MurphyA/hacker-news huggingface dataset:
Show HN: I built a website to roast hilarious AI conversations
by jeylau | 2025-06-18 13:53:29+00:00
Hey HN,

After reading Sam Altman's post on the gentle singularity last week, I built Zonk — a simple site for sharing and roasting weird, absurd, or funny AI conversations. Users can: * Upload screenshots of AI chats * Tag them by model/topic * Comment and vote * Browse a “Silicon Hall of Shame" leaderboard to track which models confidently delivers the most nonsense. The stack is React + TypeScript + Supabase. No AI models involved, nothing fancy, just a clean archive of AI absurdity. It's meant to be light, searchable, and a bit of a time capsule before the singularity hits and GPT-7 shows up and asks why we were so mean to its ancestors. Hope it gives you a laugh or two!
by skerit | 2025-06-18 13:53:55+00:00
> I don’t think I’ve encountered a case where I’ve just let the LLM churn for more than a few minutes and gotten a good result.

Is this with something like Aider or CLine?

I've been using Claude-Code (with a Max plan, so I don't have to worry about it wasting tokens), and I've had it successfully handle tasks that take over an hour. But getting there isn't super easy, that's true. The instructions/CLAUDE.md file need to be perfect.
by onlyrealcuzzo | 2025-06-18 13:54:20+00:00
> If it doesn’t solve an issue on the first or second pass, it seems to rapidly start making things up, make totally unrelated changes claiming they’ll fix the issue, or trying the same thing over and over.

Sounds like a lot of employees I know.

Changing out the entire library is quite amusing, though.

Just imagine: I couldn't fix this build error, so I migrated our entire database from Postgres to MongoDB...
by sebstefan | 2025-06-18 13:54:43+00:00
>the same argument is being made against right to repair and having spare parts available

Just as valid back then. There's nothing wrong with the argument. You have to evaluate it every time. For right to repair we just decided it was worth it.

I don't think this is worth it. A few months to dl your stuff is enough. Companies shouldn't need to host things that go against their terms of service when they ban you for infringing on their terms of service. It would be nonsense.
by wongarsu | 2025-06-18 13:54:55+00:00
It helps that in most cases when people make a zip the compression is a secondary feature. What people want 90% of the time is a container format to put multiple files or a whole folder structure into one file. .zip or .tar.gz do this just fine, even if their compression factor and speed aren't that great by modern standards.

Same with jpeg: Most people want to just encode images, reducing file size by 10% is a negligible win for most people
by apgwoz | 2025-06-18 13:56:00+00:00
> We chose the Tiger back in April 2017.

Fair. But a mascot is not a name. I hope you can see why I bring this up?

> Also TigerBeetle is an insect, not a fast cat.

It is? Damn. I thought a Tiger Beetle was a six foot long cat wearing costume wings and a springs for antennae?
by fredrikholm | 2025-06-18 13:56:02+00:00
The worst part of stories like this is how much potential there is in gaslighting you, the negative person, on just how professional and wonderful this solution is:

* Information hiding by exposing a closed interface via the API * Isolated, scalable, fault tolerant service * Iterable, understandable and super agile

You should be a team player isophrophlex, but its ok, I didn't understand these things either at some point. Here, you can borrow my copy of Clean Code, I suggest you give it a read, I'm sure you'll find it helpful.
by jerf | 2025-06-18 13:56:17+00:00
The accusations that politicians are already overusing AI are flying, and given the incentives I wouldn't be surprised more of the internal functioning of all modern governments are already more LLM-based AI than we'd realize. Or particularly appreciate.

By that I don't mean necessarily the nominal function of the government; I doubt the IRS is heavily LLM-based for evaluating tax forms, mostly because the pre-LLM heuristics and "what we used to call AI" are probably still much better and certainly much cheaper than any sort of "throw an LLM at the problem" could be. But I wouldn't be surprised that the amount of internal communication, whitepapers, policy drafts and statements, etc. by mass is probably already at least 1/3rd LLM-generated.

