MurphyA/hacker-news huggingface dataset:
by azemetre | 2025-06-11 16:49:52+00:00
I live in Boston where I make double(-ish) the household median income ($80k to $100k). For individual median incomes, I make $140k more. I'm able to save over half my monthly income and it's still not enough. I absolutely can't imagine living in this city on anything less and I don't exactly live a life of exuberance here.

This is the sign of a broken economy.
by JohnFen | 2025-06-11 16:52:08+00:00
True, but I think his point is that where there's a negotiation happening (which is what deciding where to eat is), just saying "no" isn't that helpful. More helpful is to say why you're saying "no" so that the other people can formulate an alternative proposal that resolves your objection. That back-and-forth is the essence of a successful negotiation.

Boundary-setting is something entirely different in that it's not about negotiations. In those situations, a plain "no" is often the best thing.
by joshavant | 2025-06-11 16:52:28+00:00
I want to build a large format, real-time, physical music visualizer that could orchestrate an artistic light symphony for any song.

I'm imagining physical visualizers that are columns of multiple, discrete light nodes, each able to have variable brightness and color.

The real-time music processing is the hard part (for me) to crack.

There's some standard tricks here: FFTs, bandpass filters, etc.

But I want to do more: Real-time stem separation, time signature and downbeat tracking, etc.

Imagine hearing Sweet Caroline and, when the horns kick in, the whole installation 'focuses' on the horns and bright yellow light jumps between each column on each horn note, before returning to tracking the bass line or something.

I've been noodling on this idea for a long time and slowly digging into the music and CS fundamentals. The rise of LLMs might finally be the piece that enables me to close my intelligence gap and finally build this thing...
by gooseus | 2025-06-11 16:52:39+00:00
The point I was trying to make was that the Sam Altman's of the world make a whole lot of unfalsifiable claims about the nature and capabilities of his AI, while just hand-waving a bunch of things away.

In my merry state last night I didn't do a great job so I'm not surprised by the lack of positive response, though I was kind of hoping some people would catch my drift. Oh well.
by Madh93 | 2025-06-11 16:52:52+00:00
The specific problem prxy solves is not at the network level, but at the application level, especially for tools that don't have built-in proxy settings.

With WireGuard's AllowedIPs, you route all traffic for a certain IP range through the tunnel. My use case was different: I wanted a specific browser extension to connect to my homelab, while my main browser traffic to the public internet remained on my local network. The extension only has a field for a URL, not for proxy settings.

While an SSH tunnel can achieve a similar result, I find prxy more convenient for this specific workflow because:

- It automatically rewrites the Host header, which is crucial when your homelab service sits behind a reverse proxy (like Traefik or Nginx). - It's a simple, declarative command designed for this one purpose, making it easy to script or use in a container.

So, in short: prxy is a user-space tool for application-specific tunneling when the app itself is not proxy-aware.
by AlecSchueler | 2025-06-11 16:53:39+00:00
You might believe that but their past behaviour, plans and reasoning have all been unpredictable and ostensibly irrational so there's really no reason to believe this over anything else. The next person could say they believe he wants to enact martial law, and the next could say it wasn't even an expected outcome.

In fact I bet there would be as many seemingly reasonable beliefs as there would be people willing to comment on it.

The only thing for sure is that we don't know and anyone outside the administration claiming a level of certainty around it is doing nothing more than confabulating.
by bobbiechen | 2025-06-11 16:53:39+00:00
(Author of the post here)

Agreed - I'm pretty skeptical of invasive behavioral data like mouse movements. It feels like a popular meme from an earlier time, jiggle your mouse more before clicking the CAPTCHA checkbox, but in practice it's not a very high-value signal anymore (especially with the rise of mobile). TLS fingerprinting is a significantly more useful signal for us at Stytch.
by vidarh | 2025-06-11 16:53:57+00:00
They could be better, but I don't agree they're nonsensical. The comment is fine as a comment, but when asked to give a literary critique pointing out that the language could be clearer is entirely reasonable.

