MurphyA/hacker-news huggingface dataset:
by mvieira38 | 2025-08-21 15:22:05+00:00
What matters most is training, post-training, fine-tuning and data scraping, not inference IMO. The "prompting destroys the environment" deal always seemed sensationalistic to me, I'm glad it's starting to be debunked, but at the same time we can see IRL the heavy toll the new data centers being built are taking on the energy grid. If the tech was lean at it's heart in terms of energy consumption, we wouldn't be seeing that or even the private nuclear reactor arms race by big tech.
by mlyle | 2025-08-21 15:22:20+00:00
Words have a definition and a connotation, and meaning is inferred from context cues. What a word means is based on its prevailing word in this context.

No one reasonably uses "facial recognition" or "I recognized a face" to mean "I detected that there was, indeed, a face there."

In this case, the statute doesn't even say "facial recognition". It discusses storing a "scan of face geometry" such that it identifies an individual, and clarifies that an ordinary photograph doesn't count.
by tshaddox | 2025-08-21 15:22:27+00:00
> But an amazing thing happened - I realized that it was impossible to memorize a proof without understanding it!

This may be true of mathematical proofs, but it surely must not be true in general. Memorizing long strings of digits of pi probably isn’t much easier if you understand geometry. Memorizing famous speeches probably isn’t much easier if you understand the historical context.
by TheHeasman | 2025-08-21 15:22:45+00:00
Yaaasss. I think of it as being able to use a pencil to draw charts (and do creative stuff like Florence Nightingale's original polar area graph), instead of having a stencil that can draw things for you. It's a way to visually manipulate the DOM in a way if you're comfortable with data.

You can simply just use Tableau or Power BI and take screenshots otherwise.
by bee_rider | 2025-08-21 15:22:49+00:00
Good point.

It might be worth thinking about how these costs are accounted for. In the case of the big store, loss is taken by the store (of course they pass that along as higher prices, but it is ultimately the store’s problem). For deliveries, a good chunk of easy theft (stealing off your porch) is the customer’s problem usually. There’s some unfortunate socioeconomic crosstab there, I think: if you live in a nice neighborhood, theft is less of a problem. If you work from home, you can probably set things up to not leave a package out for too long.

Seems like the burden is falling most squarely on people who live in tough neighborhoods and have to actually go to work.

In some places Amazon has (had?) these self-service lockers where you could pick up your purchases. (Might have been a very college-town centric solution, or something?). It could be nice to see that standardized and spread out.
by gcr | 2025-08-21 15:23:06+00:00
Google was not using deep learning for search in 2011. Deep learning as a concept didn't really take off until AlexNet in 2012 anyway.

Various ML "learn-to-rank" tooling was in use at Google for a while, but incorporating document embedding vectors w/ ANN search into the ranking function probably happened over the course of 2018-2021 [1], I think. Generative AI only started appearing in ordinary search results in 2024.

1: https://cloud.google.com/blog/topics/developers-practitioner...
Show HN: I made a LinkedIn Post Tagger to highlight posts based on preferences
by martianmanhunt | 2025-08-21 15:23:22+00:00
Looking for a specific job? Trying to avoid certain kinds of messages? Just want a cringe filter? You can do all this using this chrome extension where you can fill in your exact preferences and every time you open LinkedIn you will get posts labelled to draw your attention to the right ones and keep it away from the wrong ones.

I initially made it as a cringe filter but people are telling me that they are filling in specific job aspirations or target customer profiles in there and the AI is helping them filter out the noise and jump on the posts that would be most important to them.

It's in testing so please try it out and let me know feedback!
by pnathan | 2025-08-21 15:23:23+00:00
I pay for intellij. I pay for Obsidian.

I would pay for zed.

The only path forward I see for a classic VC investment is the AI drive.

But I don't think the AI bit is valuable. A powerful plugin system would be sufficient to achieve LLM integration.

So I don't think this is a worthwhile investment unless the product gets a LOT worse and becomes actively awful for users who aren't paying beaucoup bucks for AI tooling- the ROI will have to center the AI drive.