(Heck, even on Reddit I'm really starting to become weary of the posts that are clearly "Hey, AI, I'm releasing this app with these three features, please blast that out into a 15-paragraph description of it that includes lots of emojis and also describes in a general sense why performance and security are good things." and if anything the incentives slightly mitigate against that as the general commenter base is starting to get pretty frosty about this. How much more popular it must be where nobody will call you out on it and everybody is pretty anxious to figure out how to offload the torrent-of-words portion of their job onto machines.)
by plopilop | 2025-06-18 13:56:58+00:00
As the article mentions, fully homomorphic encryption is insanely slow and inefficient. But I have to say that it is a relatively new field (the first FHE scheme was discovered in 2009), and that the field has immensely progressed over the last decade and a half.

The first FHE scheme required keys of several TB/PB, bootstrapping (an operation that is pivotal in FHE schemes, when too many multiplications are computed) would take thousands of hours. We are now down to keys of "only" 30 MB, and bootstrapping in less than 0.1 second.

Hopefully progress will continue and FHE will become more practical.
by Zigurd | 2025-06-18 13:57:00+00:00
One could even be excused for the paranoid thought that there's a conspiracy of capital backing techno authoritarians. Of course, some of that is a money maker, like surveillance tech. But these are the same people backing dodgy brain implants, and third rate LLMs at fabulous valuations. And who are OK with merging a dying social media site with that third rate LLM start up.
by jrmg | 2025-06-18 13:57:04+00:00
It’s not just new frameworks, it’s new features. Good luck getting a LLM to write code that uses iOS 26 features, for example.

I’m not convinced simply getting the LLM to inject documentation about the features will work well (perhaps someone has studied this?) because the reason they’re good at doing ‘well known’ things is the plethora of actual examples they’re trained on.
by eadmund | 2025-06-18 13:57:08+00:00
I wrote in a sibling comment ‘I do get it — no-one owes me anything.’ No-one should be forced to do anything. Folks are and should be free to work on whatever suits their fancy.

But folks should also have a sense of duty or responsibility not to needlessly interfere with others. I am free to release a reïmplementation of ls(1). I’m free to extend it. But I shouldn’t change the meaning of ‘ls -d’ to delete all matching files, because it conflicts with POSIX. I shouldn’t change the meaning of ‘ls -b’ to overwrite matching files with nulls (blanks), even though POSIX doesn’t define it at all and in theory I am free to do so, because GNU ls(1) already uses it for printing C-style escapes.
by haswell | 2025-06-18 13:57:35+00:00
Can’t be done. That’s not how human brains work, and there’s no neurological basis for the claim that it is possible.

Look, this has come full circle and we’re both just restating our positions at this point.

If you’re not just trolling, I’d highly recommend you go read some of the criticisms of Hegel’s work.

You keep dismissing/side stepping the counterpoints raised here without providing substantive arguments to back up this dismissal, so I’ll leave it there.
by Nevermark | 2025-06-18 13:57:52+00:00
> We have had full AGI for years now

Models still have extreme limits relative to humans. Context size and reasoning depths, being the two most obvious. A third being their inability to incorporate new information with as little effort as humans do, without creating unintended conflicts across previously learned information.

But they vastly exceed human capabilities in other ways. The most obvious, being their ability to do shallow reasoning incorporating information from virtually any combination out of the vast number of topics that humans find useful or interesting. Another being their ability to by default produce discourse with such high written organization and grammatical quality.

For now, they are artificial "better at different things" intelligences.
by bryanlarsen | 2025-06-18 13:58:25+00:00
Remember that a big battery car is really good at averaging out intermittent usage. If you're plugging into a standard outlet which can only add 40 miles a night, you'll almost always be OK if you average less than 40 miles a day. The occasional 100+ mile day is fine as long as you average less than 40. Only if you need several consecutive 100+ mile days will you need to resort to a DC level 3 charger.
by LostMyLogin | 2025-06-18 13:59:33+00:00
Hesitating to write this because I don't want to push back at all on OP but I'm not sure I agree that something like this is a good option for people wanting to get started in weightlifting. I'm not sure it's a good option for anyone really. I applaud OP for the effort but this is recommending some pretty awful workouts. For example if I select back and bi, it's giving me nine different exercises with complete disregard for the order they are in or what other exercises are in the workout.

