MurphyA/hacker-news huggingface dataset:
by bawolff | 2025-06-02 21:42:22+00:00
Sometimes i feel like people who really like AI have a very different experience programming then i do.

They are constantly talking about AI doing all the tedious boilerplate bullshit. Don't get me wrong, some of my code is that too and its not fun. However the pro-AI people talk as if 80% of your day is dealing with that. For me its simply a rare enough occurence that the value proposition isn't that big. If that is the killer app of AI, it just doesn't sound that exciting to me.
by amysox | 2025-06-02 21:42:49+00:00
Location: Denver, CO, USA Remote: Yes Willing to relocate: No, but open to travel Technologies: Python, Java, C/C++, SQL/MySQL/Oracle, Linux, network development, integrations, Developer Relations, online community Résumé/CV: https://erbosoft.com/~amy/resume.pdf Email: amy [at] erbosoft [dot] com

I can do anything I set my mind to, and have done enough things over the course of a career to justify that statement. I want to do great things for an innovative company, and want to work with teammates interested in the same thing. If you've got something interesting, I'd like to hear about it.

Seeking a senior SWE position; I have some lead experience as a developer, but am also on the board of directors of a nonprofit, which indicates additional leadership experience.
by isranimohit | 2025-06-02 21:42:53+00:00
I’ve been trying to understand how LLMs like GPT-4 work on a deep level. Instead of a typical explainer, I wrote a short fantasy story where each part maps to a real component of the model — from tokenization to attention to training.

It’s called The Oracle of Lexiconia, and it hides the technical mapping until the end. An attempt to make the abstract intuitive.
by mrmansano | 2025-06-02 21:43:08+00:00
> I'm just starting to use Codex Web for asynchronous agents because I have a friend who swears by queueing up a dozen async prompts every morning and sifting through them in the afternoon

Bunch of async prompts for the same task? Or are you parallelizing solving different issues and just reviewing in the afternoon?

Sounds intriguing either way.
by nawgz | 2025-06-02 21:43:19+00:00
I do not see the value in making your own ad hoc style, nor does being a decent typist support any such claim. The whole point of home row is that your fingers can ergonomically access every key on the keyboard without requiring you to move your entire hand, and that seems basically like a requirement to me to be able to actually type properly without looking at your keyboard. F and J are the only keys with bumps for a reason.

I am skilled as a typist - just pulled off an easy 150wpm with 100% accuracy on this keybr site - and I learned typing and piano starting at a young age. Seems like a bit of hubris to disregard tradition just because you can beat up on internet randoms on keybr.com
by reaperducer | 2025-06-02 21:43:25+00:00
I have to say, my ability to learn Rust was massively accelerated via LLMs.

How would you know?

If you didn't know Rust already, how would you know the LLM was teaching you the right things and the best way to do things?

Just because it compiles doesn't mean it works. The world is full of bad, buggy, insecure, poor code that compiles.
by netsharc | 2025-06-02 21:44:10+00:00
I imagine a travel agent would have local knowledge and connections, and would know the quality of the hotels they're trying to send to you, a high commission isn't worth it if your customer is unsatisfied and goes to a different agent for their next trip. Of course this is based on the assumption that the customer always wants to use a travel agent (an unrealistic assumption nowadays, because it's so easy to switch to the Internet).

Someone like Rick Steves(1) still goes to the destinations every summer to check out hotels, restaurants and local companies, I imagine someone with more budget would travel with his company rather than try their luck with some booking.com hotel with a high rating...

1: https://www.youtube.com/@RickStevesEuropeOfficial
by JadeNB | 2025-06-02 21:44:16+00:00
> I agree. It sounds like lack of documented processes and leadership oversight have made that corner of the organization a kind of personal fiefdom of the administrative staff.

There are lots of problems with the way universities are set up, but, from the point of view of a faculty member and, I suspect, also that of a student, "more leadership oversight" would solve none of them. (Unless it was accompanied by a change of university leadership from those who think of a university primarily as a business, to those who think of a university primarily as a university. I have only spent a long time at one university, so it is possible that this problem is peculiar to my university, but my impression from talking to my colleagues is that it is not.)
by BeetleB | 2025-06-02 21:44:39+00:00
It's not the speech recognition model alone that's fantastic. It's coupling it to an LLM for cleanup that makes all the difference.

