MurphyA/hacker-news huggingface dataset:
by rpdillon | 2025-08-05 15:07:56+00:00
It's in no way "basically open source", and the list strikes me as completely impartial. You cite Sentry, which says this on their licensing page:

> All components powering the main Sentry and Codecov web apps use FSL, which limits their usage in a commercial Sentry-like offering.

The license limits usage in a commercial context. That's not FOSS by the OSI's definition, which is the definition I care about.

Heck, you can tell from the URL that Sentry _really_ wants to pretend they are open source.

https://open.sentry.io/licensing/
by tnlogy | 2025-08-05 15:08:26+00:00
Someone seems to have saved my old self-compiling scheme-to-c compiler in about 1k lines of scheme code. https://github.com/veqqq/llvm_scheme/blob/main/compile.ccode... (also an llvm version)

Maybe I should read and compare it. Mine was a really slow Poc to inspired by SICP, is that book still used in courses somewhere?
by account42 | 2025-08-05 15:08:29+00:00
> If we talk about Anubis, it's pretty invisible. You wait a couple of seconds in the first visit, and don't get challenged for a couple of weeks, at least. With more tuning some of the sites using Anubis work perfectly well without ever seeing Anubis' wall while stopping AI crawlers.

It's not invisible, the sites using it don't work perfectly well for all users and it doesn't stop AI crawlers.
Ask HN: Can you take your AI's memory with you?
by Manik_agg | 2025-08-05 15:08:29+00:00
You use ChatGPT, Claude, Gemini, and Grok for writing, coding, and research. But none of them know what the others learned about you. This is today's reality: your AI memory is vendor-locked.

Currently, only Cursor, Grok, and ChatGPT have memory capabilities, with more following soon. But even when all AI systems develop individual memory, this problem will still exist.

I believe we need an independent 3rd party memory layer for the AI systems, one that can share context with any AI app or agent you use.

Many people on X are already discussing this memory layer problem. Some are building memory MCPs that connect to various providers, but this only partially solves the issue since it's not deeply integrated with these systems.

An open standard for memory should

- Adds context in your memory from everywhere (pdfs, webpage, blogs, linear, notion, document, meetings etc.) - Enable seamless context recall in any AI app you use - No more vendor lock-in, you own your personal memory

Do you think your AI memory should be owned by you, or should it remain vendor-locked with each platform?

Disclaimer - I am building one of such 3rd party memory layer called CORE (https://github.com/RedPlanetHQ/core) hence it is important for me to understand how you folks see about memory ownership.
by MarkusQ | 2025-08-05 15:08:54+00:00
> First AI thing that’s made me feel a bit of derealization…

> …and this is the worst the capabilities will ever be.

I guess if this bothers you (and I can see how it might) you can take some small comfort in thinking that (due to enshitification) this could in fact be the _best_ the capabilities will ever be.
by gchamonlive | 2025-08-05 15:08:56+00:00
> This is why when we look at animals in nature, which don’t have capitalism, they’re all getting along, right? Never competing for anything, fighting each other, or battling for mates?

Even if this was true, humans aren't subjective to their base instincts and can adapt and reinvent themselves.

> Being competitive is human nature.

I'm not and I'm human.

> People will always compete for things

Sometimes you want something, but you let others have it when they need it more than you. Otherwise if you always compete for things you are just a little kid.

> This belief that we just need to come up with an alternate economic system that makes everybody stop trying to do trade and then suddenly everyone’s behaviors will change is also a fantasy. Even within a system where everyone is hypothetically taken care of, you would still see competition over prestige, accomplishments, and coveted positions (even if they paid the same).

This is a misunderstanding of what I said. If you read back I never said competition should be tossed out of the window, it's just that caring for the other as it is right now it's not a core value of the economic system. It's just best effort, if we can say that to the eventually charitable billionaire.
by Swizec | 2025-08-05 15:09:09+00:00
> Somewhere between these two extreme cases, writing with LLMs have the optimal productivity gains.