But this is also besides the point, which is that it is trivial to get these models to argue - rightly or wrongly - that there are significant issues with your writing rather than claim everything is excellent.

Whether you can get critiques you agree are reasonable is another matter.
by littlestymaar | 2025-06-11 16:54:04+00:00
> I'd say world modeling can provide the foundations from which symbolic reasoning can emerge, after all this is how we (humans) learn it too

As usual comparisons with humans provide little practical insight for what's achievable with ML. Humans don't have to learn everything from scratch like ML models do, you aren't expecting ML models to learn language out of a few thousands of tokens just because humans can, so similarly you shouldn't expect neural networks to learn reasoning from world interaction alone.
by mnau | 2025-06-11 16:54:25+00:00
I am more likely to believe someone who bypassed Denuvo.

> One can see that Denuvo does indeed intervene from time to time, but what one can clearly see: It doesn’t do that very often, definitely not every frame.

> It’s only once every few seconds. Even less, sometimes it doesn’t do anything.

> To me personally, it tells that Denuvo executes checks so infrequently, that the likelyhood of it causing major performance issues seems rather low.

https://momo5502.com/posts/2024-03-31-bypassing-denuvo-in-ho...
by ludicrousdispla | 2025-06-11 16:54:58+00:00
At one point the distinction between Gen X and Gen Y was defined as which side of the end of WW2 one's parents were born on (within reason) which would make Gen Y children of boomers, and Gen X not children of boomers.

My 6th grade teacher (in the early 80's) asked our class once which of us thought that the world would end in nuclear armageddon, and all of us raised our hands. I mention this as it's likely a baseline for how Gen X'ers view the state of the world.
by Ancapistani | 2025-06-11 16:55:38+00:00
> It's relevant because having children irrevocably changes a woman's body for life.

True, and I should have pointed that out explicitly because you're absolutely right. I've seen what my wife went through having two children.

> To a man, it can be nothing more than ejaculation.

OK?

The fact that some males - I won't call them "men" - are terrible people is exactly my point.

For any person, their choice of partner dictates the course of the rest of their life. That includes "no partner", FWIW. It's the difference between having a true partner in life and having one more person to support.

> Also, very few men die in childbirth.

... but many more men die at jobs they work to support those children than women.
by autoexec | 2025-06-11 16:55:54+00:00
> 2. and help you learn how to do something!

I think it's more likely that people will learn far less. AI will regurgitate an answer to their problem and people will use it without understanding or even verifying if it is correct so long as it looks good.

All the opportunities a person would have to discover and learn about things outside of the narrow scope they initially set their sights on will be lost. Someone will ask AI to do X and they get their copy/paste solution so there's nothing to learn or think about. They'll never discover things like why X isn't such a good idea or that Y does the job even better. They'll never learn about Z either, the random thing that they'd have stumbled upon while looking for more info about X.
by insane_dreamer | 2025-06-11 16:56:11+00:00
I think it's a bit naive to think that companies like OpenAI will be content with their monthly user subscription fees and not seek to monetize their content through ads. Yahoo and Google didn't have ads either at the beginning (neither did Facebook or Instagram). And the reason why Google became the dominant tech company aka money-maker it is today is because of Adwords.
by FireBeyond | 2025-06-11 16:56:14+00:00
LOL. When ICE detained 900 employees from Tyson Foods who were undocumented, many provided them with written instructions from the company on how to fill out onboarding, payroll, and tax paperwork if they were undocumented immigrants, i.e., the company was perfectly aware and actively facilitating.

When they had their big press conference to announce the 900 arrests, reporters asked about plans to investigate the company based on the documentation found.

"That's not in the scope of our investigation. We do not have plans to do that at this time."

To no one's shock, they've never found time to do it since, either.
by suhas_rnd | 2025-06-11 16:56:22+00:00
Friend (co-worker) had a similar ideas around travel management and he built this.

Fully open sourced https://github.com/CopilotKit/CopilotKit/tree/main/examples/...