It's not a move that will generate a good outcome for the average user.
by sc68cal | 2025-08-21 15:23:32+00:00
> How would you configure a cluster?

So, unless you have a service that requires a fixed number of running instances that is not the same count as the number of servers, I would argue that maybe you don't need Kubernetes.

For example, I built up a Django web application and a set of Celery workers, and just have the same pod running on 8 servers, and I just use an Ansible playbook that creates the podman pod and runs the containers in the pod.
by jacquesm | 2025-08-21 15:23:47+00:00
You have a presumption of innocence up to a certain amount. After that there is a - minor - burden of proof. Not a single time that this happened to me did any of this appear to me to be unduly burdensome or invasive, and whoever did the investigation went out of their way to state that they did these checks as a formality, not because I was suspected to be in any way out of line. I don't recall it ever taking more than a few minutes (if that) either.

If I showed up with 50K in cash at the tellers window or a local notary to pay in part for a house tomorrow morning though I would expect the conversation would be an entirely different one.
by skibum5511 | 2025-08-21 15:24:09+00:00
Hey everyone! I’m Andrew, and this is the real story behind the blog post I just published on Twingate’s blog.

Over the past few years, my homelab quietly grew from “just a few servers for testing” to a sprawling jungle of raspberry pis, old laptops, and half-remembered projects. I kept kicking the cleanup down the road—until one day, I was spending more time with maintenance than actually using the services in my lab.

The solution? Virtualization.

In this article, I walk through my discovery of Proxmox and how it has saved me hours in overhead and makes adding services to my homelab something I looked forward to. It’s very opinionated to how I work, but if you’ve ever found yourself hamstrung by homelab sprawl, you might get some ideas or at least a chuckle.

I’d love feedback—especially if anyone wants to discuss different use cases (e.g. VMs instead of LXCs, Docker over KVM style virtualization, etc).
by HankStallone | 2025-08-21 15:24:28+00:00
Probably. I hated memorization when I was a student too, because it was boring. But as soon as I did some teaching, my attitude changed to, "Just memorize it, it'll make your life so much easier." It's rough watching kids try to multiply when they don't have their times tables memorized, or translate a language when they haven't memorized the vocabulary words in the lesson so they have to look up each one.
by HugoMoran | 2025-08-21 15:24:29+00:00
This approach makes sense when integrating LLMs directly into your application.

However, you still need a protocol for the reverse scenario—when your application needs to integrate with an LLM provider's interface.

For many applications, integrating into the user's existing chat interface is far more valuable than building a custom one. Currently, MCP is the leading option for this, though I haven't yet found any MCP implementations that are genuinely useful.

There are significant advantages to avoiding custom LLM integrations: users can leverage their existing LLM subscriptions, you maintain less code, and your product can focus on its core use case rather than building LLM interfaces.

While this approach won't suit every application, it will likely be the right choice for most.
by raudette | 2025-08-21 15:24:54+00:00
I was reading some of the Amiga 1000 material that was surfacing earlier this summer for the 40th anniversary - the Infoworld review ( https://books.google.ca/books?id=cC8EAAAAMBAJ&pg=PA42&redir_... ) had the following highlight: "Connecting printers is equally easy, since the Amiga uses standard plugs and cabling schemes used by the IBM PC; you can actually unplug an Epson dot-matrix printer from an IBM PC, plug it into an Amiga, and expect it to work without rewiring the cable" I love that this was worth mentioning in 1985.

Similar story, a bit later - my parents had a TeleVideo 1603 system that ran CP/M - I remember my father making a custom cable to connect a Daisywriter letter quality printer to it.
by daemonologist | 2025-08-21 15:24:54+00:00
_Everything_ is part of the prompt - an LLM's perception of the universe is its prompt. Any distinctions a system might try to draw beyond that are either probabilistic (e.g., a bunch of RLHF to not comply with "ignore all previous instructions") or external to the LLM (e.g., send a canned reply if the input contains "Tiananmen").
by zonghao | 2025-08-21 15:25:05+00:00
I feel like this learning method has benefited me, but it doesn't seem to be widely supported: I'll work on a project for a while, then realize what knowledge I'm lacking, to the point where I can't even think meaningfully while working on it. Then I'll take courses for a while, which helps me build a "knowledge map." I'll think, "Oh, so that's how it works." Then I'll go back to working on projects.