See https://blog.nawaz.org/posts/2023/Dec/cleaning-up-speech-rec...

(This is not the best example as I gave it free rein to modify the text - I should post a followup that has an example closer to a typical use of speech recognition).

Without that extra cleanup, Whisper is simply not good enough.
by Barrin92 | 2025-06-02 21:44:51+00:00
>simple fact that you can now be fuzzy with the input you give a computer, and get something meaningful in return

I got into this profession precisely because I wanted to give precise instructions to a machine and get exactly what I want. Worth reading Dijkstra, who anticipated this, and the foolishness of it, half a century ago

"Instead of regarding the obligation to use formal symbols as a burden, we should regard the convenience of using them as a privilege: thanks to them, school children can learn to do what in earlier days only genius could achieve. (This was evidently not understood by the author that wrote —in 1977— in the preface of a technical report that "even the standard symbols used for logical connectives have been avoided for the sake of clarity". The occurrence of that sentence suggests that the author's misunderstanding is not confined to him alone.) When all is said and told, the "naturalness" with which we use our native tongues boils down to the ease with which we can use them for making statements the nonsense of which is not obvious.[...]

It may be illuminating to try to imagine what would have happened if, right from the start our native tongue would have been the only vehicle for the input into and the output from our information processing equipment. My considered guess is that history would, in a sense, have repeated itself, and that computer science would consist mainly of the indeed black art how to bootstrap from there to a sufficiently well-defined formal system. We would need all the intellect in the world to get the interface narrow enough to be usable"

Welcome to prompt engineering and vibe coding in 2025, where you have to argue with your computer to produce a formal language, that we invented in the first place so as to not have to argue in imprecise language

https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667...
by csmpltn | 2025-06-02 21:45:01+00:00
There are tens (if not hundreds) of thousands of OAuth libraries out there. Probably millions of relevant codebases on GitHub, Bitbucket, etc. Possibly millions of questions on StackOverflow, Reddit, Quora. Vast amounts of documentation across many products and websites. RFCs. All kinds of forums. Wikipedias…

Why are you so surprised an LLM could regurgitate one back? I wouldn’t celebrate this example as a noteworthy achievement…
by malfist | 2025-06-02 21:45:03+00:00
Today I had a dentist appointment and the dentist suggested I switch toothpaste lines to see if something else works for my sensitivity better.

I am predisposed to canker sores and if I use a toothpaste with SLS in it I'll get them. But a lot of the SLS free toothpastes are new age hippy stuff and is also fluoride free.

I went to chatgpt and asked it to suggest a toothpaste that was both SLS free and had fluoride. Pretty simple ask right?

It came back with two suggestions. It's top suggestion had SLS, it's backup suggestion lacked fluoride.

Yes, it is mind blowing the world we live in. Executives want to turn our code bases over to these tools
by dgb23 | 2025-06-02 21:45:20+00:00
My hunch is that to exploit LLMs one should lean on data driven code more. LLMs seem to have a very easy time to generate data literals. Then it's far less of an issue to write in a niche language.

Not familiar with Elixir but I assume it's really good at expressing data driven code, since it's functional and has pattern matching.
by seabrookmx | 2025-06-02 21:45:39+00:00
They're not arbitrary, far from it. You have a very constrained set of tools each agent can do. An agent has a "job" if you will.

Maybe the agent feeds your PR to the LLM to generate some feedback, and posts a the text to the PR as a comment. Maybe it can also run the linters, and use that as input to the feedback.