A recent win for me has been to use LLMs for finding references. I’ll write a paragraph about one of those “everyone knows this” concepts or a “I’ve seen this be true dozens of times IRL”. But it could use a citation.

So you go “Hey LLM, find me papers that support or refute this claim <paragraph>”. And it does. With links. It’s wonderful. Unlike Google there’s no recency bias, I’ve found original source blogs from 2005 (since requoted lots in SEO spam), papers about software engineering truths from the 1960’s (requoted ad nauseam by SEO spam), and sometimes even “Here are 2 papers that say you’re right and 3 papers that say you’re not”. Then I get to dig in and figure out who’s right.

Easily 10x faster than doing the research myself.
by Bukhmanizer | 2025-08-05 15:09:10+00:00
I’ve mentioned this elsewhere, but I think a better question is: do you find AI makes your coworkers N times better.

It makes everyone “produce more code” but your worst dev producing 10X the code is not 10X more productive.

There’s also a bit of a dunning Kruger effect where the most careless people are the most likely to YOLO thousands of lines of vibecode into prod. While a more meticulous engineer might take a lot more time to read the changes, figure out where the AI is wrong, and remove unnecessary code. But the second engineer would be seen as much much less productive than the first in this case
by imtringued | 2025-08-05 15:09:14+00:00
Don't you think that your book suggestions in the last paragraph are oddly focused on a niche branch of internet economics, one that happens to be particularly popular in the US and not particularly popular in Germany or Austria where they geographically originated from?

One would think that a discussion about teaching teenagers would focus on teaching them a broader view instead of tunneling them in one specific direction that happens to antagonize socialism and then only at the end teach them about socialism. That sounds eerily close minded.

I have different reasons for disliking socialism, reasons that are far more banal and simple to understand that don't even involve economics. I don't need an "economic calculation problem" that applies against market economies just as much as it does against socialism, etc.

The funniest part about Austrian economics is that Austrians (the nation and their people) practiced Austrian economics all the way until the beginning of world war two, at which point the Austrian economists got kicked out by an Austrian and fled to the US.
by praptak | 2025-08-05 15:09:31+00:00
No, it doesn't solve the actual problem which is both: a) "conveniently pay for whatever is legal" and b) "have some recourse if someone takes my money and doesn't send me anything".

You may argue that current payment processors do a poor job at b) but they do an infinitely better job than crypto since it's a division by zero situation.
by eythian | 2025-08-05 15:09:33+00:00
In my (limited) experience, programming classes, especially intro level, often end up with a binomial-ish distribution anyway. I was casually assisting some research on why this is when I was helping teach labs and such so was interested. I'm sure more research happened after I wasn't doing that any more, but I remember the best way of removing this at the time was catchup classes.

A lot of intro programming builds directly on previous lessons, much more so than, e.g., maths. If you missed how variables work (off sick, just didn't get it, whatever), you're still stuck when it comes to functions and anything else following and then you're going to fail - it was quite predictable. We studied other university courses and nothing came close to the pattern we were seeing, except "computing for chemistry" or something, which was basically the same sort of course just in a different department.

So we added explicit catch-up classes a few days after a topic was covered so if you missed it, you could get quite personal help on getting back up to speed. This really shifted the distribution to the right, then the people who failed were either those who just didn't care, or those under more extreme circumstances where this couldn't help (or those who just could not learn programming for love nor money but that was rare ime.)
by bayindirh | 2025-08-05 15:09:37+00:00
> I can go to the cinema and watch a movie, then come on this website and describe the whole plot. That isn't copyright infringement.

This is a false analogy. A correct one would be going to a 1000 movies and creating the 1001th movie with scenes cropped from these 1000 movies and assemble it as a new movie, and this is copyright infringement. I don't think any of the studios would applaud and support you for your creativity.

> But it is wrong-headed (and actually wrong in fact) to try to say someone may or may not use my content for some purpose because it hurts my feelings or it messes with my ad revenue.

Why does it have to be always about money? Personally it's not. I just don't want my work to be abused and sold to people to benefit a third party without my consent and will (and all my work is licensed appropriately for that).