In case you find it useful.

https://examples-coagents-ai-travel-app-git-main-copilot-kit...
by kjkjadksj | 2025-06-11 16:56:23+00:00
In a way it is. Why are housing costs so high in Redmond, WA? The result of an influx of high income tech workers to the local housing market and the resulting shift of prices such as to eventually dilute the utility of that high salary to begin with. People in the area without a hook on that whale are of course left high and dry.
by atombender | 2025-06-11 16:57:09+00:00
Very happy with CH, but I'm sadly disappointed with HyperDX:

* Not possible to reorder columns?

* Not possible to wrap cells?

* The doesn't seem to be a concept of "field popularity" as Kibana has (where you can also "pin" fields)?

* The log view's chart is very simplistic. No breakdown. Time selector is very primitive. Look at Google Cloud's log view if you want to see something good here.

* No field value autocompletion when using the query builder?

* Live view is annoying as hell. It scrolls to the top every few seconds even when there is no need data.

* Chart view is nearly useless. I tried to create a chart showing two time series calculations, average and P95 of a metric, and it doesn't draw it correctly, and the series get messed up, and overall I think it's not usable. Happy to explain further, but even a cursory test should reproduce this. Fortunately Grafana can access CH data and do a much better job here.

* The drill-down sidebar doesn't seem to have any idea what's important or not, so some fields I will never want to filter on are high up in the list and others are further down. I can't rearrange the fields?

* Lots of other nuisances.

Overall I found it much, much weaker than Kibana for both logs and charts, and Kibana is already pretty atrocious at both, so.

I can probably live with it because I'm desperate to replace Elastic with CH, but I think I will kiss the functionality of the Kibana UI.
by rbanffy | 2025-06-11 16:57:27+00:00
> I always find it hilarious to see how the vocal minority is overrepresented on this forum.

Those who oppose the norm are usually a lot more vocal than the people who support it, or just don't care. This is why you get bathtub curves in ratings - you can bet the low ratings are over-represented in comparison with the meh and the praise.
by dblohm7 | 2025-06-11 16:57:58+00:00
> I have no insider knowledge but from my perspective the reason Firefox OS failed is the same reason WebOS failed and the same reason Windows Phone failed: apps.

I was at Mozilla during this time, and I remember a huge blocker was WhatsApp. They were not interested in porting, but at the time it was essentially the killer app in the same emerging markets that Firefox OS was targeting.
by BobaFloutist | 2025-06-11 16:58:44+00:00
Sure, I'm saying maybe we should distribute public funds to reduce or minimize the affect of having children on your quality of life, if we agree that having children is a public good.

The same way that we give people tax breaks for making donations, because we think making donations is good, people having children are donating their time, physical health, money, and earning potential to the greater good of society, so maybe they should be compensated for it.
by thenthenthen | 2025-06-11 16:59:10+00:00
Never been a big funk fan until the unreleased demo instrumentals of midnight express got released on People’s Potential United (check out their catalog if you havent): https://ppudc.bandcamp.com/album/the-midnight-express-show-b...

Also some demo’s by Prince are amazing.

Not sure, but the rawness just breathes life and blows most studio stuff out of the water.

[Edit] bonus end game track: https://youtu.be/dQN3fxoIOpk (thank you Gilles Peterson)
by HauntedDrum | 2025-06-11 16:59:15+00:00
This is a popular quote from Battlestar Galactica:

Commander William Adama: Yeah, but I'm not going to be your policeman. There's a reason why you separate military and the police. One fights the enemy of the state. The other serves and protects the people. When the military becomes both, then the enemies of the state tend to become the people.
by dimitry12 | 2025-06-11 16:59:19+00:00
If you bridge recorded trajectories with LVLM, then cameras are necessary visual input for LLM to decide which sub-tasks need to be performed to accomplish long-horizon task, and sub-tasks correspond to pre-recorded ("blind") trajectories which are replayed.

If you go beyond pre-recorded "blind" trajectories into more robust task-policies (which you would have to train from many demonstrations) then cameras become necessary to execute the sub-task.
by yuck39 | 2025-06-11 16:59:35+00:00
Many of the traditional SEO players are now figuring out how to game the system to get their customers to show up more frequently in LLM responses.