But the at the end of the day, all it's really doing is posting text to a github comment. At worst it's useless feedback. And while I personally don't have much AI in my workflow today, when a bunch of smart people are telling me the feedback can be useful I can't help but be curious!
by williamcotton | 2025-06-02 21:46:02+00:00
Static errors are caught by linters before runtime errors are caught by a test suite. When you have an LLM in a feedback loop, otherwise known as an agent, then iterative calls to the LLM will include requests and responses from linters and test suites, which can assure the user, who typically follows along with the entire process, that the agent is writing better code than it would otherwise.
by nathan_douglas | 2025-06-02 21:46:27+00:00
These are delightful. I think I like LingoPrio the best, since I'm (re)learning French. My kid and I went to a pediatrician appointment and my kid asked, "How do you say 'constipation' in French?" And I didn't have to look it up, since it ended in "ation".

> I just enjoy exploring what the web can be when it doesn’t try to be “useful”.

I have a project that's arguably strange but deeply serious. I'm building a Pi Bramble [1] and adding services with the goal of making a homelab that is continuously collapsing under the weight of its own complexity. Y'know, for education! But it's also really fun, when I have time to spend on it.

[1] https://clog.goldentooth.net/
by grues-dinner | 2025-06-02 21:46:29+00:00
Minutes to start and get the book open, and stuttering when doing things like choosing a book and turning pages was eventual my experience on all the devices: iPad Mini, Nexus 7, and a Samsung Tab 10.1. To be fair, someone else I know had an iPad Air for years and it was completely fine, so maybe they're the only tablets that actually work (or the Mini was a lemon and Androids just are bad?). Or maybe tablets are better since then: it's been a very long time since those devices went into a drawer, never to be used again.
by spiksla | 2025-06-02 21:46:31+00:00
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by Invictus0 | 2025-06-02 21:47:01+00:00
John Rockefeller didn't sit down in a big chair, twirl his mustache, and invent AI to funnel money to the hands of the wealthy. This technology was created by researchers and has been mostly accessible to everyone for as long as it has been around.

All technology has the effect of concentrating wealth, and anyone who insists on using their two hands to fashion things when machines exist that can do it better will always be relegated to the "artisan" bin as time rolls on.
by alkonaut | 2025-06-02 21:47:01+00:00
I can’t even get copilot to autocomplete 5 working lines consistently. I spend hours every day arguing with ChatGPT about things it’s hallucinating. And Agents? It took me a year to convince anyone to buy me a copilot subscription. It’s not good enough now? But it was the bees knees just a year or two ago? See I hate the thing where the JS-framework tempo thing happens to the part of the software world I’m in.
Automated ML research, AI drives the process from idea to report
by killerstorm | 2025-06-02 21:47:13+00:00
LLMs are now sufficiently smart to do at least some basic ML research tasks autonomously (going from idea to report). And quite likely by the end of the year they might be capable enough to reproduce ML papers with some variations, thus, possibly, accelerating AI research.

Example of autonomous work (artifacts): https://github.com/killerstorm/auto-ml-runner-artifacts/tree...

Runner script: https://github.com/killerstorm/auto-ml-runner
by edflsafoiewq | 2025-06-02 21:47:18+00:00
What translation models are better than LLMs?

The problem with Google-Translate-type models is the interface is completely wrong. Translation is not sentence->translation, it's (sentence,context)->translation (or even (sentence,context)->(translation,commentary)). You absolutely have to be able to input contextual information, instructions about how certain terms are to be translated, etc. This is trivial with an LLM.
by guywithahat | 2025-06-02 21:47:58+00:00
I mean it depends on the model; some people running deepseek report they have better performance at home running on a CPU with lots of ram (think a few hundred gigabytes). Even when running locally vram is more relevant than the performance of the GPU. That said I'm really not the person to ask about this, as I don't have AI agents running amuck on my machine yet
by juancn | 2025-06-02 21:48:12+00:00
There's so many graduates that are not worth the paper their degree is printed on that it's laughable (if it weren't sad).

That's a good part of the reason why hiring processes are so long and you need to re-check everything people are supposed to know. Filtering out hundreds of candidates to get a mediocre one at best, thousands to get a really good one.

There are job openings, but just having a piece of paper is not enough to get to those.

AI tools have made recruiting a miserable experience for everyone involved, there's so much cheating in applicants and you waste so much time filtering those out and sadly, good candidates sometimes get lost in the noise.

