MurphyA/hacker-news huggingface dataset:
by joshstrange | 2025-05-20 17:51:22+00:00
I'm trying very hard not to be flippant or inconsiderate but I keep coming back to "no job is guaranteed", it never has been, it never will be. I'll couple that with "If you aren't always learning/improving you are falling behind".

> imagine that there are tons of artists out there who just wish they didn't have to spend so much time making their art

I read this as "you are taking away the thing people love to do" but then

> Those jobs are normally a steady livelihood for artists, even if they aren't that interesting.

Maybe you mean "not interesting" to other people (not the artist) but I'm reading this as "Yeah, it's not great but it's a living" which leads me to ask "Which is it? Are they doing it because they love it or because it pays the bills?" (Yes, yes, "porque no los dos").

Maybe it's "completely different" but one of the biggest uses of LLMs (well, at least here on HN) is generating/writing code yet, as a programmer, I have zero worry about losing my job to the LLM. I don't worry for multiple reasons, one, I've used them and seen what they are and are not capable of. Two, they are a great _tool_ but they are not close to replacing the work I or my co-workers do (I've tried). Three, if they start to errode my "edge" then I'll work to hone some other skills and/or move "up" the chain/stack/whatever. If I was an artist/musician then I'd be looking at what LLMs do well and how I can use my skillset to leverage LLMs as tools or start positioning myself for a different role.

Over the span of my career I have worked on all types of different systems. Each time I had to learn (at least enough to be dangerous) something new. If my job didn't consist of this I think I'd find it incredibly dull. I think a lot of "people losing their job to AI" is really disguised firings (similar to how people use layoffs to cut the low performers) and/or misguided execs who will end up walking it back or failing. I'm not even sure if, with our current generation of AIs, that we won't have more employment even with "AI Layoffs", AI creates jobs as well.

Technology moves on, jobs become obsolete, industries are created and destroyed, you have to learn and change or you die, it's as simple as that.
by blackmamoth | 2025-05-20 17:51:49+00:00
Haven't set a limit to how many connections are shown, once all the commands are executing, each result (success/failure) is shown at once. So if you connect to 1000 computers, your shell will be flooded with progress bars first and then the output.

Maybe I should set a limit or let the user set a limit to how many results should be shown once the process is completed. Showing m and n results from the start and end
by quotemstr | 2025-05-20 17:52:02+00:00
This is not a compiler. It is doing no program translation. No register allocation. No parsing. No linking. It in no way resembles a compiler. Not every program that produces an executable file is a compiler just because some programs you may have heard of, like gcc, are in fact compilers.

I wish the JS universe would stop inventing new and wrong names for things.

(That said, this thing is at least using postject for actual insertion of the payload blob into the target executable, and based on its README, postjecth as the good taste to embed data as PE/ELF/Mach-O sections instead (as Bun does) of just YOLOing the attachment with cat.)
by photochemsyn | 2025-05-20 17:52:04+00:00
This approach is very interesting, and one attention-catching datum is that their proposed compound, ripasudil, is now largely out-of-patent with some caveats, via Google Patents and ChatGPT 03:

> 1999 - D. Western Therapeutics Institute (DWTI) finishes the discovery screen that produced K-115 = ripasudil and files the first PCT on 4-F-isoquinoline diazepane sulfonamides. (Earliest composition-of-matter priority. A 20-year term from a 1999 JP priority date takes you to 2019 (before any extensions).

> 2005 - Kowa (the licensee) files a follow-up patent covering the use of ripasudil for lowering intra-ocular pressure. U.S. counterpart US 8 193 193 issued 2012; nominal expiry 11 July 2026. (A method-of-use patent – can block generics in the U.S. even after the base substance expires).

