MurphyA/hacker-news huggingface dataset:
by superkuh | 2025-08-21 16:51:27+00:00
This isn't AI damaging anything. This is corporations damaging things. Same as it ever was. No need for scifi non-human persons when legal corporate persons exist. They latch on to whatever big new thing in tech that people don't understand which comes along and brand themselves with it and cause damage trying to make money; even if they mostly fail at it. And for most actual humans they only ever see or interact with the scammy corporation versions of $techthing and so come to believe $techthing = corporate behavior.

And as for denying service and preventing human people from visiting websites: cloudflare does more of that damage in a single day than all these "AI" associated corporations and their crappy crawlers have in years.
by RaftPeople | 2025-08-21 16:51:35+00:00
> "There is no sensible way to represent tree-like data in that [RDBMS] environment" - there is endless literature covering storing data structures in relational schemas. The complaint seems to be to just be "it's complicated".

Ya, this one really confused me. Tree-like data is very easy to model in an RDBMS in the same way it is in memory, with parent+child node pointers/links/keys.

It's possible he was thinking of one of these challenges:

1-SQL doesn't easily handle the tree structure. You can make it work but it's square peg round hole.

2-He mentioned JSON so maybe he was really thinking in terms of different types of data for each node. Meaning one node might have some text data and the next node might have a list or dictionary of values. That is tougher in RDBMS.
by TimCTRL | 2025-08-21 16:52:12+00:00
I like this take, in fact i feel a little uneasy when i see startups mention "MCP" on their landing pages! Its a protocol and its like saying we use HTTP here.

I could be wrong but, all in all, buy a .com for your "ai" product, such that you survive the Dot-ai bubble [1]

I Love LLM's though!! Amazing math and tech.

[1] - https://en.wikipedia.org/wiki/Dot-com_bubble
by cobar | 2025-08-21 16:52:12+00:00
While product often does operate in a waterfall model, I think this is the wrong mindset. Good product management should adopt a lot of the same principles as software development. Form a testable hypothesis, work to get it into production and begin gathering data, then based on your findings determine what the next steps are and whether to adjust the implementation, consider the problem solved or try a different approach.
by kelseyfrog | 2025-08-21 16:52:28+00:00
Organization size has no bearing on veracity. Veracity is a function to closeness to truth, end of story.

Besides, if organization size did have a epistemic preference, then we run into obviously untrue and bizarre preferences.

Maybe yours line up with these:

Catholic Church (~1.3 billion baptized members)

Red Cross / Red Crescent Movement (~97 million volunteers and members)

Scouting Movement (~50+ million members worldwide)

U.S. Department of Defense (~3 million, including active-duty, reserves, and civilians)

People’s Liberation Army (China) (~2 million active personnel)

Walmart (~2.1 million employees worldwide)

Amazon (~1.5 million employees)

Foxconn (~1 million employees)

If they don't, you're just adding epicycles to a very flawed way at arriving at truth. Do you see this as a stable epistemic methodology you'd stand by elsewhere, or is it a situational tactic for this debate?
by bwfan123 | 2025-08-21 16:52:29+00:00
My abstract algebra class had it exactly backwards. It started with a lot of needless formalism culminating in galois theory. This was boring to most students as they had no clue why the formalism was invented in the first place.

Instead, I wished it showed how the sausage was actually made in the original writings of galois [1]. This would have been far more interesting to students, as it showed the struggles that went into making the product - not to mention the colorful personality of the founder.

The history of how concepts were invented for the problems faced is far more motivating to students to build a mental model than canned capsules of knowledge.

[1] https://www.ams.org/notices/201207/rtx120700912p.pdf
by michaelt | 2025-08-21 16:53:09+00:00
Surely all uses of water are part of the closed-loop water cycle? Other than launching it into space for astronauts to drink, and using it in permanent reactions like concrete hydration?

Drinking water, spraying it on crops, using it to clean a car, or using it to flush a toilet all end up with the water evaporating, or making its way to the ocean and evaporating from there.

