MurphyA/hacker-news huggingface dataset:
by dannyobrien | 2025-06-02 21:33:58+00:00
This is also where I am, and I guess it has been a source of mild and growing consternation since I first blagged an OpenAI GPT account when they were private, in an attempt to get ahead of what was coming -- both the positive and negative sides of the advances. Most people either ignored the advances, or quickly identified and connected to the negative side, and effectively filtered out the rest.

As somebody who comes from a politically left family, and was also around in the early days of the Web, let me tentatively note that this issue has a particular political slant, too. The left has strong roots in being able to effectively critique new developments, economic and social, that don't come from its own engines of innovation which have revolved around those critiques, plus solidarity, organization, and sociopolitical action.

The movement's theorists work far more slowly on how to integrate the effect of those changes into its vision. That means when something like this comes along, the left's cultural norms err on the side of critique. Which is fine, but it makes any other expression both hard to convey, and instantly suspect in those communities. I saw this in the early Web, where from a small group of early adopters of all political slants, it was the independents, heterodox leftists, and the right, -- and most vocally, the libertarians -- who were able to most quickly adapt to and adopt the new technology. Academic leftists, and those who were inspired by them took a lot longer to accomodate the Net into their theses (beyond disregarding or rejecting it) and even longer to devise practical uses for it.

It wasn't that long, I should say -- a matter of months or years, and any latent objections were quickly swamped by younger voices who were familiar with the power of the Net; but from my point of view it seriously set back that movement in practicality and popularity during the 80s and 90s.

I see the same with AI: the left has attracted a large generational of support across the world from providing an emotionally resonant and practical alternative to the status quo many people face. But you quickly lose the mandate of heaven if you fail to do more than just simplistically critique or reject a thing that the average person in the world feels they know better, or feels differently toward, than you do. This is something to consider, even if you still strongly believe yourselves to be correct in the critiques.
by GuB-42 | 2025-06-02 21:34:27+00:00
Looked at french words, most have a rating of 2 (mostly profane) even for words that are not profane at all (ex: envoyer => send), words that have a profane second meaning, but their non-profane meaning is also in common use (ex: morue => cod). Also "retard" just means "delay", I have never heard it used as profanity, maybe in Quebec? ("retard" in English would translate to "attardé" in French)
by baobun | 2025-06-02 21:34:31+00:00
The privacy aspect and other security risks tho? So far all the praise I hear on productivity are from people using cloud-hosted models.

Claude, Gemini, Copilot and and ChatGPT are non-starters for privacy-minded folks.

So far, local experiements with agents have left me underwhelmed. Tried everything on ollama that can run on my dedicated Ryzen 8700G with 96GB DDR5. I'm ready to blow ~10-15k USD on a better rig if I see value in it but if I extrapolate current results I believe it'll be another CPU generation before I can expect positive productivity output from properly securely running local models when factoring in the setup and meta.
by homefree | 2025-06-02 21:34:35+00:00
Yes! It's amazing how even in a field that tends to lean more early adopter than average you still get a lot of the default knee-jerk dismissal and cynicism - even when it's something clearly amazing and useful as thinking machines.

We're in the middle of a major shift - there will benefits to those that adapt first. People outside the field have no idea what's coming, even those of us in the field are underestimating the shift.

There were a few outliers in the 60s who understood what the computing revolution meant and would mean, but most did not. This is likely an even bigger change than that.
by AnotherGoodName | 2025-06-02 21:34:48+00:00
This happened with the introduction of smartphones too. Every slashdot post had a haughty and upvoted ‘why would i want such a thing!!!’.

It was obviously huge. You could see it taking off. Yet a lot of people proudly displayed ignorance and backed each other up on it to the point that discussion around the topic was often drowned out by the opposition to change. Now today it takes minutes of playing with ai coding agents to realise that it’s extremely useful and going to be similarly huge.

Resistance to change is not a virtue!
by coderholic | 2025-06-02 21:34:53+00:00
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We're always on the look out to strong software or data engineers with an internet measuremenet / analysis background to join our team too.
by __padding | 2025-06-02 21:34:58+00:00
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by sublinear | 2025-06-02 21:35:12+00:00
I have to completely agree with this and nobody says this enough.

This tradeoff of unfamiliarity with the codebase is a very well understood problem for decades. Maintaining a project is 99% of the time spent on a successful project.

In my opinion though, having AI write the initial code is just putting most people in a worse situation with almost no upside long term.
by derefr | 2025-06-02 21:35:44+00:00
So do the thing that a student copying their notes from the board does: look at the PR on one monitor, and write your own equivalent PR by typing the changes line-for-line into your IDE on the other. Pretend copy/paste doesn’t exist. Pretend it’s code you saw in a YouTube video of a PowerPoint presentation, or a BASIC listing from one of those 1980s computing magazines.

