MurphyA/hacker-news huggingface dataset:
by vigneshnkumar | 2025-06-02 19:30:40+00:00
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by fellowniusmonk | 2025-06-02 19:30:56+00:00
I really don't understand people who are down on LLM.

In terms of code output. I have gone from the productivity of being a Sr. Engineer to a team with .8 of a Sr. Engineer, 5 Jr. Engineers and One dude solely dedicated to reading/creating documentation.

Unlike a lot of my fellow engineers who are also from traditional CS backgrounds and haven't worked in revenue restricted startup environments, I also have been VERY into interpreted languages like ruby in the past.

Now compiled languages are even better, I think from a velocity perspective compiled languages are now incredibly on par for prototyping velocity and have had their last weakness removed.

It's both exciting and scary, I can't believe how people are still sleep walking in this environment and don't realize we are in a different world. Once again the human inability to "gut reason" about exponentials is going to screw us all over.

One terribly overlooked thing I've noticed that I think explains the differing takes. Foundation of my position here: https://www.nature.com/articles/s41598-020-60661-8

Within the population that writes code there are a small number of successful people who approach the topic in a ~purely mathematical approach, and a small number of successful people that approach writing code in a ~purely linguistic approach. Most people fall somewhere in the middle.

Those who are on the MOST extreme end of the mathematic side and are linguistically bereft HATE LLM's and effectively cannot use them.

My guess is that HN population will tend to show stronger reactions against LLM's because it was heavily seeded with functional programmers which I think has a concentration of the successful extremely math focused. I worked for several years in a purely functional shop and that was my observation: Elixir, Haskell, Ramda.

Just my speculation.
by CalRobert | 2025-06-02 19:31:10+00:00
It's definitely an issue - I was at a heat pump company working on data, and as much as the work was interesting (and I liked doing something related to sustainability), there was a core question of "wait, _why_ do we need to gather data from everyone's thermostats again?"

Though as we move towards things like virtual power plants and more integrated systems with home batteries, etc. the use case is clearer.
by foobiekr | 2025-06-02 19:31:18+00:00
Charitably, your low expectations are probably the source of your finding them acceptable.

It’s also possible - and you should not take this as an insult, it’s just the way it is - you may not know enough about the subjects of your interactions to really spot how wrong they are.

However the cases you list - brainstorming - don’t really care about wrong answers.

Coding is in the eye of the beholder, but for anything that isn’t junk glue code, scripts or low-complexity web stuff, I find the output of LLMs just short of horrendous.
by thewebguyd | 2025-06-02 19:31:44+00:00
> I think there's a huge huge space of software to build that isn't being touched today because it's not cost-effective to have an engineer build them.

That's definitely an interesting area, but I think we'll actually see (maybe) individual employees solving some of these problems on their own without involving IT/the dev team.

We kind of see it already - a lot of these problem spaces are being solved with complex Excel workflows, crappy Access databases, etc. because the team needed their problem solved now, and resources couldn't be given to them.

Maybe AI is the answer to that so that instead of building a house of cards on Excel, these non-tech teams can have something a little more robust.

It's interesting you mentioned accounting, because that's the one department/area I see taking off and running with it the most. They are already the department that's effectively programming already with Excel workflows & DSLs in whatever ERP du jour.

So it doesn't necessarily open up more dev jobs, but maybe fulfills the old the mantra of "everyone will become a programmer." and we see more advanced computing become a commodity thanks to AI - much like everyone can click their way through an office suite with little experience or training, everyone will be able to use AI to automate large chunks of their job or departmental processes.
by acj | 2025-06-02 19:33:12+00:00
They un-archived it today long enough to revert a change to the purging algorithm that was merged in March [0]. The first archive date I saw this morning was from the last week of May. I won't speculate about the reason, but it's a small relief that the archiving seems deliberate and that the maintainers are still active.

[0] https://github.com/jemalloc/jemalloc/commit/27d7960cf9b48a9a...
by gte525u | 2025-06-02 19:33:48+00:00
^This - we're trying to use one to partially automate some system engineering type activities.

It's great for reviews where any given reviewer could be expected to have a misunderstanding of certain details or skip a section (RAG somewhat helps this) - but it's frustrating for artifact generation where missing details cascade through the project.