> We should not have laws that say, yes you can read my site but no you can't use it to train an LLM, or to build a search index.

This goes both ways. If big corporations can scrape my material without asking me and resell it as an output of a model, I can equally distill their models further and sell it as my own. If companies can scrape my pages to sell my content as theirs, I can scrape theirs and unpaywall them.

But that will be copyright infringement, just because they have more money. What angers me is "all is fair game because you're a small fish, and this is a capitalist marketplace" mentality.

If companies can paywall their content to humans that don't pay, I can paywall AI companies and demand money or push them out of my lawn, just because I feel like that. The inverse is very unethical, but very capitalist, yes.

It's not always about money.

P.S.: Oh, try to claim that you can train a model with medical data without any clearance because it'd be unethical to have laws limiting this. It'll be fun. Believe me.
by gh0stcat | 2025-08-05 15:09:54+00:00
I just wanted to throw my 2 cents, I work in IT and in meat processing there is perhaps only one or two software products that does catch-weight processing well due to the time constraints and custom labeling. If you can do that well you stand to gain a lot in that industry. It doesn't look like you guys are focusing on specific industries, but I actually think you can provide an incredible value to real businesses by doing so.
by sergiotapia | 2025-08-05 15:10:05+00:00
Product guys with no technical experience are getting one-shotted by VC dollars making them think they can create projects themselves. It's an admirable goal but will never happen.

Now for senior developers, AI has been tremendous. Example: I'm building a project where I hit the backend in liveview, and internally I have to make N requests to different APIs in parallel and present the results back. My initial version to test the idea had no loading state, waiting for all requests to finish before sending back.

I knew that I could use Phoenix Channels, and Elixir Tasks, and websockets to push the results as they came in. But I didn't want to write all that code. I could already taste it and explain it. Why couldn't I just snap my fingers?

Well AI did just that. I wrote what I wanted in depth, and bada bing, the solution I would have written is there.

Vibe coders are not gonna make it.

Engineers are having the time of their lives. It's freeing!
by ollin | 2025-08-05 15:10:43+00:00
This is very encouraging progress, and probably what Demis was teasing [1] last month. A few speculations on technical details based on staring at the released clips:

1. You can see fine textures "jump" every 4 frames - which means they're most likely using a 4x-temporal-downscaling VAE with at least 4-frame interaction latency (unless the VAE is also control-conditional). Unfortunately I didn't see any real-time footage to confirm the latency (at one point they intercut screen recordings with "fingers on keyboard" b-roll? hmm).

2. There's some 16x16 spatial blocking during fast motion which could mean 16x16 spatial downscaling in the VAE. Combined with 1, this would mean 24x1280x720/(4x16x16) = 21,600 tokens per second, or around 1.3 million tokens per minute.

3. The first frame of each clip looks a bit sharper and less videogamey than later stationary frames, which suggests this is could be a combination of text-to-image + image-to-world system (where the t2i system is trained on general data but the i2w system is finetuned on game data with labeled controls). Noticeable in e.g. the dirt/textures in [2]. I still noticed some trend towards more contrast/saturation over time, but it's not as bad as in other autoregressive video models I've seen.

[1] https://x.com/demishassabis/status/1940248521111961988

[2] https://deepmind.google/api/blob/website/media/genie_environ...
by shortformblog | 2025-08-05 15:10:47+00:00
It’s up to them how they spend their money, not you. You can complain if they somehow damaged your product, they got your money unfairly, or were somehow doing something bad with your data, but at some point it is their money to spend how they see fit. They earned it, and they might spend it on advertising.

If I buy stuff at a grocery store, I can’t get a random bagger fired just because I feel like it. At some point the transaction ends and they ultimately continue to operate with or without your input.
by swader999 | 2025-08-05 15:10:56+00:00
This was the best insight in the article: Do 10x engineers actually exist? "This debate isn't something I want to weigh in on but I might have to. My answer is sometimes, kinda. When I have had engineers who were 10x as valuable as others it was primarily due to their ability to prevent unnecessary work. Talking a PM down from a task that was never feasible. Getting another engineer to not build that unnecessary microservice. Making developer experience investments that save everyone just a bit of time on every task. Documenting your work so that every future engineer can jump in faster. These things can add up over time to one engineer saving 10x the time company wide than what they took to build it."