(And, if you like, do as TFA says and rephrase the code into your own house style as you’re transcribing it. It’ll be better for it, and you’ll be mentally parsing the code you’re copying at a deeper level.)
by FridgeSeal | 2025-06-02 21:35:51+00:00
The counter-argument as I see it is that going from “not using LLM tooling” to “just as competent with LLM tooling” is…maybe a day? And lessening and the tools evolve.

It’s not like “becoming skilled and knowledgeable in a language” which took time. Even if you’re theoretically being left behind, you can be back at the front of the pack again in a day or so. So why bother investing more than a little bit every few months?
by _jsunj | 2025-06-02 21:35:56+00:00
Location: Atlanta, GA, USA Remote: Yes Willing to relocate: Yes Technologies: JavaScript, TypeScript, Python, Node.js, React, Express, PostgreSQL, MongoDB, AWS (EC2, ECS, S3, ELB, VPC, CloudFormation, IAM), Docker, OpenAI API, LLM, RAG, Linux, Bash Résumé/CV: https://drive.google.com/file/d/10OhRUpQ4-DVTJQ2ocvfiadMUE1QVbtpR/view?usp=sharing Email: jasonjabarjones@gmail.com

Greetings! I'm Jason, a full-stack engineer with an affinity for back-end & cloud infrastructure, plus 8+ years of experience in healthcare & higher education systems administration. I recently created Providence (https://providence-replay.github.io/), an open-source session replay framework leveraging AI technologies for user session analytics. I've also been an active open source contributor to Firefox Desktop and wrote a short overview of some of that work here: https://medium.com/p/cc475fff189d
by mjburgess | 2025-06-02 21:36:07+00:00
Can we get a video of a workday conducted by these people?

Unless there's a significant sense of what people are working on, and how LLMs are helping -- there's no point engaging -- there's no detail here.

Sure, if your job is to turn out tweaks to a wordpress theme, presumably that's now 10x faster. If its to work on a new in-house electric motor in C for some machine, presumably that's almost entirely unaffected.

No doubt junior web programmers working on a task backlog, specifically designed for being easy for juniors, are loving LLMs.

I use LLMs all the time, but each non-trivial programming project that has to move out of draft-stage needs rewriting. In several cases, to such a degree that the LLM was a net impediment.
by steveklabnik | 2025-06-02 21:36:35+00:00
I do think that's a poor argument, but there's a better version: tools take skills to use properly.

The other day, I needed to hammer two drywall anchors into some drywall. I didn't have a hammer handy. I used the back of a screwdriver. It sucked. It even technically worked! But it wasn't a pleasant experience. I could take away from this "screwdrivers are bullshit," but I'd be wrong: I was using a tool the wrong way. This doesn't mean that "if you just use a screwdriver more as a hammer, you'll like it", it means that I should use a screwdriver for screwing in screws and a hammer for hammering things.
by tim333 | 2025-06-02 21:36:52+00:00
>Yet, the Saturn V launched 50 tonnes to the Moon for only $1.8 billion in today’s dollars

According to Wikipedia the Apollo program cost $257 billion in 2020 dollars which given ~20% inflation since is a little over $300bn. The $10bn on Starship so far is quite modest in comparison. The article seems a bit biased against it. I mean:

>Is this progress? If we are being pedantic, sure. Reusing a Super Heavy Booster and reaching orbital speeds without exploding are both steps forward. But in all actuality, this was a lateral move.

Getting to orbit when you haven't before isn't progress? C'mon.

Musk did a presentation on how it's going a couple of days ago http://x.com/SpaceX/status/1928185351933239641 It's quite interesting. Some seems like usual Musk overoptimtic projections but they've made a lot of progress on the raptor 3 engine which is a real thing that's working.
by jchw | 2025-06-02 21:37:00+00:00
The best answer to this is literally "I don't know." I can actually observe what my hand does and give you an answer, but the truth is that I don't conciously make a choice. I do rely on the bumps on f and j to align my fingers initially, and I know I make use of keys with different shapes as landmarks. Otherwise though it just kind of floats around. I would guess it looks a bit like playing a musical instrument (but I don't play any, so hell if I know.)
by skissane | 2025-06-02 21:37:36+00:00
> When stuff slips through code review, even if it is a mistake you might have made, you would remember that you made it.

I don’t know. Ever had the experience of looking at 5+ year old code and thinking “what idiot wrote this crap” and then checking “git blame” and realising “oh, I’m the idiot… why the hell did I do this? struggling to remember” - given enough time, humans start to forget why they did things a certain way… and sometimes the answer is simply “I didn’t know any better at the time, I do now”

> You don't get that with AI. The codebase is always new.