Once the pressure to turn a profit is high enough the big players surely won't just leave that money on the table.

The scary part is that even if we end up paying for "ad-free" LLM services how do we really know if it is ad-free? Traditional services are (usually) pretty clear on what is an ad and what isn't. I wouldn't necessarily know if raid shadow legends really is the greatest game of all time or if the model had been tuned to say that it is.
by cgriswald | 2025-06-11 16:59:42+00:00
I've noticed this even with product placement in film and television. It's not enough that Super Agent X drives a Palmora Targon, they just have to pan, zoom, tilt the camera to include a shot of the Palmora logo perfectly centered in frame for a few seconds as the car careens off a cliff. I'm only surprised the protagonist isn't also talking about how well the car has served him with its <insert technical details> as he laments its loss while he parachutes to safety.
by Kim_Bruning | 2025-06-11 16:59:47+00:00
How about "Cartoon car, not Pixar" for instance.

I think it's important for AI to learn from sources; just to know what not to do as well.

And I suppose it's legal to explore a visual space for your own personal use as well.

Actually publishing copyright infringing materials is a different story. Not sure you should blame the tool though.
by vidarh | 2025-06-11 17:00:21+00:00
Most human criticism is not doing anything of deep analysis either, but just reading the text and comparing it to what we know about similar text.

> Even if there was nothing wrong at all Claude would still find something to critique

And the entire point was that you claimed 'Both ChatGPT and Claud always say something like, "a few grammar corrections are needed but this is excellent!"'.

Which clearly is not the case, as demonstrated. What you get out will depend on how much effort you're willing to put into prompting to specify the type of response you want, because they certainly lack "personality" and will try to please you. But that includes trying to please you when your prompt specifies how you want them to treat the input.

> It doesn't really have an understanding of the text at all.

This is a take that might have made sense a few years ago. It does not make sense with current models at all, and to me is a take that typically suggest a lack of experience with the models. Current models can in my experience e.g. often spot reasoning errors in text provided to them that the human writer of said text refuse to acknowledge is there.

I suggest you try to paste some bits of text into any of the major models and ask them to explain what they think the author might have meant. They don't get it perfectly right all of the time, but they can go quite in-depth and provide analysis that well exceeds what a lot of people would manage.
by freedomben | 2025-06-11 17:00:38+00:00
Just a theory, but given how much fracturing/variation of music tastes people have developed in the last 50 years, I'm not sure there's enough of an audience for any of those mega bands to get to that level anymore (except for a few pop artists here and there).

I also suspect discoverability is a lot more of a challenge now too given the saturation of content out there and the small market. I've discovered some excellent bands (for my musical tastes of course, which are Rock & Metal) that I can't believe aren't bigger. These Four Walls and Thousand Needles In Red come to mind. Like Thieves is pretty decent too, nice music to put in the background on a drive through the canyon or while working. All of those bands are on Bandcamp btw.
by glomgril | 2025-06-11 17:00:58+00:00
one man's exfiltration is another man's distillation `¯\_(ツ)_/¯`

you could say they're playing by a different set of rules, but distilling from the best available model is the current meta across the industry. only they know what fraction of their post-training data is generated from openai models, but personally i'd bet my ass it's greater than zero because they are clearly competent and in their position it would have been dumb to not do this.

however you want to frame it, they have pushed the field forward -- especially in the realm of open-weight models.
by arturocamembert | 2025-06-11 17:00:59+00:00
I can only speak to my own experience of doing this professionally in northern climes without power tools for ~5 years, but both of your suggestions are foreign to me. I take this as a nice reminder that there is lots of regional variation to this craft around the world, which isn't surprising.

Even then, building a barn with dried pine or hemlock is much more tedious and incurs many more trips to the sharpening wheel. It is in no way easier.
by kylecazar | 2025-06-11 17:01:08+00:00
I agree with all of the assertions about what software should be.