Why are compound lifts in the middle of the workout and why am I doing three different types of chin ups? There are also no reps / sets calculated nor are there 1RM percentages for weight.

Bro splits are some of the lowest quality routines you can use and this somehow makes them worse. You could replace all of this, remove the bells and whistles, and create a bare bones PPL app that determines exercises based on equipment available and it would be light years better than this.
by jeroenhd | 2025-06-18 13:59:33+00:00
I think mentioning that IPv6 makes NAT unnecessary for most use cases is more than enough.

Of course, NAT still exists in IPv6. It probably shouldn't, but tools like Docker will assign a full /64 to your local network even on systems like VPS servers where you only have a /112 or smaller available to you. Plus, NPT is a type of NAT that just happens to switch only part of the address around, you still need to mangle checksums and such.

Most people could probably get away with Docker using your local GUA for addressing and proxying NDP directly (what's that chance your developers are actually using 2^64 addresses?) but because of the way Docker interacts with nftables and the way most Linux firewalls work, using NAT is probably easier to maintain safety for.
by msgodel | 2025-06-18 13:59:47+00:00
Real Estate is one of the worst investments available to normal people. The risk premium is near zero while the risk they absorb is massive. Many landlords I know are cash flowing near zero, in some cases negative. I knew that would happen and was telling them a couple years ago but they said it's impossible because "everyone has to live somewhere." Their model of the economy is just so bizarre, like production will just materialize out of nowhere.

They still think it's ok because on paper their assets have appreciated but I think the market is just so iliquid right now they're not able to mark them accurately.
by prmph | 2025-06-18 14:00:03+00:00
> complexity very bad

Oh boy, this is so true. In all my years of software engineering this is one of those ideas that has proved consistently true in every single situation. Some problems are inherently complex, yes, but even then you'd be much, much better off spending time to think things through to arrive at the simplest way to solve it. Again and again my most effective work has been after I questioned my prior approaches and radically simplified things. You might lose some potential flexibility, but in most case you don't even need all that you think you need.

Some examples:

- Now that reasonably good (and agentic) LLMs are a thing, I started avoiding overly complex TypeScript types that are brittle and hard to debug, in favor of writing spec-like code and asking the LLM to statically generate other code based on it.

- The ESLint dependency in my projects kept breaking after version updates, many rules were not sophisticated enough to avoid false positives, and keeping it working properly with TypeScript and VSCode was getting complicated. I switched to Biome.js, and it was simpler and just as effective. However, I'm recently having bugs with it (not sure if Biome itself or the VSCode extension is to blame). But whatever, I realized that linting is a nice-to-have, not something I should be spending inordinate amount of times babying. So I removed it from the build tool-chain, and neither do I even need have it enabled all the time in VSCode. I run Biome every now and then to check the code style and formatting , and that's it, simple.

- Working on custom data migration tooling for my projects, I realized forward migrations are necessary to implement, but backwards migrations are not worth the time and complexity to implement. In case a database with data needs to be rolled back, just restore the backup. If there was no data, or it is not a production database, just run the versioned initialization script(s) to start from a clean state. Simple.
by marcosdumay | 2025-06-18 14:00:17+00:00
> See the target/know which direction it is? Go that direction unless you see an obstacle, in that case go around the obstacle, eventually even backtracking if it turns out the obstacle was worse than you could see. Don't see/know the target? Brownian motion until you do or get tired.