As great as the technology (right now) it seems so far from reliable business process automation.
by zX41ZdbW | 2025-06-02 19:34:02+00:00
Nice trick:

> How is it faster than std: It uses the fact that popcount of a uniformly distributed integer follows a binomial distribution. By rescaling that binomial distribution and adding some linear fill we can achieve a curve very similar to a proper normal distribution in just a few instructions. While that level of precision is not suitable for a general use, in instances where quality is not particularly important (gamedev, fuzzing) this is perhaps the fastest possible way of generating normally distributed floats.
by CuriouslyC | 2025-06-02 19:34:24+00:00
If they're public, it'd be fair use, and I guess they could stop you by not letting you download them in the first place, but if they're out there it's fair game. WRT the original point you were trying to make, I agree that using the pile/libgen is questionable, but so are publishers trying to gouge companies who use the materials for training by charging them a higher price than they'd charge people with the intention of reading the book.

If your problem is billionaires, that's separate from AI (which can be open source and run on commodity systems), and we can also have a conversation there. Shitting on AI because some unethical actors are pursuing it is like shitting on top hats and monocles because rich people wear them though.
by AlienRobot | 2025-06-02 19:35:01+00:00
I'm no AI fan, but articles talking about the shortcomings of LLM's seem to have to be complaining that forks aren't good for drinking soup.

Don't use LLM's to do 2 + 2. Don't use LLM's to ask how many r's are in strawberry.

For the love of God. It's not actual intelligence. This isn't hard. It just randomly spits out text. Use it for what it's good at instead. Text.

Instead of hunting for how to do things in programming using an increasingly terrible search engine, I just ask ChatGPT. For example, this is something I've asked ChatGPT in the past:

in typescript, I have a type called IProperty<T>, how do I create a function argument that receives a tuple of IProperty<T> of various T types and returns a tuple of the T types of the IProperty in order received?

This question that's such an edge case that I wasn't even sure how to word properly actually yielded the answer I was looking for.

function extractValues<T extends readonly IProperty<any>[]>( props: [...T] ): { [K in keyof T]: T[K] extends IProperty<infer U> ? U : never } { return props.map(p => p.get()) as any; }

This doesn't look unrealiable to me. It actually feels pretty useful. I just need [...T] there and infer there.
by heyyfernanda | 2025-06-02 19:35:27+00:00
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by keybrd-intrrpt | 2025-06-02 19:35:50+00:00
That's all new technology though. Dishwashers _were_ like that.

What's seemed to change are people's expectations of technology that "just works". When in reality, we are in the infant years of AI/ML and LLMs

We're so spoiled by the pace of innovation we're upset it requires a bit of hand-holding while they figure things out.
by Ramsundar24 | 2025-06-02 19:36:58+00:00
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by polivier | 2025-06-02 19:37:23+00:00
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by polivier | 2025-06-02 19:38:05+00:00
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by GauntletWizard | 2025-06-02 19:38:13+00:00
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by hypeatei | 2025-06-02 19:38:15+00:00
I think what's more angsty is replies like this. You can't possibly fathom anything other than the default so you fallback to slop like this.

Yes, life can suck and I'm not saying we need to suicide as a species because of that. But, individuals can experience a much larger percentage of suffering than joy. So is it unreasonable to at least consider that possibility rather than going "haha you were brought into this world, suck it up and be happy"?
by HideousKojima | 2025-06-02 19:38:22+00:00
Doesn't really do anything to ensure the end-user truly has ownership over the device and the ability to control what software runs on it. 10 years of security updates is nice (assuming the company making the device doesn't go out of business in that time) but doesn't stop those devices becoming vulnerable after that (and a truly useful device will likely have more than 10 years of useful life). I don't know the specifics of the CRA, but most proposed regulatory solutions I've seen intentionally take control away from the end-user.
by pmdulaney | 2025-06-02 19:38:46+00:00
Most likely because of its connection with Columbia University, which Trump and the populist wing of the Republican party hate.

I voted for Trump and I can't say I regret it, but he sure has been a disappointment this time around. I fear that the populists are greatly influenced by envy, which is an unfortunate and unfruitful sensibility. Every young American should be raised to believe that there are many, many people in this country who are smarter and harder-working than he or she is. But you can aspire to be like them! And ascend to great heights, Lord willing. Envy is pathetic, envy is a symptom of giving up, envy is sin.
by arendtio | 2025-06-02 19:38:59+00:00
One way to mitigate the issue is to use tests or specifications and let the AI find a solution to the spec.

A few months ago, solving such a spec riddle could take a while, and most of the time, the solutions that were produced by long run times were worse than the quick solutions. However, recently the models have become significantly better at solving such riddles, making it fun (depending on how well your use case can be put into specs).

