MurphyA/hacker-news huggingface dataset:
by westurner | 2025-09-06 13:38:01+00:00
I suspect this was downvoted in ignorance.

Do you understand how consensus matters with distributed databases and DLTs?

Do you understand the difference between WAL checksums and Merkle hashes?

If the WAL checksums are not sufficient, is the SQL database sufficient? Why are Merkle hashes not "bolted on" but native to blockchains?

How many integrity hashes should be bolted onto a SQL database for there to be replication with data integrity?
by ACCount37 | 2025-09-06 13:38:32+00:00
Is there any knowledge of "correct vs incorrect" inside you?

If "no", then clearly, you can hit general intelligence without that.

And if "yes", then I see no reason why an LLM can't have that knowledge crammed inside it too.

Would it be perfect? Hahahaha no. But I see no reason why "good enough" could not be attained.
by hnlmorg | 2025-09-06 13:38:42+00:00
> XREAL is DisplayPort Alt Mode + USB for gyros. It's also wired only.

I know what Xreal uses. As I said, I have a pair

> DP needs 10-40Gbps of bandwidth, doesn't work wireless.

And as I also said, having a cable is a feature, not a problem.

VR headsets are heavy and uncomfortable. USB powered XR glasses are not. And the reason for that is because you don’t need to make those XR glasses as literal portable computers with heavy batteries.

You might relish the idea of an ugly monstrosity that weighs as much as a laptop strapped to your head. Myself, I’d much rather have something that look and feel like sunglasses. If that means I need a discreet UsB cable behind my ear, then thats a small price to pay because they’d still look less stupid than wearing anything bulkier out in public.

> USB cameras also aren't natively supported on iOS/Android. You need apps. With apps comes lock-in opportunities which are never not tapped.

That’s not a limitation for all platforms though. And you’d have that problem on Android whatever solution you opted for. So it’s a moot point.

> So "just use USB" doesn't make technical sense at all.

It does and plenty of people, myself included, owning a pair of Xreal glasses are proof of that.

The problem here is not USB, it’s that you have very specific differing requirements and thus are dismissing the practical value myself and others have shared.
by dingdingdang | 2025-09-06 13:38:48+00:00
Very impressive numbers.. wonder how this would scale on 4 relatively modern desktop PCs, like say something akin to a i5 8th Gen Lenovo ThinkCentre, these can be had for very cheap. But like @geerlingguy indicates - we need model compatibility to go up up up! As an example it would amazing to see something like fastsdcpu run distributed to democratize accessibility-to/practicality-of image gen models for people with limited budgets but large PC fleets ;)
by amelius | 2025-09-06 13:39:02+00:00
They hallucinate because it's an ill-defined problem with two conflicting usecases:

1. If I tell it the first two lines of a story, I want the LLM to complete the story. This requires hallucination, because it has to make up things. The story has to be original.

2. If I ask it a question, I want it to reply with facts. It should not make up stuff.

LMs were originally designed for (1) because researchers thought that (2) was out of reach. But it turned out that, without any fundamental changes, LMs could do a little bit of (2) and since that discovery things have improved but not to the point that hallucination disappeared or was under control.
by danaris | 2025-09-06 13:39:06+00:00
So now that we're all terrified that one of our various pharmaceuticals might, hypothetically cause an increased chance of autism, we have to take them all off the market and do extensive testing of absolutely everything? All the painkillers, blood pressure medicines, immunosuppressants for transplant patients, antipsychotics and antiseizure meds—everything?

Surely you understand that that makes no sense at all? All of these medicines have already been tested and shown to be safe, based on the science and understanding of the time. That's why they're on the market in the first place.

For better or for worse, the burden of proof is now on those who want to show that they are dangerous.
by sparkie | 2025-09-06 13:39:57+00:00
The biggest issue is that companies which depend on something like OpenSSL do not do enough to sustain it, leaving its maintainers working often uncompensated, for the benefit of people making far more money.