It depends on how you use AI… e.g. I will often ask an AI to write me code to do X because it gets me over the “hump” of getting started… but now this code is in front of me on the screen, I think “I don’t like how this code is written, I’m going to refactor it…” and by the time I’m done it is more my code than the AI’s
by stock_toaster | 2025-06-02 21:37:56+00:00
I read a study[1] (caveat, not peer reviewed yet I don't think?) that seems to imply that you are correct.

< When using GenAI tools, the effort invested in critical thinking < shifts from information gathering to information verification; < from problem-solving to AI response integration; and from task < execution to task stewardship.

[1]: https://www.microsoft.com/en-us/research/wp-content/uploads/...
by pixl97 | 2025-06-02 21:38:15+00:00
>Yeah, who cares about the quality, the mediocrity, the craft..

Just about no-one in the F100 unless they are on very special teams.

If you care about the craft you're pushed out for some that drops out 10x LOC a day because your management has no ability to measure what good software is. Extra bonus points for including 4GB of node_modules in your application.
by matt_lo | 2025-06-02 21:38:19+00:00
5 minutes of typeracer saves 1 hour of procrastination

Typing fast is a way to unlock the brain. Anything past 90, you start to focus on exactly what is needed to type accurately with speed.

I average around 106-130 (depending on recent races) for the past 15 years, and it's still one of the best ways to "get into dev mode" really quickly.
by SideQuark | 2025-06-02 21:38:33+00:00
By far the vast majority of RNG calls in use need to be non-crypto. They are so many orders of magnitude too slow for so many uses that it's ludicrous to claim there are " vanishingly few use cases for non-crypto RNGs," unless you're trying to scare people into using your work.

Science, neural networks, simulation, gaming, rendering, weather, nuclear, robotics, signal processing, engineering, finance, and more industries require fast rngs to get billions to trillions of them quickly.

Very few things actually need secure - only the things that need a secure endpoint, and most of those simply use the secure rng to do a private key transfer algo, after which there is no more rngs.

Use the right tool for the job. Widen your view of what things are used for. Etc.
by bsder | 2025-06-02 21:38:58+00:00
Here's what to do: Show me a video of LLM fixing four filed issues in the KiCad codebase.

If you do that, I'll swallow my AI skepticism.

I would love to have an LLM that I can turn loose on an unfamiliar codebase that I can ask questions of. I would love to have an LLM that will fill in my Vulkan boilerplate. etc.

I use emacs and Mercurial. You can demonstrate magic to me and I can be convinced even if it's not mainstream.

Rewriting Javascript slop to StackOverflow standards is not convincing me.

Get to it.

(The OAuth stuff posted earlier certainly moved my needle, but the fact that they needed a gaggle of reviewers as well as hand holding when the LLM got stuck mutes the impact significantly.)
by albertzeyer | 2025-06-02 21:39:10+00:00
That's not quite true. State of the art both in speech recognition and translation is still a dedicated model only for this task alone. Although the gap is getting smaller and smaller, and it also heavily depends on who invests how much training budget.

For example, for automatic speech recognition (ASR), see: https://huggingface.co/spaces/hf-audio/open_asr_leaderboard

The current best ASR model has 600M params (tiny compared to LLMs, and way faster than any LLM: 3386.02 RTFx vs 62.12 RTFx, much cheaper) and was trained on 120,000h of speech. In comparison, the next best speech LLM (quite close in WER, but slightly worse) has 5.6B params and was trained on 5T tokens, 2.3M speech hours. It has been always like this: With a fraction of the cost, you will get a pure ASR model which still beats every speech LLM.

The same is true for translation models, at least when you have enough training data, so for popular translation pairs.

However, LLMs are obviously more powerful in what they can do despite just speech recognition or translation.
by sarchertech | 2025-06-02 21:39:13+00:00
This article feels incredibly defensive. If you have really have a technique that makes you 100x, 50x, or even just 2x more productive, you don’t need to write an article calling people who don’t agree with you nuts.

You keep using that tool, to your advantage. I’d you’re really altruistic you post some videos of how productive you can be like DHH did with his blog in 15 minute videos.

If you’re really that much more productive, the skeptics won’t be able to keep up and it should only take 6 months or some for that to become self evident.
by capnrefsmmat | 2025-06-02 21:39:49+00:00
The argument seems to be that for an expert programmer, who is capable of reading and understanding AI agent code output and merging it into a codebase, AI agents are great.

Question: If everyone uses AI to code, how does someone become an expert capable of carefully reading and understanding code and acting as an editor to an AI?

The expert skills needed to be an editor -- reading code, understanding its implications, knowing what approaches are likely to cause problems, recognizing patterns that can be refactored, knowing where likely problems lie and how to test them, holding a complex codebase in memory and knowing where to find things -- currently come from long experience writing code.