In my experience, sonnet 3.7 represented a significant step forward compared to sonnet 3.5 in this discipline, and Gemini 2.5 Pro was even more impressive. Sonnet 4 makes even fewer mistakes, but it is still necessary to guide the AI through sound software engineering practices (obtaining requirements, discovering technical solutions, designing architecture, writing user stories and specifications, and writing code) to achieve good results.

Edit: And there is another trick: Provide good examples to the AI. Recently, I wanted to create an app with the OpenAI Realtime API and at first it failed miserably, but then I added the most important two pages of the documentation and one of the demo projects into my workspace and just like that it worked (even though für my use-case the API calls had to be use quite differently).
by ArchieHub | 2025-06-02 19:39:15+00:00
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Hi, my name is Marius and I am the CTO at Archie (https://www.archiehub.com/). Archie is here to make buying a home easier, faster, and more transparent by reducing paperwork and improving efficiency. We are well-funded, growing quickly, and led by founders with over 20 years of combined experience in real estate and tech.

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by raminf | 2025-06-02 19:40:25+00:00
Any post about IoT security that doesn't mention or link to Shodan (https://www.shodan.io) is missing a lot of context. It's way worse than you think.

Also, with tools like Chip Whisperer (https://www.newae.com/chipwhisperer) the physical security of the hardware root of trust needs to be reevaluated.
by ironman1478 | 2025-06-02 19:40:49+00:00
What are you doing to actually keep them at your company? I left a company after they invested a lot in training me. They gave me very little raises and already paid poorly, no guaranteed bonus, bad vacation hours, and no opportunities for promotion. They were shocked when I left, even though I had asked for very modest raises and was way more productive than the "seniors" at the company.

Most companies outside of FAANGs treat their talented juniors like crap, so of course they'll leave.
by ghita_ | 2025-06-02 19:40:52+00:00
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by PaulHoule | 2025-06-02 19:40:56+00:00
Yeah, I am thinking of updating my autoposter so it reads the headlines and if it has been changed the system will edit it back to what it was. It's enough of a hassle to squeeze everything into 80 characters, but to never be allowed to start a headline with "How" is ridiculous.

As for the article, it's a running gag in my pod that articles get posted about animals that prove what people working with animals already knew all of the time. Probably the best category is the studies that show that various animals have a "theory of mind" which is probably is intrinsic to being able to hunt or not get hunted but frequently a difficult experiment to set up.
by runjake | 2025-06-02 19:40:56+00:00
I can no longer edit my above comment, but I've since been keeping track of purported drone videos on the news and Reddit.

It looks to me like these drones are being steered into aircraft by remote human pilots. The control plane adjustments as the drones approach a target don't look like they're being autonomously directed.

Here's some brief footage at this link: https://www.nbcnews.com/world/ukraine/ukraines-massive-drone...
by jmeyers44 | 2025-06-02 19:41:22+00:00
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by glkindlmann | 2025-06-02 19:42:09+00:00
Now that I've actually looked at the "utl::random" code in the OP, I see that its UniformRealDistribution is a wrapper around std::generate_canonical, so the juicy bits about turning a random into into a random float are not exposed here at all. But the utl::random code does include an pointer* to an informative C++ working group note.

* https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2023/p09...
by wvoch235 | 2025-06-02 19:42:35+00:00
IMO attempts to make it low paid work will fail, just like almost every STEM profession. But... the number of engineers that we need who operate as "power multipliers" on team will continue to decrease. Many startup and corporate teams already aren't needing junior/mid level engineers any longer.

They just need "drivers", senior/lead/staff engineers that can run independent tracks. AI becomes the "power multiplier" in the teams who amplify the effects of the "driver".

Many people pretend that 10x engineers don't exist. But anyone who has worked on an adequately high performing team at a large (or small) company knows that skill, and quite frankly intelligence, operate on power laws.

The bottom 3 quartiles will be virtually unemployable. Talent in the top quartile will be impossible to find because they're all employed. Not all that unlike today, though which quartile you fall into is largely going to depend on how "great" of an engineer you are AND how effectively you use AI.

As this happens, the tap of new engineers who are learning how to make it into the top quartile, will cutoff for everyone except for those who are passionate/sadistic enough to programming without AI, then learn to program WITH AI.

Meanwhile the number of startups disrupting corporate monopolies will increase as the cost of labor goes down due to lower headcount requirements. Lower head counts will lead to better team communication and in general business efficiency.

At some point the upper quartile will get automated too. And with that, corporate moats evaporate to solo-entrepreneurs and startups. The ship is sinking, but the ocean is about to boil too. When economic formulas start dividing by zero, we can be pretty sure that we can't predict the impact.