Would it be a rug pull if those maintainers simply burned out and decided "I'm moving onto something else," Leaving the project in limbo, with nobody maintaining it?

Or maybe they really do enjoy working on the project, but it doesn't pay the bills, so they have to look for an alternative way to monetize it, and that way can continue working on it.

My opinion is that unless you genuinely just enjoy working on something and sharing it, you are not obliged to do unpaid labour for the benefit of anyone else. Companies depending on FOSS software should be contributing financially to each and every one of them. This is the real shitty behavior - the expectation these companies have of getting bugfixes and improvements for free.

In the Mongo/Elastic and Amazon cases for example, this is far smaller companies being taking advantage of by a giant. IMO they were right to "rug pull" by relicensing under SSPL. Amazon can easily afford to maintain forks for these projects - but it probably would've been cheaper for them to just contribute financially, and they wouldn't have needed to switch from AGPL. Anyone who works on OpenSearch without compensation is a fool - essentially doing unpaid labour for one of the wealthiest companies on the planet.
by benrutter | 2025-09-06 13:40:02+00:00
Tangential, but I think github's secret weapon of inertia is. . .(drumroll) github stars.

They're still seen by a lot of people as a sign of project maturity and use. My unfounded suspicion is if they all dissapeared tomorrow, people would be a lot more likely to try alternative code forges.

I've been using codeberg of late, more because of their politics than anything, but in all honesty the user experience between github/gitlab/codeberg/sourcehut/gitea is near identical.
by tombert | 2025-09-06 13:40:09+00:00
I was about to say this. Elon would go on stage and say something like “and this is something we can do today”, or “coming next year” in 2018. The crowd goes wild, the stock price shoots up.

The first time could be an honest mistake, but after a certain point we have to assume that it’s just a lie to boost the stock price.
by Juliate | 2025-09-06 13:40:34+00:00
1/ any day that includes a single meeting (related or not) should be marked as fully unavailable.

So if you have planned meeting in a week, group them (but not all of them on a single day either) and mark that day as unavailable. That usually already reduces a week of work to 4 days.

Then it's usually more on the longer term, but you (well, each dev actually) may benchmark continuously previous estimates against reality, so that they can understand their bias over time.

2/ do delegate approvals with a few basic rules: have a (short) rationale written down for each decision taken without a n+1 request; should be reversible if it's important.

3/ how long are your sprints usually?
by api | 2025-09-06 13:40:36+00:00
Oh stop. When someone gives you free stuff and then changes the terms a little that isn’t a “rug pull” and it’s not “feudalism.” If you contributed a little and voluntarily signed a CLA this is also not a “rug pull.”

The whole reason for these “rug pulls” is abuse of the open source ethos by big companies using it as free labor for SaaS and giving nothing back.

SaaS is more like feudalism than any other software model, yet the open source community seems committed to making sure the SaaS industry can continue its free ride.

Part of why I’d hesitate to ever again make free (as in beer) software is this whole toxic shitty mentality. If I give you a ton of work for free, say thank you. If a bunch of investors fund that, say thank you. This entitlement mentality from a bunch of people with careers that mostly put them in or near the global 1% is gross. It’s not like you people need stuff for free. You ain’t poor.
by 3np | 2025-09-06 13:40:42+00:00
I've had an ongoing support ticket with GH for several months now asking them to actually disable Copilot, as there is Copilot all over and it's clear from inlined JSON on github.com pages when signed in that my account is actually opted in to Copilot features despite Settings page saying features should be disabled. I've never ever opted in to anything related to GH AI and am not a vscode user.

They keep closing the ticket and saying it's "with the engineering team". I keep reopening and asking for resolution, escalation, or progress.

GitHub did have working and professional support in the past but in 2025 they are just malicious.

It's surreal.
by alchemist1e9 | 2025-09-06 13:40:49+00:00
Any pointers to what is SOTA for cluster of hosts with CUDA GPUs but not enough vram for full weights, yet 10Gbit low latency interconnects?