But... I think a lot of it already is customizable, and users don't want to configure. End-users (or doctors) hate having to learn more about software than they absolutely must. Just an example, Epic (EHR from the essay) definitely has the ability to mark fields as optional/required. Someone just needs to get in and do it, and they don't want to/know how.

The inaccessibility of config to laypeople may actually be where AI shines. You prompt an in-app modal to change X to Y, and it applies the change. A natural language interface to malleability.
by jauntywundrkind | 2025-06-11 17:01:43+00:00
That so much of the document is about how UltaEthernet maps to Libfabric rather confirms that premise! There's also a credit based flow system, and connection manager roles, which are also easily identifiable Infiniband concepts.

I'm interested to see what the optional hardware features are. And what their relationship is to the different UE profiles (AI Base, AI Full, and HPC).

> The Ultra Ethernet Transport (UET) layer is designed to handle the most challenging application scale, deliver packets reliably and securely, manage and avoid congestion within the network, and react to contention at the endpoints. Its goals are minimal tail latency and highest network utilization. At the same time, UET is designed to enable simple hardware and software implementations – such as what might be required for accelerator-integrated endpoints. UET can be programmed through the OFI libfabric standard interface. It sets out to address the shortcomings of RoCEv2, specifically its semantics, transport layer, wire operations, implementation complexities, and scale limits
by quantified | 2025-06-11 17:01:51+00:00
> Within five years, the most beloved AI product won’t have an app, a screen, or a UI, and its brand will be more trusted than your bank.

I'm not saying this won't be true, in the sense that people will place as much trust in the product as they do in their own mother or the effects of gravity, only that it'll be horribly misplaced. Your innermost thoughts and behaviors will be on sale to criminals, and you'll be nudged in whatever direction the managers of the product see fit.
by mook | 2025-06-11 17:02:30+00:00
It sounds like reading the code and forking it (therefore preventing malicious updates) totally satisfies the intent behind the policy, then.

My company has a similar whitelist of actions, with a list of third-party actions that were evaluated and rejected. A lot of the rejected stuff seems to be some sort of helper to make a release, which pretty much has a blanket suggestion to use the `gh` CLI already on the runners.
Show HN: Spark, An advanced 3D Gaussian Splatting renderer for Three.js
by dmarcos | 2025-06-11 17:02:56+00:00
I'm the co-creator and maintainer of https://aframe.io/ and long time Web 3D graphics dev.

Super excited about new techniques to author / render / represent 3D. Spark is a an open source library to easily integrate Gaussian splats in your THREE.js scene I worked with some friends and I hope you find useful.

Looking forward to hearing what features / rendering techniques you would love to see next.
by timeinput | 2025-06-11 17:03:02+00:00
> I still get to stub out the types and function signatures I want, but the LLM can fill them in and I move on. More likely I'll even have my go at the implementation but then tag in the LLM when it's not fun anymore.

This is the best part for me. I can design my program the way I want. Then hack at the implementation, get it close, and then say okay finish it up (fix the current compiler errors, write and run some unit tests etc).

Then when it's time to write some boiler plate / do some boiler plate refactoring it's extract function xxx into a trait. Write a struct that does xxx and implements that trait.

I'm not over the resentment entirely, and if someone were to push me to join a team that coded by creating github issues, and reviewing the PRs I would probably hate that job, I certainly do when I try to do that in my free time.

In wood working you can use hand tools or power tools. I use hand tools when I want to use them either for a particular effect, or just the joy of using them, and I don't resent having to use a circular saw, or orbital sander when that's the tool I want to use, or the job calls for it. To stretch the analogy developing with plain text prompts and reviewing PRs feels more like assembling Ikea furniture. Frustrating and dull. A machine did most of the work cutting out the parts, and now I need to figure out what they want me to do with them.
by jeffbee | 2025-06-11 17:03:07+00:00
There is a good article scattered within this article, but unfortunately it is hard to take seriously when it claims to be based on "research" entitled "Is Google Getting Worse" which is one of the most misleading papers of the last few years. That's the title and everyone just closes the tab. University researchers have proved that Google is getting worse! There was a paper! But the problem with the paper is that none of the search results it evaluates are from Google.