Scanning the vast library of out-of-patent pharmaceuticals for novel uses has great potential for curing disease and reducing human suffering, but the for-profit pipeline in academic/corporate partnerships is notoriously uninterested in such research because they want exclusive patents that justify profits well beyond a simple %-of-manufacturing cost margin. Indeed they'd probably try to make random patentable derivatives of the compound in the hope that the activity of the public domain substance was preserved and market that instead (see the Prontosil/sulfanilimide story of the 1930s, well-related in Thomas Hager's 2006 book "The Demon Under The Microscope).

I suppose the user of these tools could restrict them to in-patent compounds, but that's ludicrously anti-scientific in outlook. In general it seems the more constraints are applied, the worse the performance.

Another issue is this is a heavily studied area and the result is more incremental than novel. I'd like to see it tackle a question with much less background data - propose a novel, cheap, easily manufactured industrial catalyst for the conversion of CO2 to methanol.
by johnisgood | 2025-05-20 17:52:35+00:00
I think your example is different, because we are talking about something that would be only my code, should it not be up to me? And even if it was not feasible right now, someone else would write the code to make it possible, for their own project. Twitter is not your product, you are only using it. And it is also possible to do it, so why not document it? That makes no sense. That is akin to security through obscurity.

Also he said "but also leads to decision paralysis for most users", but it does not have to be the case. Default can be whatever you want.
by dhosek | 2025-05-20 17:52:36+00:00
> he looks like the subject of a modern drivers license photo.

I was reminded of an interview on Fresh Air around 10 years ago or so where a director was talking about going through casting photos looking for people who “looked like“ they belonged in the WWI era. Terry Gross knew exactly what he was getting at (as did I), in that outside of clothes and hairstyle, some people seem to just seem like they belong in different historical contexts (conversely, there are plenty of old portraits of people who see, like they belong more in the 21st century than the 18th).
by hannofcart | 2025-05-20 17:53:23+00:00
From the limited game dev experience I have/had, my recommendation is to introspect whether building the tech is just fun escapism from working on the really hard part of game dev: designing something that's really fun to play.

Building your own engine may "feel" like progress but it isn't. A fun game loop implemented with the most rudimentary frameworks, (or sometimes even pen and paper!) is more valuable than just a fancy custom engine implementation without a fun game mechanic.

Very often I find some friends of mine still in gamedev getting sidetracked by the intellectual stimulation that building tech gives them (because they are programmers) and burn out before they actually design/discover a fun game mechanic that they can actually ship a game with.

All this is ofcourse assuming you want to make money off your game. If you are just having fun with a hobby project or doing it to hone your programming skills, go nuts with the custom game engine code; more power to you!
by chw9e | 2025-05-20 17:53:38+00:00
Think we've got a long time yet for that. We're going to be writing code a lot faster but getting these things to 90-95% on such a wide variety of tasks is going to be a monumental effort, the first 60-70% on anything is always much easier than the last 5-10%.

Also there's a matter of taste, as commented above, the best way to use these is going to be running multiple runs at once (that's going to be super expensive right now so we'll need inference improvements on today's SOTA models to make this something we can reasonably do on every task). Then somebody needs to pick which run made the best code, and even then you're going to want code review probably from a human if it's written by machine.

Trusting the machine and just vibe coding stuff is fine for small projects or maybe even smaller features, but for a codebase that's going to be around for a while I expect we're going to want a lot of human involvement in the architecture. AI can help us explore different paths faster, but humans need to be driving it still for quite some time - whether that's by encoding their taste into other models or by manually reviewing stuff, either way it's going to take maintenance work.

In the near-term, I expect engineering teams to start looking for how to leverage background agents more. New engineering flows need to be built around these and I am bearish on the current status quo of just outsource everything to the beefiest models and hope they can one-shot it. Reviewing a bunch of AI code is also terrible and we have to find a better way of doing that.