Ultimately, if a river provides a certain number of acre-feet of fresh water, evaporating it to cool a data centre uses it just as much as to evaporating it to grow alfalfa in a desert, except perhaps more usefully.
by hollowturtle | 2025-08-21 16:53:12+00:00
B2B SaaS in most cases are sophisticated masks over some structured data, perhaps with great ux, automation and convenience, so I can see LLMs be more successful there, even so because there is more training data and many processes are streamlined. Not all domains are equal, go try develop a serious game, not the yet another simple and broken arcade, with llms and you'll have a different take
by vkou | 2025-08-21 16:53:28+00:00
What if you tried your best to do everything that a money launderer does without actually doing any money laundering?

If you and your friends are just innocently idling in a your car wearing a ski mask in the middle of summer with a shotgun and a large duffel bag, in front of a bank that was robbed in this manner four times last month, you're highly unlikely to, at minimum, beat the ride.
by crowcroft | 2025-08-21 16:53:29+00:00
IMO 'Zero return' is really just saying that these companies never had a plan for their AI implementation in the first place, and so never had any idea what they were trying to achieve and measure in the first place.

The article does call out clear issues companies have with AI workflows etc. and those are likely real problems, but if you're saying *zero* return those aren't the root cause problems.
Show HN: DockFlow – Dock presets for instant workflow switching on macOS
by pugdogdev | 2025-08-21 16:53:53+00:00
80 days ago I launched DockFlow and got amazing feedback from the HN community. Since then, I've been building based on your suggestions and just shipped a major update.

What's new since my last post:

- App Actions - Auto-launch apps AND open specific projects in your IDE when switching presets. Switch to "React Project" preset → opens VS Code / Cursor with that exact project + Terminal + browser, all in one click

- Enhanced Shortcuts integration for advanced automation workflows

- More granular CLI tools for power users

- Improved performance and stability based on user feedback

Core DockFlow features:

- Save and instantly switch between multiple Dock configurations

- Assign custom hotkeys to change layouts

- Add apps, folders, files, or website links to your Dock

- Insert visual spacers to organize your workspace

- Lightweight and macOS-native (no permissions needed)

- Supports macOS 13.5+

Real workflow example: My "Development" preset loads Cursor with my current project, opens Terminal in the right directory, launches Figma for designs, and adds project folders to the Dock—all automatically when I switch contexts.

No subscriptions. One-time €9.99 for lifetime access.

Try it: https://dockflow.appitstudio.com/

Would love to hear what other App Actions would be useful for your workflows!
by duxup | 2025-08-21 16:54:10+00:00
I've had bad luck. Most of it very frustrating where the bot obviously doesn't understand anything.

My best luck with a chat bot was ironically only because of HN.

I was to complaining about amazon's chat bot (it would send me in an infinite loop of directions) and someone who worked at Amazon on HN told me that there were multiple chat bots, and they told me the right one use (I had to click a different link on the amazon webpage than I was clicking).

That one worked ... it took some engineer on HN to make me understand how to make it work.
by indoordin0saur | 2025-08-21 16:54:12+00:00
There's definitely a vibe shift underway. C-Suites are seeing that AI as a drop-in replacement for engineers is a lot farther off than initial hype suggested. They know that they'll need to attract good engineers if they want to stay competitive and that it's probably a bad idea to scare off your staff with saying that they'll be made irrelevant.
by Wowfunhappy | 2025-08-21 16:54:32+00:00
How are they decrypting your password manager database? Sure they'll get your tax returns, but while I'm not saying that's great, didn't they get most of it from Equifax anyway?

My personal "thread model" is basically to make sure I can survive an automated attack. I'm convinced I can with my current Mavericks setup. If an experienced attacker was targeting me specifically, I'm sure Mavericks would make their life easier, but I also think they'd probably succeed no matter what OS I was running. https://xkcd.com/538/

But I do have my Bitwarden vault set to use 2,000,000 KDF iterations, literally the highest it will go...
by Symbiote | 2025-08-21 16:54:33+00:00
Using the EU and UK systems is optional, but without using it the small business's customers might be annoyed by the handling fees applied by the recipient's mail carrier, and the delay it causes.