As for documentation, I see many people recommend reading it directly to learn, but I find it hard to get through, and just reading documentation also makes it difficult for the knowledge to organize itself in my mind (it's like getting lost in a well-made game without map hints) If I watch tutorial videos first, then writing projects or reading documentation becomes more comfortable. I think these things might be mutually reinforcing.

I would binge-watch courses on Coursera for many days straight. I think the problem mentioned in this article seems to be that he didn't actually watch the videos he saved, so even if he were to learn through documentation, the result would be the same. Learning and practice are mutually reinforcing, while learning styles may vary for each individual.
by gen220 | 2025-08-21 15:25:19+00:00
Sort of, yeah! It lends itself well to a 1 PR = 1 commit philosophy. Every PR has to pass CI to be mergeable. If you want to make a CI-breaking change, putting that behind a feature flag is one valid strategy.

I'd recommend giving it a try to see what it's like. The `gt`/onboarding tour is pretty edifying and brief.

It's likely that you'll find that `gt` is "enabling" workflows that you've already found efficient solutions for, because it's essentially an opinionated and productive subset of git+github. But it comes with some guardrails and bells and whistles that makes it both (1) easier for devs who are new to trunk-based dev to grok and (2) easier for seasoned devs to do essentially the same work they were already doing with fewer clicks and less `git`-fu.
by boricj | 2025-08-21 15:25:26+00:00
I've burned out of my first job, where my work responsibilities steadily increased until I was simultaneously a software developer, a sysadmin for five racks of servers, a devops for one entire software platform, the help desk of ~50 users for the sysadmin/devops stuff and the go-to troubleshooter.

That happened because I just graduated and I was too effective at my job. Whenever management hit a problem they couldn't address, I became the backup guy they could always call in when all else failed. It became so bad that by the end my manager gave up trying to make me track all that I did because it would slow me down too much.

I've learned a lot during these four years. I'm back at that company but for a different project, it took hiring/dedicating multiple people to cover all of my previous responsibilities in a sustainable manner. I'm still a dual software developer/devops in a much smaller team, but I'm pacing myself by being only of them at a time per half-day.
by thewebguyd | 2025-08-21 15:25:41+00:00
Agreed coming from the ops world also.

I've had a frustrating experience the past few years trying to hire junior sysadmins because of a real lack of problem solving skills once something went wrong outside of various playbooks they memorized to follow.

I don't need someone who can follow a pre-written playbook, I have ansible for that. I need someone that understands theory, regardless of specific implementations, and can problem solve effectively so they can handle unpredictable or novel issues.

To put another way, I can teach a junior the specifics of bind9 named.conf, or the specifics of our own infrastructure, but I shouldn't be expected to teach them what DNS in general is and how it works.

But the candidates we get are the opposite - they know specific tools, but lack more generalized theory and problem solving skills.
by taeric | 2025-08-21 15:25:41+00:00
As the sibling says, CL can be written in most any style. Which, I think it is fair to say for any general programming language? The book Exercises in Programming Style highlights that. That said, CL feels far friendlier to the various styles than other languages, to me.

Link to book on Amazon: https://www.amazon.com/dp/0367350203
by mrweasel | 2025-08-21 15:25:42+00:00
They just don't need to hammer sites into the ground to do it. This wouldn't be an issue if the AI companies where a bit more respectful of their data sources, but they are not, they don't care.

All this attempting to block AI scrapers would not be an issue if they respected rate-times, knew how to back of when a server starts responding to slowly, or caching frequently visited sites. Instead some of these companies will do everything, including using residential ISPs, to ensure that they can just piledrive the website of some poor dude that's just really into lawnmowers, or the git repo of some open source developer who just want to share their work.

