people to increase their utility within society.

What your statement is effectively arguing is... to go with anarchy; that we should not have rules that change human behavior, because human behavior _should_ be to maximize utility.

I think it's pretty well accepted that "just let everyone do whatever they want" isn't a viable system for a society.
by tmilard | 2025-07-03 14:54:44+00:00
You said : "- detecting lines from pixels - detecting geometry in pointclouds - constructing 3D from stereo images, photogrammetry, 360 panoramas"

==> For me it is more something like : Source = crude video-or-photo pixels (to) ===> Find simple many rectangle-surface that are glued together one another.

This is, for me, how you really go easily to detecting rather complexes geometry of any room.
by mikeyg | 2025-07-03 14:55:09+00:00
anyone else feel like the linux kernel release quality has come down a bit here in the 2020s? i feel like it hasn't been this bad since the mid 90s. anecdotally in the past couple years, i've experienced a data corruption bug in xfs, wonky wifi firmware/kernel regressions, graphics artifacts and hard crashes in amdgpu. my experience with mainline releases before 2020 has been that they're rock solid. i'd doubt myself before i doubted the kernel. i say all this with a deep appreciation for everyone and the work they're doing... my intuition says that the complexity of it all is reaching a tipping point that is finally overwhelming the ages old release engineering processes.
by destructionator | 2025-07-03 14:55:37+00:00
> D2 re-write

No such thing happened. D has always been built on the same codebase, and the labels "D1" and "D2" are just arbitrary points on a mostly linear evolution (in fact, the tags D 1.0 and D 2.0 came only 6 months apart; 1.0 was just meant to be a long term support branch, not a different language. It was the addition of `const` that broke most code around release 2.6 but if you update those, old and new compilers generally work.

I'd say where D failed was its insistence on chasing every half-baked trend that someone comments on Hacker News. Seriously, look at this very thread, Walter is replying to thing after thing saying "D has this too!!" nevermind if it actually is valuable irl or not.
by brendan_bormann | 2025-07-03 14:55:39+00:00
I'm Brendan - A senior engineer with a focus on back-end and systems, particularly in Rust and/or TypeScript

Location: Denver, Colorado USA

Remote: Yes, open to hybrid

Willing to relocate: Not at this time

Technologies & Expertise: Back-end, Systems, Networking, Full-Stack web apps, Desktop apps, Distributed systems

Languages/Frameworks: TypeScript, Rust, Go, Node, React

Website: https://brendan.bormann.dev/

LinkedIn: https://www.linkedin.com/in/brendanbormann/

GitHub: https://github.com/Brendan-Bormann

Email: hnhiring [at] bormann [dot] dev
by shelajev | 2025-07-03 14:55:45+00:00
it's the latter: "you can actually start telling it to write a Playwright Python script instead and run that".

and while running the code might faster, it's unclear whether that approach scales well. Sending an MCP tool command to click the button that says "X", is something a small local LLM can do. Writing complex code after parsing significant amount of HTML (for correct selectors for example) probably needs a managed model.
by AnimalMuppet | 2025-07-03 14:55:47+00:00
I lost count of the logical fallacies in this post.

> Universities were initally founded as "repressive" regimes as the first universities started as theological schools.

Genetic fallacy.

> Using your logic I guess we don't have any great universities in the US or any great universities in europe. All universities exist in societies and every society has "repression" of some kind of another.

Non sequitur. More repressive regimes will create more things that you cannot say. It's not black and white; there is a continuum between "more free" and "more repressive", and where you are on it really matters.

The rest of the post is just more flawed logic that I don't have the energy to trace through.