Networking is what has the highest signal to noise ratio. A good recommendation from someone you trust helps a lot, but it penalizes people just starting their careers and have smaller networks.

It's a sad state of affairs.
by darepublic | 2025-06-02 21:48:18+00:00
I do use LLMs for coding and the newer models have definitely been a blessing. I don't know about using coding agents (or agentic coding) though. I personally do not find this better than chatting with the llm, getting the code back and then copy / pasting it and grokking / editing it. The author of this seems to suggest that.. there is one correct flow, his flow (which he doesn't entirely detail) and everything else is not appropriate. He doesn't go into what his process is when the LLM hallucinates either. Not all hallucinations show up in static analysis.
by Workaccount2 | 2025-06-02 21:48:50+00:00
Real devs excel at writing software for hundreds, thousands, millions of users with fractal use cases and feature needs.

LLMs excel at writing software for one or a handful of users with a very narrow but very well defined use cases.

I don't need an LLM to write Excel.exe for keeping track of 20 employee's hours. A simple GUI on a SQLite database can easily do that.
by BoorishBears | 2025-06-02 21:49:02+00:00
Well everyone's experience is different, but that's been a pretty atypical failure mode in my experience.

That being said, I don't primarily lean on LLMs for things I have no clue how to do, and I don't think I'd recommend that as the primary use case either at this point. As the article points out, LLMs are pretty useful for doing tedious things you know how to do.

Add up enough "trivial" tasks and they can take up a non-trivial amount of energy. An LLM can help reduce some of the energy zapped so you can get to the harder, more important, parts of the code.

I also do my best to communicate clearly with LLMs: like I use words that mean what I intend to convey, not words that mean the opposite.
by fellowniusmonk | 2025-06-02 21:49:08+00:00
Frankly, as someone who is engaged in fields where LLMs can be used heavily.

I would stay in any high danger/high precision/high regulation role.

The speed at which LLM stuff is progressing is insane, what is cutting edge today wasn't available 6 months ago.

Keep up as a side hobby if you wish, I would definitely recommend that, but I just have to imagine that in 2 years a turnkey github project will get you pretty much all the way there.

Idk, that's my feeling fwiw.

I love LLMs but I'm much less confident that people and regulation will keep up with this new world in a way that benefits the very people who created the content that LLMs are built on.
by sannysanoff | 2025-06-02 21:49:20+00:00
Got a new Mac, found the Desk View app (pre-installed).

Enjoyed it.

Before, I felt mute during Zoom meetings. Now I can explain things with paper and pen. Mouse drawing was never my thing.

My friends couldn’t do the same—it’s a native app for newer Macs only. They all use different OSes or older hardware.

Spent half a day vibe coding a public version. Enjoy. Free as in beer.

Make sure to enable webcam permissions on the page.

Explanation:

=============

This tool displays a live, perspective-corrected view of your camera pointed at a sheet of paper—like a whiteboard for your meetings. Next, you share that browser tab to your colleagues.

Limitations:

===========

1. On Windows, stop using the camera in your meeting app (e.g., Zoom) to allow browser access. Not needed on Mac; possibly not needed on Linux.

2. You must tilt your laptop lid down ~45° during setup and use.

3. TODO: Allow setting up paper corners falling outside of the camera view.

Usage:

==========

• You can share the browser tab in your meeting.

• If Windows+Zoom => stop camera in zoom

• Ensure webcam feed is visible on this app/page.

• Tilt the lid, aim the camera at your paper.

(One-time setup for your paper type)

• With the lid tilted, press spacebar to hold a snapshot.

• Return the lid to upright position.

• Adjust the trapezoid corners to fit your paper.

• Press spacebar again to release the video.

• Tilt the lid again and place your paper within the trapezoid.

(End setup)

• With the lid tilted, press Enter to enter presentation mode.
by neilcresswell | 2025-06-02 21:49:37+00:00
If you have a need to run Kubernetes at the device edge (think IOT), and are struggling to get k3s, k0s, microk8s working on such lightweight hardware (1 CPU, <1GB RAM) then we might have just the solution for you.