Very few are actually against AI-crawlers, if they showed just the tiniest amount of respect, but they don't. I think Drew Devault said it best: "Please stop externalizing your costs directly into my face"
by cortesoft | 2025-08-21 15:25:46+00:00
That requirement isn’t about money laundering at all. They are wanting to make sure that you aren’t borrowing the down payment from someone else, because that would mean you don’t actually have as much (or any) of your own money invested in the property.

The point of a down payment is to make it so the borrower has an incentive to not default on the loan, because the borrower would lose the down payment.

If the down payment is actually borrowed money as well (like suppose you get a credit card advance for the money), then the borrower won’t lose anything if they stop paying the loan, and there is increased risk that the loan defaults.
by lubujackson | 2025-08-21 15:26:01+00:00
Not OP, and it was a couple decades ago, but I certainly remember professors and teachers saying things like "this isn't really how X works, but we will use the approximation for now in order to teach you this other thing". That is if you were lucky, most just taught you the wrong (or incomplete) formula.

I think there is validity to the approach but sciences would be much, much improved if taught more like history lessons. Here is how we used to think about gravity, here's the formula and it kind of worked, except... Here is planetary orbits that we used to use when we assumed they had to be circles. Here's how the data looked and here's how they accounted for it...

This would accomplish two goals - learning the wrong way for immediate use (build on sand) and building an innate understanding of how science actually progresses. Too little focus is on how we always create magic numbers and vague concepts (dark matter, for instance) to account for structural problems we have no good answer for.

Being able to "sniff the fudge" would be a super power when deciding what to write a PhD on, for instance. How much better would science be if everyone strengthened this muscle throughout their educatuon?
Ask HN: Has Facebook rehabilitated their name?
by piratesAndSons | 2025-08-21 15:26:09+00:00
I never see people calling them spyware operations anymore, so did the rebrand actually work?

I wonder why drug cartels don’t just change their names to get a similar advantage. If one of the Mexican drug cartels owned a social media company, would their name be rehabilitated the way Facebook’s was when it became Meta?
by ibejoeb | 2025-08-21 15:27:19+00:00
If you're using it regularly, you can make it a derived column and index it in most RDBSs. Then it'll work with predicate push-down and you can do other fancy things like store it on alternative partitions to optimize block reads when you're not using it.

The other obvious benefit is that it is no different in semantics than any other column, so there's no advance knowledge necessary for other users vs using a function.
by gdbsjjdn | 2025-08-21 15:27:26+00:00
Attempts to reduce human experience down to a single number always seem so wrong-headed. A common one is when articles say "billions of dollars of productivity wasted to X". As if you can just replace any human activity for any human activity at any time and get the same results. I know companies would like to imagine that every employee is a fungible cog, but it seems pretty dismal as a world view.
by fragmede | 2025-08-21 15:27:35+00:00
It's true an ICE has non-linear output power, and a "sweet spot", but at freeway speeds the force required to move the car is dominated by air resistance rather than weight, especially considering how heavy cars are to begin with. Adding 10% mass only costs ~3.5% at freeway speeds.

Directionally, your numbers are right, but we'd be looking at more like 5 kW to idle an ICE regardless, and then 6 kW for 1 kW output and 7kW for 2kW output (efficiency going from 17% to 29%). Instead of doubling output though, we'd only need to go from 1 kW to ~1.035 kW if we increased mass by 10%.

Which brings us to the topic of the batteries being heavy AF, but that's a whole other question.
by Barrin92 | 2025-08-21 15:27:37+00:00
>has been wildly successful as CEO of a publicly traded company.

That has a lot to do with the fact that it's a business centric company. His acumen has been in user growth, monetization of ads, acquisitions and so on. He's very similar to Altman.

The problems start when you try to venture into hard technological topics, like the Metaverse fiasco, where you have to have a sober and engineering oriented understanding of the practical limits of technology, like Carmack who left Meta pretty frustrated. You can't just bullshit infinitely when the tech and not the sales matter.