I expect since we're going to be stuck on figuring out background agents for a while that teams will start to get in the weeds and view these agents as critical infra that needs to be designed and maintained in-house. For most companies, foundation labs will just be an API call, not hosting the agents themselves. There's a lot that can be done with agents that hasn't been explored much at all yet, we're still super early here and that's going to be where a lot of new engineering infra work comes from in the next 3-5 years.
Show HN: Reflexive AI Intelligence hub replicating deep human investigations
by sabi_soltani | 2025-05-20 17:54:36+00:00
We built Golden Owl because the data that matters to strategy, like leaks, emerging competitors, reputation hits, and regulatory shifts, is scattered and hard to catch in time.

Golden Owl uses a network of AI agents to monitor and analyze data across the open, deep, and dark web. It pulls from non-indexed sources like court filings, breach dumps, sanctions lists, forum threads, and social media. Then it de-duplicates, merges, and ranks everything in real time.

What it does:

Discover: Finds hidden documents, domains, leaks, forum posts, and more from hundreds of OSINT sources.

Analyze: Uses AI to extract entities, map relationships, detect anomalies, and identify trends.

Monitor: Sends live alerts on brand mentions, competitor actions, geopolitical shifts, and supply chain risks.

Compare: Provides side-by-side dashboards for companies, markets, or investments.

Under the hood:

~200 AI agents act like digital investigators at scale.

Custom scrapers + Tor relays for deep/dark web access.

Vector graph store for relationships and clustering.

API with 100+ endpoints offering both raw and enriched data.

All data stays private—no public indexes, no shared queries.

We're live at https://goldenowl.ai

Would love feedback on: Usability and UI Data coverage and freshness Anything you'd expect from an OSINT tool but don't see

Thanks!
by andrewmunsell | 2025-05-20 17:54:49+00:00
> incorrect, its an o3 finetune.

This is Open AI's fault (and literally every AI company is guilty of the same horrid naming schemes). Codex was an old model based on GPT-3, but then they reused the same name for both their Codex CLI and this Codex tool...

I mean, just look at the updates to their own blog post, I can see why people are confused.

https://openai.com/index/openai-codex/

Edit:

Google just did it too. "Gemini Ultra" is both a model (https://deepmind.google/models/gemini/ultra/) and their new top-tier subscription plan (a la Open AI's Pro plan). Why is this so difficult?
by minimaxir | 2025-05-20 17:55:16+00:00
> Diffusion models work differently. Instead of predicting text directly, they learn to generate outputs by refining noise, step-by-step. This means they can iterate on a solution very quickly and error correct during the generation process. This helps them excel at tasks like editing, including in the context of math and code.

This is deliberately unhelpful as it begs the question "why hasn't anyone else made a good text diffusion model in the years since the technology has been available?"

The answer to that question is that unlike latent diffusion for images which can be fuzzy and imprecise before generating the result image, text has discrete outputs and therefore must be more precise, so Google is utilizing some secret sauce to work around that limitation and is keeping it annoyingly close to the chest.
by Konnstann | 2025-05-20 17:55:25+00:00
Depending on your definition of AI, a pipeline for drug repurposing my team used was able to identify a therapeutic for a rare disease that was beating the state of the art in every test they threw at it, eventually being given orphan drug designation by the FDA. I doubt this would have happened without machine learning or AI or whatever you want to call it.

I'm also against "agents as scientists" as a concept for numerous reasons, but deep learning etc has or is leading to breakthroughs.
by dylukes | 2025-05-20 17:55:53+00:00
I've done research involving sampling from all extant notebooks on GitHub and manually analyzing them, and have been a heavy user of them in non-CS research contexts for a long time (and Mathematica notebooks for years before iPython Notebooks grew in popularity).

Having manually sifted through hundreds of randomly sampled notebooks, I feel I can confidently speak on the distribution of characteristics in them, at least up through a couple years ago.

1. Notebooks on GitHub are not necessarily an entirely representative sample of notebooks at large. If the author is putting it on GitHub, there's already a significant selection bias towards certain topics, despite notebooks being used in practically any discipline you can think of at least to some extent.