What a long and convoluted way to try to reinvent the A* algorithm...
by dahart | 2025-06-18 14:00:47+00:00
The phrasing is correct and pretty normal, it’s just potentially ambiguous. English is like that sometimes. I’m not a grammarian, but I think “I counted all the yurts in Mongolia using machine learning” would normally be interpreted correctly by most people, with ‘using’ referring to the subject ‘I’. The way you’d write the other interpretation is “I counted all the yurts in Mongolia that use machine learning”. Your proposed alternative is also correct and less ambiguous.
by bloppe | 2025-06-18 14:00:50+00:00
The first part about labor is a bit incoherent. It bemoans the accumulation of wealth by the capital class, then the part on profitability claims that the capital class is actually losing by investing in AI. It also seems to imply that laborers should be entitled to demand for their services. Imagine if your car mechanic wanted to charge you no matter whether your car needed work or not. The lump of labor fallacy is alive and well.

Some good points in the rest of the post.
by bryanlarsen | 2025-06-18 14:01:35+00:00
From what I've read, standard nickel-cobalt lithium ion batteries last longer with lots of little charges to keep the battery at around 60% than they do with less frequent larger charges.

The effect is really minor, though. The important thing is to keep the battery between 20% and 80% as much as possible. Going below 20 or above 80 is the most significant thing that shortens life.
by rurp | 2025-06-18 14:02:01+00:00
This honestly sounds slower than just doing it myself, and with more potential for bugs or non-standard code.

I've had the same experience as parent where LLMs are great for simple tasks but still fall down surprisingly quickly on anything complex and sometimes make simple problems complex. Just a few days ago I asked Claude how to do something with a library and rather than give me the simple answer it suggested I rewrite a large chunk of that library instead, in a way that I highly doubt was bug-free. Fortunately I figured there would be a much simpler answer but mistakes like that could easily slip through.
by a-dub | 2025-06-18 14:02:45+00:00
hmm.. i wonder how it would compare then with clang+linux, clang+stl or hotspot+j2ee.

reminds me a bit of the days when perl programs would often outrun native c/c++ for common tasks because ultimately they had the most efficient string processing libraries baked into the language built-ins.

how is space efficiency? last i checked, because of big libraries and ease of adding them to projects, a lot of rust binaries tend to be much larger than their traditional counterparts. how might this impact overall system performance if this trade-off is made en-masse? (even if more ram is added to counteract loss of vm page cache, does it also start to impact locality and cache utilitization?)

i'd be curious how something like redox benchmarks against traditional linux for real world workloads and interactivity measures.
by haswell | 2025-06-18 14:03:47+00:00
Religious faith is when you take the words and ideas of a man - ideas that are highly controversial and not widely accepted by philosophers or scientists - and then claim with certainty that they are the absolute truth. It’s one thing to find those ideas interesting, but another entirely to bring this kind of absolute certainty.

Hegel’s work could be described as a hypothesis at best, yet you’re treating it as gospel truth despite the fact that most philosophers find his conclusions untenable and most scientists conclude that he couldn’t have had a proper understanding of science to reach the conclusions that he reached.

Your arguments up to this point are indistinguishable from the claims made by the religious folks in my life who say they have the absolute truth because of their belief in the Bible and relationship with Jesus.

Your only defense of Hegel’s work to this point amounts to “I believe it’s true” and have been entirely circular.
by bryanlarsen | 2025-06-18 14:05:11+00:00
I've done a 3000 km trip with kids 4 times in a Tesla. On one trip the Tesla took 15 minutes longer than a gas car would have. Only once did we did we do a small charge with the kids sleeping where we had to wait for the charger. Every other time we spent longer bathrooming or eating or checking out the roadside attraction than we did charging.
by PaulHoule | 2025-06-18 14:05:58+00:00
This was always my mental model. If you have a process with N steps where your probability of getting a step right is p, your chance of success is pᶰ, or 0 as N → ∞.

It affects people too. Something I learned halfway through a theoretical physics PhD in the 1990s was that a 50-page paper with a complex calculation almost certainly had a serious mistake in it that you'd find if you went over it line-by-line.

I thought I could counter that by building a set of unit tests and integration tests around the calculation and on one level that worked, but in the end my calculation never got published outside my thesis because our formulation of the problem turned a topological circle into a helix and we had no idea how to compute the associated topological factor.
by xenophonf | 2025-06-18 14:06:02+00:00
It'd be a lot more accurate—not to say more honest—to say the author _estimated_ the number of all the yurts in Mongolia using machine learning. ML algorithms are stochastic; their outputs are whatever the algorithm deems the most probable of the options generated from the given inputs. They barely give a thought to all the ways their count could be wrong—no error analysis, no confidence intervals. There's a meaningless prediction score of 40%, and they blithely add "a hundred or so" to the count.