I have seen some foreign merchants (I think DigiKey?) offer the choice, as their business customers don't need to pay VAT directly in this way, and may well prefer to do the import paperwork themselves.

I haven't seen a choice for any large retailer (Amazon, eBay, Etsy, AliExpress etc). They don't want customers annoyed by fees, or returned packages from unpaid fees and duties.
by sc68cal | 2025-08-21 16:54:40+00:00
> Now, CBA has apologized to the fired workers. A spokesperson told Bloomberg that they can choose to come back to their prior roles, seek another position, or leave the firm with an exit payment.

So no real consequences to the Bank for these underhanded tactics, since this just returns everything back to status quo before the layoffs, perhaps with reduced overall headcount as some workers choose not to return and take the exit payment instead, but surely the numbers still worked well enough that they will do it again but be more crafty about it so they don't lose the appeal.
by Fade_Dance | 2025-08-21 16:54:42+00:00
>If we did, it was seemingly mild in hindsight.

That's pretty much the consensus.

Also, remember that markets are most responsive to rates of change, which is an important angle to consider beyond the hard recession definition. It may have technically been a mild recession, but the rates of change in many areas were extreme and had some fairly catastrophic consequences (for example, fixed income/rate volatility getting so high that systemic risk skyrocketed and Fed intervention was required).
by jackero | 2025-08-21 16:55:05+00:00
Here is a long ass post with some more but they come with a huge disclaimer — they are VERY personal opinions:

If you care a lot about plot and hate holes, go for critic >70%. 60-69% is passable but only if you like the subject/genre of the movie.

Very personal opinion — I find any movie with critic <50% completely unwatchable. I literally want to walk out of the theater. This includes nearly every modern horror movie because characters in horror movies always do dumb things. I know that’s the appeal but I hate it.

The extremely rare horror movie with >85% critic probably won’t be scary but these are personally the only horrors I enjoy (e.g. The Cabin in the Woods).

Movies with audience scores below 60% are hard watches.

>90% critic movies are really well done as in they did their homework. Left no stone unturned. It doesn’t mean that it’s an objectively good or memorable movie (use IMDB scores for that).

If you like experimental movies and/or are you’re into filmmaking, go for >90% critic and 65-85% audience for gems. If you’re not, you will HATE these movies.

But watch out — sometimes if you come an across a movie with high critic and low audience, it’s a movie really for people in the movie industry. You have to read the synopsis to figure out which case it is. See Once Upon a Time in Hollywood.

Superhero movies and fandom movies (e.g. LOTR) need extra consideration. If they didn’t follow source material, audience scores seem to be even lower than if it was original content. On the other hand, it also goes the other way.

If you’re a deep cut kind of person, check to make sure that the movie has a high enough rating count. Scores for less well-known movies are less accurate.

Old movies, especially those older than the 70s-80s, are harder to judge on RT. There seems to be a self-selection bias of people who are only rating those movies because they remembered liking them. But at the same time, they were also more revolutionary for their time (to be fair to the movie).

All of these tips are for movies. I watch few TV shows and don’t have insight into that side of RT.
by SpicyLemonZest | 2025-08-21 16:55:08+00:00
Am I not supposed to notice the transition from "he promised me 5 calls and I guaranteed he'd never have to do it again" to "Every engineer takes 5 sales calls per quarter"? This kind of casual dishonesty makes me question the entire story. I've encountered a lot of people who think they're building a better product when they're really building N customized installs that will never again reconverge.
by bee_rider | 2025-08-21 16:55:15+00:00
I think there may have been a miscommunication somewhere on the chain of Mathematicians-Teachers-Students if that was the plan, when I was in elementary school.