2. Notebooks in repositories that contain requirements.txt files are a minority and tend to be intended/cleaned up for sharing (itself not the norm).

3. What's more common is just a handful of !pip install at the top.

4. Even more common is just some details on dependencies in an adjoining README.

A very non-trivial chunk of notebooks on GitHub are just copies of the "Hands On ML 3" textbook/exercise set. If my memory serves there are tens of thousands of copies of that one repository. The fork count shown by GitHub doesn't account for the plethora of copies that weren't made using it.
by ogoffart | 2025-05-20 17:56:04+00:00
Off-topic, but the idea of "colored functions" from the "What Color is Your Function" article doesn't apply to Rust's async/await. That article is about JavaScript before it had async/await, when it used callbacks.

In Rust, you can call async functions from normal ones by spawning them on the executor. The .await syntax isn't as painful as dealing with callbacks and closures in JavaScript. Plus, if you call an async function incorrectly, Rust's compiler will catch it and give you a clear error message, unlike JavaScript, where bad function calls could lead to unpredictable behavior. The premises of the article don't apply, so Rust's async/await doesn't introduce the same "colored function" issues.

(See also https://without.boats/blog/let-futures-be-futures/ )
by bunderbunder | 2025-05-20 17:57:20+00:00
Also human subjectivity makes it kind of impossible to do this sort analysis in a systematic way that yields an apples-to-apples comparison. How do you properly account for slang or figurative language in a way that works consistently across languages when every dictionary you might use is maintained by a different group of people with different editorial standards?

And then, yes, agglutination. What's way more interesting to me than how many words Inuktitut or Chinese have for snow is the way the very structure of these languages illustrates how ill-defined a concept "word" is in the first place. You might think you know what it means in English, and that might transfer reasonably well to other Indo-European languages, but as you go further afield you start to see more and more examples where the concept needs heavy modification to remain useful.
by cyberax | 2025-05-20 17:58:07+00:00
Yes, it might be possible, but also expensive. But there just isn't a lot of space available to support both a good tactile feedback, and to be able to interrupt the line voltage. There are requirements for high-low voltage separation that are difficult to meet, while staying within the allowed size for a switch.

Since I'm doing it for myself, I will selfishly just do a low-voltage system :) But I'm seriously considering funding a startup to do engineering for an integrated version.

The closest thing that I found to a _good_ smart dimmer was https://www.alibaba.com/product-detail/Zwave-Zks31-Knob-Dimm... (ZKS-31). It has a physical knob as a control, and it only misses the visual indication of the current state and simulated detents.

I'm really at a loss why nobody else is trying to do something like this, while doing crap like touch-sensitive switches with LED displays.
by yapyap | 2025-05-20 17:58:56+00:00
I don’t wanna be too harsh but I think that learning how to live from deathbed letters, especially the deathbed letters from people who were going to be sentenced to death is utter nonsense.

The letters were going to be checked by the people that were killing you — the nazis in this example — so your letter was never going to be “fuck those utter pigs” or anything resentful of the people that were going to be your murderers because they would just be shredded or burnt or destroyed in some way. So this has a massive impact on the contents of the letters.

Then there’s the unreliability of the narrator on the deathbed, I recently read a beautiful article about this about why you should not take advice from people on their deathbed or from yourself on your deathbed, the inherent bias you have will make you unreliable and the things you value and take for granted on your deathbed will not necessarily have been things you have always had but instead may be things you have worked hard for in your life. [1]

Now that’s not to say their words are nothingburgers but when you have to wholly draw your own conclusions from inherently biased letters it starts to feel like we are all pretending to care more about these words because of the sacredness of death. No one wants to disrespect the dead, no one wants to say “wow, he must have been really losing it at the end” and that’s a given, not to be rude to dead people. That’s like punching down to the first degree. But like even things that would be considered light critiques or nice criticism don’t get to be said about take it or leave it bodies of work from dead people, because they are dead. On the one hand that’s a beautiful thing because let’s not start disrespecting dead people but on the other hand let’s keep it real.