But a novice who outsources their thinking to an LLM or an agent (or both) will never develop those skills on their own. So where will the experts come from?

I think of this because of my job as a professor; many of the homework assignments we use to develop thinking skills are now obsolete because LLMs can do them, permitting the students to pass without thinking. Perhaps there is another way to develop the skills, but I don't know what it is, and in the mean time I'm not sure how novices will learn to become experts.
by kulahan | 2025-06-02 21:39:52+00:00
Translation seems like the ideal application. It seems as though an LLM would truly have no issues integrating societal concepts, obscure references, pop culture, and more, and be able to compare it across culture to find a most-perfect translation. Even if it has to spit out three versions to perfectly communicate, it’s still leaps and bounds ahead of traditional translators already.
by dgunay | 2025-06-02 21:39:54+00:00
IMO you're better off just asking Aider to write one tailored to your specific use cases. Anonymizing the code so that I could post this gist is actually the first time I've read most of it, and it's really bad code. But in case none of that deters you, here you go: https://gist.github.com/dgunay/4a07db199ca154614c2193718da60...
by ghc | 2025-06-02 21:40:53+00:00
> while people working on DoD contracts will be typing things into vim like a fool

Forget LLMs, try getting Pandas approved. Heck I was told by some AF engineers they were banned from opening Chrome Dev Tools by their security office.

FWIW I think the LLM situation is changing quite fast and they're appearing in some of our contracts. Azure-provided ones, of course.
by fellowniusmonk | 2025-06-02 21:41:23+00:00
If you've ever run or been part of a team that does thorough, multi-party, pull request reviews you know what I am talking about.

The only part I don't automate is the pull request review (or patch review, pre-commit review, etc. before git.), thats always been the line to hold for protecting codebases with many contributors of varying capability, this is explicitly addressed in the article as well.

You can fight whatever straw man you want. Shadowbox the hypotheticals in your head, etc. I don't get all these recent and brand new accounts just straight up insulting and insinuating all this crap all over HN today.
by mrguyorama | 2025-06-02 21:41:25+00:00
How about an automated weapon you shoot from a howitzer 15 miles away that autonomously surveils the area under it's impact zone for a couple armored vehicles and reliably eliminates them?

https://en.wikipedia.org/wiki/SMArt_155

You can actually see video of these in action in Ukraine. Bofors has also produced the BONUS round which is basically identical in action.
by chaps | 2025-06-02 21:41:26+00:00
This is how a (video game) programming class in my high school was taught. You had to transcribe the code from a Digipen book.... then fix any broken code. Not entirely sure if their many typos were intentional, but they very much helped learn because we had no choice but to correct their logic failures and taypos to move onto the next section. I'm still surprised 20 years later how well that system worked to teach and push us to branch our understandings.
by eterm | 2025-06-02 21:41:29+00:00
> if you require your parens to be balanced, that's no longer a regular language.

TIL: https://en.wikipedia.org/wiki/Pumping_lemma_for_regular_lang...

As someone who has only recently learned the formal definition of regular language ( Thanks to https://www.youtube.com/watch?v=9syvZr-9xwk as mentioned on this board recently ), I'm interested in the formal proof for this?

It feels intuitively true, but I haven't finished the course yet and therefore haven't come across it and can't yet reason well about it.

Is the problem then in trying to "encode" whether brackets are balanced, that we would need infinite "levels" of how many more brackets we've opened rather than closed, (i.e a stack) and that violates the finite nature of finite automota?

So I've googled it now, and I've found the result is due to the "Pumping lemma": https://en.wikipedia.org/wiki/Pumping_lemma_for_regular_lang...
by BeetleB | 2025-06-02 21:41:34+00:00
> Machine translation and speech recognition.

Yes, yes and yes!

I tried speech recognition many times over the years (Dragon, etc). Initially they all were "Wow!", but they simply were not good enough to use. 95% accuracy is not good enough.

Now I use Whisper to record my voice, and have it get passed to an LLM for cleanup. The LLM contribution is what finally made this feasible.

It's not perfect. I still have to correct things. But only about a tenth of the time I used to. When I'm transcribing notes for myself, I'm at the point I don't even bother verifying the output. Small errors are OK for my own notes.
by sneak | 2025-06-02 21:41:36+00:00
It’s a riff on the “10x programmer” concept. People who haven’t worked with 10x programmers tend to not believe they exist.

I’m nowhere near that, but even unaided I’m quite a bit faster than most people I’ve hired or worked with. With LLMs my high quality output has easily tripled.

Writing code may be easier than reading it - but reading it is FASTER than writing it. And that’s what matters.