Anecdotally (I only worked with math students as a tutor for a couple years), that math requires a lot of the boring type of memorization seems to be a really widespread misunderstanding.
by 1zael | 2025-08-21 16:55:26+00:00
This is clever...using embeddings to turn RSS from a source-following model into a topic-following one based on your daily LLM usage feels like the straightforward evolution of RSS. Have you considered adding a "serendipity slider" to occasionally inject high-quality off-topic content? One of RSS's hidden benefits was stumbling onto things outside your filter bubble.
by systemerror | 2025-08-21 16:55:53+00:00
The big issue with LLMs is that they’re usually right — like 90% of the time — but that last 10% is tough to fix. A 10% failure rate might sound small, but at scale, it's significant — especially when it includes false positives. You end up either having to live with some bad results, build something to automatically catch mistakes, or have a person double-check everything if you want to bring that error rate down.
by SilverElfin | 2025-08-21 16:56:05+00:00
It’s so strange to see Trump destroy America’s relationship with India, which has been slowly building up over 20 years. In my opinion it is really important that America win India over. Without them, there’s no real way to contain China (if that matters) and there’s no other place to get that amount of cheap labor as a manufacturing partner. I saw Trump was also building up new agreements with Pakistan, which probably doesn’t help the India relationship. What’s the strategy here?
by chatmasta | 2025-08-21 16:56:21+00:00
The comment I was responding to was implying that it would be better for the collective if Meta was not paying these exorbitant salaries. You said “it [paying high salaries] is a great way to kneecap collective growth and development.”

In other words, you’re suggesting that _not_ paying high salaries would be good for collective growth and development.

And if Meta is currently willing to pay these salaries, but didn’t for some reason, that would be the definition of wage suppression.
by jcims | 2025-08-21 16:56:26+00:00
I built a little solution to record and transcribe all of my own meetings. I have many meetings (30hr week+) and I can't keep pace with adequate note-taking while participating in them all.

I'm finding that the summarization of individual meetings very useful, I'm also finding that the ability to send in transcripts across meetings, departments, initiatives whatever to be very effective at surfacing subtexts and common pain points much more effectively than I can.

I'm also using it to look at my own participation in meetings to help me see how I interact with others a (little) bit more objectively and it has helped me find ways to improve. (I don't take its advice directly lol, just think about observations and determine myself if it's something that's important and worth thinking about)
by JumpCrisscross | 2025-08-21 16:56:32+00:00
“the government's rollback of energy subsidies, which previously made electricity more affordable. Pakistan made these subsidy reforms in recent years because of loan requirements from the International Monetary Fund, or IMF”

A pretty solid statement of success for IMF policy.

“In June, the government also announced a 10% tax on imported solar panels into Pakistan — almost all of which come from China.”

Dumb fucks.
by doorhammer | 2025-08-21 16:56:34+00:00
Not the op, but I did work supporting three massive call centers for an f500 ecom.

It's 100% plausible it's busy work but it could also be for: - Categorizing calls into broad buckets to see which issues are trending - Sentiment analysis - Identifying surges of some novel/unique issue - Categorizing calls across vendors and doing sentiment analysis that way (looking for upticks in problem calls related to specific TSPs or whatever) - etc

False positives and negatives aren't really a problem once you hit a certain scale because you're just looking for trends. If you find one, you go spot-check it and do a deeper dive to get better accuracy.

Which is also how you end up with some schlepp like me listening to a few hundreds calls in a day at 8x speed (back when I was a QA data analyst) to verify the bucketing. And when I was doing it everything was based on phonetic indexing, which I can't imagine touching llms in terms of accuracy, and it still provided a ton of business value at scale.
by rapind | 2025-08-21 16:57:05+00:00
I suspect there's a lot of nuance you can't really capture in a study like this.

How you use AI will depend on the model, the tools (claude-code vs cursor vs w/e), your familiarity and process (planning phases, vibe coding, etc.), and the team size (solo dev versus large team), your seniority and attention to detail, and hard to measure effects like an increased willingness to tackle harder problems you may have procrastinated on otherwise.

I suspect we're heading to a plateau. I think there's a ton of polish that can be done with existing models to improve the coding experience and interface. I think that we're being massively subsidized by investors racing to own this market, but by the time they can't afford to subsidize it anymore, it'll be such a commodity that the prices won't go up and might even go down regardless of their individual losses.