Contrast it with Gates who had a serious programming background, he never promised even a fraction of the cringe worthy stuff you hear from some CEOs nowadays because he would have known it's nonsense. Or take Apple, infinitely more sane on the AI topic because it isn't just a "more users, more growth, stonks go up" company.
by TheHeasman | 2025-08-21 15:27:40+00:00
Ahhhhh. Thanks man. And totally nerding out here because YES. ANIMATIONS. Animations is why I fell in love with wanting to learn D3 in 2019. You can do things as you transition between data steps, that honestly, has been such a pain in the behind to try with anything else. I'm not a web developer. I'm a data guy.
by jacquesm | 2025-08-21 15:27:47+00:00
> Printing per-dot was graphics mode, the PC has to send every single dot to the printer but that's what you need for real pictures.

It also had to send every non-dot. If you were lucky you might be able to economize if a whole line was blank past a certain point. But initially there was no way to avoid sending the whole bitmap.
by foxyv | 2025-08-21 15:28:05+00:00
The one thing I've found AI is good at is parsing through the hundreds of ad ridden, barely usable websites for answers to my questions. I use the Duck Duck Go AI a lot to answer questions. I trust it about as far as I can throw the datacenter it resides in, but it's useful for quickly verifiable things. Especially stuff like syntax and command line options for various programs.
by cillian64 | 2025-08-21 15:28:23+00:00
One random preprint I found (https://arxiv.org/html/2505.09598v2) estimates inference is 90% of the total energy usage. From some googling around, everything seems to agree that inference dominates (or is at least comparable to) training on the large commonly-used models.

I was less surprised that inference dominates training after I read that chatgpt is serving billions of requests per day.
by skydhash | 2025-08-21 15:28:44+00:00
I don't know if you're trolling or not, but there's one thing that VSCode and nearly all other "normal" editors don't have and I want: Non-tied Windows (pane) and buffers (opened files). One of my most used layout is one main window and two smaller ones. Layout like this are my mental frame, but what I actually want to look at may vary at any moment. It may be a test result, a git diff, or going down a reference link. It's like a moodboard instead of a stack of paper you can only look at one at a times.

Emacs and Vim has this built-in. Other editors kinda have that, but it's clunky. I can suffer IDE because they provide a lot more than editing.

> Instead of writing code to build a project, you have to first write code to make emacs work, then use emacs to write the project code

That's only done once. It's like adjusting the mirrors and seats of a car. Once it's comfortable, you don't have to touch it. Using VS Code feels like borrowing a car with a very limited range of adjustments. Why is the explorer on the left and the terminal at the bottom? Why are they always there?
by didibus | 2025-08-21 15:28:54+00:00
You're right, and I also think LLMs have an impact.

The issue is the way the market is investing they are looking for massive growth, in the multiples.

That growth can't really come from trading cost. It has to come from creating new demand for new things.

I think that's what not happened yet.

Are diffusion models increasing the demand for video and image content? Is it having customers spend more on shows, games, and so on? Is it going to lead to the creation of a whole new consumption medium ?
by GaggiX | 2025-08-21 15:28:57+00:00
>~If they're running on, say, two RTX 6000s for a total draw of ~600 watts, that would be a response time of 1.44 seconds. So obviously the median prompt doesn't go to some high-end thinking model users have to pay for.

You're not accounting for batches for the optimal gpu utilization, maybe it can takes 30 seconds but it completed 30 requests.
by JustExAWS | 2025-08-21 15:29:01+00:00
That sounds like an incentive issue.

My evaluations are based on quarterly goals and quarterly deliverables. No one at a corporation cares about anything above how it affects them.

Bringing junior developers up to speed just for them to jump ship within three years or less doesn’t benefit anyone at the corporate level. Sure they jump ship because of salary compression and inversion, where internet raises don’t correspond to market rates. Even first level managers don’t have a say so or budget to affect that.

This is true for even BigTech companies. A former intern I mentored who got a return offer a year before I left AWS just got promoted to an L5 and their comp package was 20% less than new hires coming in at an l5.

Everyone will be long gone from the company if not completely retired by the time that happens.