So true, a lot of value and gains are had when tech leads can effectively negotiate and creatively offer less costly solutions to all aspects of a feature.
by Glyptodon | 2025-08-05 15:11:08+00:00
I don't consider myself a 10x engineer. The number one thing that I've realized makes me more productive than other engineers at my company is thinking through system design and business needs with patterns that don't take badly written product tickets literally.

What I've seen with AI is that it does not save my coworkers from the pain of overcomplicating simple things that they don't really think through clearly. AI does not seem to solve this.
by 4b6442477b1280b | 2025-08-05 15:11:09+00:00
>And no human is so worthless as to be replaceable with a machine.

did the author oversleep the past several centuries?

as for the rest of it, the current crop of LLMs are bad at writing because of ~~brainwashing~~ alignment and the vast amount of ESL-written assistant exchanges being heavily prioritized during training. when you interact with a corporate model via its default chat interface, without a jailbreak and a generous prefill, you interact with the equivalent of a HR lady who takes her DEI training super seriously. the Chinese models train heavily on the slop produced by GPT/Claude/Gemini, so they exhibit similar behavior. it was particularly noticeable with original llama, whose base models were much more human compared to the finetunes, which were heavily tainted with GPT slop.

I guess what I'm trying to say is that LLMs are not inherently incapable of writing well. a model trained only on high-quality human data and without safety/alignment brainwash will be far, far more capable than the current ones.
by dragontamer | 2025-08-05 15:11:14+00:00
I've been following this protest for a bit out of curiosity (because I really do think Visa/Mastercard is problematic).

But almost all the Reddit posts or Tweets I've seen are about Visa call centers or Mastercard call centers. The number of people protesting Stripe is miniscule in comparison (if there even is anyone to begin with).
by gchamonlive | 2025-08-05 15:11:17+00:00
> Capitalism will destroy the world, but unspecified alternative which doesn’t exist and isn’t described is better. Anyone who doesn’t believe in the non-existent superior non-capitalistic that solves everyone is the bad person, right?

And this is the classic positivist rethoric that prevents self assertion and self criticism. Every doctrine that can't take criticism and take care of it's flaws while maintaining it's benefits is doomed to fail.

Nobody is saying that you are bad in essence, that is the whole idea. There is no essence. You create the meaning you see in the world.
by mgfist | 2025-08-05 15:11:23+00:00
My biggest takeaway from using AI is that

(1) for my day job, it doesn't make me super productive with creation, but it does help with discovery, learning, getting myself unstuck, and writing tedious code.

(2) however, the biggest unlock is it makes working on side projects __immensely__ easier. Before AI I was always too tired to spend significant time on side projects. Now, I can see my ideas come to life (albeit with shittier code), with much less mental effort. I also get to improve my AI engineering skills without the constraint of deadlines, data privacy, tool constraints etc..
by raesene9 | 2025-08-05 15:11:50+00:00
(speaking at least for myself) I'm not suggesting this is a good outcome, more that having seen the way many companies handle development and IT, it's quite a likely one.

FWIW I'd agree that (for now at least) it's challenging to get LLM/AI created code to avoid security vulnerabilities without careful prompting and review. Whether that's a fixable problem or whether it'll just generate mountains of new CVEs, bug bounties and ransomware attacks, remains to be seen.
by bgwalter | 2025-08-05 15:11:59+00:00
That bar is industry standard in the hype machine. Altman and others have set it:

https://www.windowscentral.com/software-apps/sam-altman-ai-w...

https://brianchristner.io/how-cursor-ai-can-make-developers-...

https://thenewstack.io/the-future-belongs-to-ai-augmented-10...
by coltonv | 2025-08-05 15:12:00+00:00
> Wait, now you're saying I set the 10x bar? No, I did not.