[1] https://www.hjorthjort.xyz/2018/02/21/the-deathbed-fallacy.h...
by ttepasse | 2025-05-20 18:00:59+00:00
Here: https://docs.swift.org/swift-book/documentation/the-swift-pr...

Easter egg: The example is named dogcow, after a 90s Mac icon, designed by Susan Kare, which later became a small mascot: https://512pixels.net/dogcow/

Regarding .length: Effectly that is just the result of Unicode, there is no one-to-one equivalent between characters code points, the code units in an encoding and the resulting grapheme clusters. That is in effect a result of the complexity of the world's alphabets, including Emoji.
by alephnerd | 2025-05-20 18:01:53+00:00
My point is a reserve currency doesn't help the median Chinese in any shape or form, nor does the USD being a reserve currency help the median American.

There are benefits to being a reserve currency at the macro-scale, but they are not felt by the vast majority of households, and any attempts at making the CNY a competitive reserve currency would require dramatically reducing currency controls along with increasing the independence of the PBOC from political leadership, and leave the lower tier of Chinese workers open to job loss and outsourcing [0][1][2][3] as low-to-medium complexity industries remain the primary employment generator in Chinese manufacturing.

This is the exact same thing that happened to Thai, Malaysian, and Mexican manufacturing workers during the 2000s when they hit plateaus similar to China today.

Finally, the US's dominant position is the cause of the USD as a reserve currency, not the other way around [4]. Having a reserve currency is orthogonal to having great power status, as can be seen with the rise of China.

A rising tide lifts all ships - the China story will stagnate if a serious effort at helping the bottom half of Chinese does not develop.

[0] - https://www.degruyterbrill.com/document/doi/10.1515/cfer-202...

[1] - https://www.tandfonline.com/doi/abs/10.1080/13602381.2025.24...

[2] - https://sysengi.cjoe.ac.cn/EN/10.12011/SETP2023-0562

[3] - https://www.nature.com/articles/s41599-024-03797-6

[4] - https://www.ussc.edu.au/the-reserve-currency-myth-the-us-dol...
Show HN: I Made Resend.com Cheaper
by javidabd | 2025-05-20 18:02:38+00:00
Hi HN!

Resend.com is known for its simplicity, but it is quite expensive for marketing emails.

So, I've built selfmailkit.com. It has three types:

- Cloud: Fully managed. Just open an account and start sending - Connect: Bring your own AWS SES and let us handle everything else. It's cheaper and you keep your reputation separate. - Self-Hosted: One-command deployment and manage everything in your own account

Initially, I only started with the self-hosted type but added Connect and Cloud types upon request.
by breppp | 2025-05-20 18:03:02+00:00
I believe that if this would happen in a normal court case this would end in mistrial.

It is not true that this must be in favor of Israel, a criminal that tries to prevent his trial by influencing witnesses, could also try to influence the judges, misrepresent evidence and such, if he thinks moving forward with the trial will save him. There is evidence he pressured the victim precisely on the reason of this trial success, without a trial he will go to jail.

This also raises a question, if there are multiple persons in the supposedly neutral prosecution team including victim and head of prosecution, that believe that ignoring a rape is worth it in order to follow through with a trial against a specific country, so early in the trial, then how do we know that the rest of this organization including judges does not have major prejudices against Israel?

I think that if you take the fact that they completely ignored the principle of complementarity, claiming essentially Israel does not have an independent judiciary system, when said judiciary system is prosecuting Nethanyahu currently for a different crime while upping the irony when half of the ICC judges come from countries with actually non-functioning judiciary systems

Then add to it the fact that they passed through a highly creative way of interpreting their jurisdiction, while ignoring the chance for the accused to plea and ending that with highly unusual arrest warrants against a current head of state, whose process is criticized by the very same court a year later. Then you get something that looks bad, at least to me