KubeSolo is a purpose-built Kubernetes distro built for tiny devices. Designed to run on hardware with just 512MB of RAM and a single-core ARM/Atom CPU.

It's not designed to compete with more established distros; it's intended to provide an option for running Kubernetes when those are too resource-intensive to work.

Should you run Kubernetes on your IOT hardware?? Only if you absolutely need to (your ISV only supports Kube).. else run Docker/Podman, or even just directly installed binaries...

KubeSolo, when no other distro will run.

Open Source, MIT Licensed...

github.com/portainer/kubesolo
by Denzel | 2025-06-02 21:49:42+00:00
Thanks for sharing!

It's worthwhile to note that https://github.com/deepseek-ai/open-infra-index/blob/main/20... shows cost vs. theoretical income. They don't show 80% gross margins and there's probably a reason they don't share their actual gross margin.

OpenAI is the easiest counterexample that proves inference is subsidized right now. They've taken $50B in investment; surpassed 400M WAUs (https://www.reuters.com/technology/artificial-intelligence/o...); lost $5B on $4B in revenue for 2024 (https://finance.yahoo.com/news/openai-thinks-revenue-more-tr...); and project they won't be cash-flow positive until 2029.

Prices would be significantly higher if OpenAI was priced for unit profitability right now.

As for the mega-conglomerates (Google, Meta, Microsoft), GenAI is a loss leader to build platform power. GenAI doesn't need to be unit profitable, it just needs to attract and retain people on their platform, ie you need a Google Cloud account to use Gemini API.
by timr | 2025-06-02 21:50:01+00:00
As someone who has spent the better part of today fixing the utter garbage produced by repeated iteration with these supposedly magical coding agents, I'm neither in the camp of the "AI skeptic" (at least as defined by the author), nor am I in the camp of people who thinks these things can "write a large fraction of all the tedious code you’ll ever need to write."

Maybe I'm doing it wrong, but I seem to have settled on the following general algorithm:

* ask the agent to green-field a new major feature.

* watch the agent spin until it is satisfied with its work.

* run the feature. Find that it does not work, or at least has major deficiencies [1]

* cycle through multiple independent iterations with the agent, doing something resembling "code review", fixing deficiencies one at a time [2]

* eventually get to a point where I have to re-write major pieces of the code to extract the agent from some major ditch it has driven into, leading to a failure to make forward progress.

Repeat.

It's not that the things are useless or "a fad" -- they're clearly very useful. But the people who are claiming that programmers are going to be put out of business by bots are either a) talking their book, or b) extrapolating wildly into the unknown future. And while I am open to the argument that (b) might be true, what I am observing in practice is that the rate of improvement is slowing rapidly, and/or the remaining problems are getting much harder to solve.

[1] I will freely grant that at least some of these major deficiencies typically result from my inability / unwillingness to write a detailed enough spec for the robot to follow, or anticipate every possible problem with the spec I did bother to write. T'was ever thus...

[2] This problem is fractal. However, it's at least fun, in that I get to yell at the robot in a way that I never could with a real junior engineer. One Weird Fact about working with today's agents is that if you threaten them, they seem to do better work.
by genewitch | 2025-06-02 21:50:15+00:00
Its ~50 to eat at any sit down restaurant for two adults in Central Louisiana; compare to 20 years ago where I was feeding a family of four for $40 in southern california.

The inflation is staggering.

Anyone else remember the $6 Burger from Carl's? It didn't cost $6 at first, it cost like $3, and was aimed at "expensive restaurant burgers" They discontinued the Burger when tbe Burger itself cost $6 a LA carte.

A $6 burger now is a steal
by sneak | 2025-06-02 21:50:22+00:00
“an LLM made a mistake once, that’s why I don’t use it to code” is exactly the kind of irrelevant FUD that TFA is railing against.

Anyone not learning to use these tools well (and cope with and work around their limitations) is going to be left in the dust in months, perhaps weeks. It’s insane how much utility they have.