I distinctly did not say that. I said your article was one of the ones that made me feel anxious. And it's one of the ones that spurred me to write this article. I demonstrated how your language implies a massive productivity boost from AI. Does it not? Is this not the entire point of what you wrote? That engineers who aren't using AI are crazy (literally the title) because they are missing out on all this "rocket fuel" productivity? The difference between rocket fuel and standing still has to be a pretty big improvement.

The points I make here still apply, there is not some secret well of super-productivity sitting out in the open that luddites are just too grumpy to pick up and use. Those who feel they have gotten massive productivity boosts are being tricked by occasional, rare boosts in productivity.

You said you solved hallucinations, could you share some of how you did that?
Show HN: Orator – AI speech analysis using the 5 Ps framework (completely free)
by orator2025 | 2025-08-05 15:12:38+00:00
I built Orator after realizing most speech analysis tools only count filler words, missing the core elements that actually make speakers effective.

*The technical approach:* Instead of basic word counting, Orator analyzes five dimensions based on communication research: - *Pitch:* Time & frequency-domain analysis for vocal variety detection and monotone identification - *Pause:* Silence detection with timing analysis - *Pace:* Real-time WPM calculation with engagement optimization - *Power:* Volume dynamics and emphasis pattern recognition - *Prose:* Readability scoring and linguistic complexity analysis

*Architecture:* AI-based audio processing, real-time visualization with pitch movements and power variations, pause timing charts, and comprehensive analytics dashboard. Frontend using Next.js with Typescript, React and Tailwind, backend Python Flask API and various LLM/AI services

*Why free:* Wanted to democratize access to professional-level speech coaching. No signup required, all advanced features included.

*Demo:* You can analyze famous speeches (e.g. Ellen DeGeneres, Steve Jobs) or upload your own recordings. The visual analytics are surprisingly insightful – you can see quantitatively what you’re good at and what you need to improve.

Try it: https://orator.feynman.ai/

Looking for feedback on the technical approach and whether these analytics actually help people improve. What speech analysis features would be most valuable to the HN community?
by bombcar | 2025-08-05 15:12:47+00:00
People laugh about that, but when you look at when the whole thing was designed and came out, and how much it would have cost to have a "pimped out" system that pushed the limits (if even possible!) it becomes much more reasonable.

Nobody expected this silly machine to be relevant and affecting computing 44 years later!

It came with 16KB of RAM! 640KB would have been 40 times as much - that's the equivalent of a modern laptop (which comes with checks Apple 16GB of RAM) going up to 640GB of RAM.

The original machine had support for two floppies and a tape drive - the first hard drives were in the 5MB for $2000 in 1982 range. That's about $6,700 today.

Even the writings of the day assumed that the IBM PC would last "for a time" like all previous machines had, newer ones would come out on new chips that were completely different. Nobody really expected backwards compatibility and Windows to eat the world.
by yla92 | 2025-08-05 15:13:07+00:00
> The Proxmox VE mobile interface has been thoroughly reworked, using the new Proxmox widget toolkit powered by the Rust-based Yew framework.

First time hearing about Yew (yew.rs). First time hearing about it. Is it like writing frontend code in Rust and compiled to WASM ? Is anyone using it (other than Proxmox folks, of course).
by rpdillon | 2025-08-05 15:13:11+00:00
You don't have to agree, but it doesn't have the same effect.

The reality is the company is releasing software to customers that have no way of using the source code to that software under an open source license. You can claim this is somehow open source because they will eventually be able to use the source code under an open source license, but that doesn't make the software open source today, any more than you can lock someone in jail and claim they're actually free because they'll get out in two years.
by ZeroGravitas | 2025-08-05 15:13:16+00:00
This appears to be ripping off this article, and totally garbling its message in the process:

https://www.weforum.org/stories/2025/07/addressing-northern-...

The original article points to fracking and industry as the key stressors on water in the region.

In general renewables are less water hungry than anything with a steam component.