This is anti-information. People reading this uncritically will come away with completely wrong ideas about the number of yurts in Mongolia, about machine learning algorithms, about data science in general.
by donatj | 2025-06-18 14:06:15+00:00
We started using AVIFs recently in picture elements with fallback to JPEG, and I'm a pretty big fan. The compression is good, the tooling is decent. They're supported by most things natively.

Browser support for AVIF is nearly good enough that you might not need the fallback in reality. The only real problem I have encountered is that animated AVIFs are super stuttery in Safari for some reason.
Show HN: VeilStream – prod-like data without the PII
by joram87 | 2025-06-18 14:06:36+00:00
# TL;DR We built VeilStream, a drop-in, read-only PostgreSQL proxy that strips, masks, or anonymizes sensitive values as queries stream through. In less than two minutes, you can put a proxy in front of a PostgreSQL database, whether hosted on your laptop, Neon, Supabase, or a cloud provider, and the user is able to start configuring filter rules.

The use cases we're trying to solve are:

- Production-like data in development environments

- Improve incident handling by masking all data that is not relevant

- Share a subset of your data

- Protecting data being shipped into a data lake

- Safe data to expose in internal tooling, metrics, or BI dashboards

- Empower non-technical staff to vibe-code against sanitized data

# How it fits in your stack

- Role based policies: define masking rules in our web dashboard

- The proxy picks up the configuration and starts applying rules automatically.

## You host it

- it's a docker container, two environment variables: an api key, and the database URI connection

## We host it

- Drop-in proxy: no code changes. Point your connection string at a new endpoint, that's it.

# How it works (and how fast it is)

Restructuring the query AST based on the config. AST rewrites depend on the text/structure of the query, not on how many rows the database eventually returns, so they are effectively O(1) with respect to result size.

# Status & feedback wanted

VeilStream is GA, but billing isn’t switched on yet so it's currently free at all tiers. We’d love your thoughts on:

- throughput / latency in real workloads

- Filter rules & DevX

- weird edge-case queries (pg_dump, logical replication, etc.)

I’ll be around all day to answer questions and dig into issues.

# tagline

Ship features with data you can trust and privacy you don't have to worry about.
by chasil | 2025-06-18 14:06:54+00:00
This is in queue, will update with final URL if successful.

Edit: This just jumped from #7 in queue to #2380 in queue. I should have used another service.

https://archive.ph/wip/hOIIa

If/when it completes, it should be here:

https://archive.ph/hOIIa
by arghwhat | 2025-06-18 14:07:10+00:00
> Where did your [...] go?

That statement is both still there in its entirely unchanged form, and still entirely true - quoting the comment as it appears on my screen right now, long after any edit window closed:

> but it's easy for others to read this and conflate "problems with application's Wayland support" as "problems with Wayland"
by minimalist | 2025-06-18 14:07:11+00:00
It does not appear to be working for me right now, I get "error loading exercises".

What are your thoughts about the wger project [0]? It is a FLOSS AGPL-licensed self-hosted fitness/workout/nutrition manager that has existed for almost a decade (I think?) It's a django app and has a companion flutter app that runs on android/ios/windows/linux/macos. It supports multiple users and could even be used to run a gym. Body.build [1] is a newer FLOSS project (also browser-based) that is focused around building a weight lifting program. The author of body.build also contributes to wger.

I'm using wger in my homelab and while there are a lot of moving pieces to the self-host process, it works well. I'd say the biggest limitation is the comprehensiveness of their exercise database, but that is something that many people have recognized and are steadily expanding. If anyone is willing to contribute exercises (and exercise media) to this AGPL licensed project, they would definitely appreciate it!

[0]: https://github.com/wger-project

[1]: https://github.com/Dieterbe/body.build