As someone who knows they are benefitting from AI (study shmuddy), I'm perfectly fine with things slowing down since it's already quite good and stands to be much better with a focus on polish and incremental improvements. I wouldn't invest in these AI companies though!
by recallingmemory | 2025-08-21 16:57:07+00:00
Yeah, I am in the opposing camp too - I don't use Cloudflare's bot fight tooling on any of our high traffic websites. I'm not seeing the issue with allowing bots to crawl our websites other than some additional spend for bandwidth. Agent mode is pretty powerful when paired with a website that cooperates, and if people want to use AI to interact with our data then what's wrong with that?
by dpc_01234 | 2025-08-21 16:57:08+00:00
FWIW. Claude Code does great job for me on complex domain Rust projects, but I just use it one relatively small feature/code chunk at the time, where oftentimes it can pick up existing patterns etc. (I try to point it at similar existing code/feature if I have it). I do not let it write anything creative where it has to come up with own design (either high-level architectural, or low level facilities). Basically I draw the lines manually, and let it color the space between, using existing reference pictures. Works very, very well for me.
by Spivak | 2025-08-21 16:57:18+00:00
Why wouldn't it, once you actually have that project you have the raw audio to generate the transcripts. Only spend the money at the last second when you know you need it.

Edit: Tell me more how preemptively spending five figures to transcribe and summarize calls in case you might want to do some "data engineering" on it later is a sound business decision. What if the model is cheaper down the road? YAGNI.
by bakuninsbart | 2025-08-21 16:57:19+00:00
It is tough though, I'd like to think I learnt how to think analytically and critically. But thinking is hard, and often times I catch myself trying to outsource my thinking almost subconsciously. I'll read an article on HN and think "Let's go to the comment section and see what the opinions to choose from are", or one of the first instincts after encountering a problem is googling and now asking an LLM.

Most of us are also old enough to have had a chance to develop taste in code and writing. Many of the young generation lack the experience to distinguish good writing from LLM drivel.
by WaltPurvis | 2025-08-21 16:57:22+00:00
My go-to grocery store does not use a scale in the bagging area. You don't even have to bag anything, you can just scan items and put them back in your cart, which is what I normally do. There is one employee standing there monitoring 7 or 8 self-checkouts, but they've never confronted me about allegedly not scanning something, and I've never heard them confronting anyone else.

Another nearby mega-chain still uses the scales and makes you bag every item before you can scan anything else. I don't ever shop there, almost entirely for that reason alone. I would definitely never knowingly shop at a store that was scanning my face and storing it in a database.
by beart | 2025-08-21 16:57:26+00:00
But... that is the actual job. A clear medical history is very important, and I'm not ready yet to cut out my doctor from that process.

This reminds me of the way juniors tend to think about things. That is, writing code is "the actual job" and commit messages, documentation, project tracking, code review, etc. are tedious chores that get in the way. Of course, there is no end to the complaints of legacy code bases not having any of those things and being difficult to work with.
by twic | 2025-08-21 16:57:33+00:00
Depends on the index. The usual ones are indeed market cap weighted, and so adopt the overvaluation of bubble stocks, but there are indexes which are weighted otherwise, in an attempt to avoid that. One example is the RAFI fundamental family of indexes:

https://www.rafi.com/index-strategies/rafi-fundamental-indic...

They are pretty cagey about the exact formula, but they do say that

> Security weights are determined by using fundamental measures of company size (adjusted sales, cash flow, dividends + buybacks, and book value) rather than price (market cap).

The top ten holdings in their US index are (rank - company - weight):

1 Apple 4.1 2 Microsoft 3.4 3 Alphabet 3.3 4 Berkshire Hathaway 2.3 5 Amazon 2.2 6 Meta Platforms 2.2 7 JPMorgan Chase 2.1 8 Exxon Mobil 2.0 9 Bank Of America 1.4 10 Chevron 1.3

Whereas those of their benchmark, the Solactive GBS United States Large & Mid Cap Index, whatever that is, are:

1 Nvidia 7.1 2 Microsoft 7.0 3 Apple 5.7 4 Amazon 4.0 5 Alphabet 3.7 6 Meta Platforms 3.1 7 Broadcom 2.4 8 Tesla 1.7 9 JPMorgan Chase 1.5 10 Eli Lilly 1.3