If that problem gets solved, even if for only a batch approach that enables parallel batch inference resulting in high total token/s but low per session, and for bigger models, then it would he a serious game changer for large scale low cost AI automation without billions capex. My intuition says it should be possible, so perhaps someone has done it or started on it already.
by diggan | 2025-09-06 13:40:49+00:00
> In practice, by and large, with very few exceptions, macros are frowned upon in the same way that using metaprogramming in ruby is. Macros are only fun to the person writing them (and not even the author when they have to maintain it).

I'm not sure "frowned upon" is the right expression, but I'm not a native speaker.

The way I've internalized it, is basically "Avoid macros unless there is no other way", which basically means use functions/anything else whenever you can, but if you absolutely have to use a macro for something (like you wanna read the arguments before they're parsed), then go for it.
by co_dh | 2025-09-06 13:41:00+00:00
But why do you need serialization? Because the data structure on disk is not the same as in memory. Arthur Whitney's k/q/kdb+ solved this problem by making them the same. An array has the same format in memory and on disk, so there is no serialization, and even better, you can mmap files into memory, so you don't need cache!

He also removed the capability to define a structure, and force you to use dictionary(structure) of array, instead of array of structure.
by codedokode | 2025-09-06 13:41:15+00:00
Is this legal: scan billions of pirated books, train a LLM on them and generate billion public domain books with it so that nobody ever needs copyrighted books anymore?

Also if there is a software library with annoying Stallman-style license, can one use LLM to generate a compatible library but in a public domain or with commercial license? So that nobody needs to respect software licenses anymore? Can we also generate a free Photoshop, Linux kernel and Windows this way?
by armcat | 2025-09-06 13:41:55+00:00
One of the most interesting mathematical aspects to me are the fact that LLMs are logit emitters. And associated with this output is uncertainty. Lot of ppl talk about networks of agents. But what you are doing is accumulating uncertainty - every model in the chain introduces its own uncertainty on top of what it inherits. In some situations I've seen a complete collapse after 3 LLM calls chained together. Hence why lot of people recommend "human in the loop" as much as possible to try and reduce that uncertainty (shift the posterior if you will); or they recommend more of a workflow approach - where you have a single orchestrator that decides which function to call, and most of the emphasis (and context engineering) is placed on that orchestrator. But it all ties together in the maths of LLMs.
by macNchz | 2025-09-06 13:42:15+00:00
Build and tag internal base images on a regular cadence that individual projects then use in their FROM. You’ll have `company-debian-python:20250901` as a frozen-in-time version of all your system level dependencies, then the Dockerfile using it handles application-level dependencies with something that supports a lockfile (e.g. uv, npm). The application code itself is COPY’d into the image towards the end, such that everything before it is cached, but you’re not relying on the cache for reproducibility, since you’re starting from a frozen base image.

The base image building can be pretty easily automated, then individual projects using those base images can expect new base images on a regular basis, and test updating to the latest at their leisure without getting any surprise changes.
by diggan | 2025-09-06 13:42:22+00:00
> So, (re)defining language constructs in a project seems nightmarish to me to support in production and therefore I never even attempted anything serious in a functional programming language.

It can be, but also not. If you isolate them into libraries with clear interfaces, you can kind of avoid that. I think clojure.core.async is an excellent showcase in something you couldn't do in other languages, where asynchronous channels were possible to add to the core language without changing anything in the core compiler itself, and because of the small interface, you can still use it without ending up with nightmares :)
by tombert | 2025-09-06 13:44:05+00:00
I am not 100% sure which “sense” this would be, but when I drive I can “feel” the texture of the road and intuit roughly how much traction I have. I’m not special, every driver does this, consciously or not.

I am not saying that you couldn’t do this with hardware, I am quite confident you could actually, but I am just saying that there are senses other than sight and sound at play here.
by diggan | 2025-09-06 13:44:30+00:00
> I think GitHub added the “pull request” as a really useful add on to git and that really made it take off.

Personally, I remember the initial selling point of GitHub being that it was more "social" than any other forges at the time, since we were all wrapped up in the Web 2.0 hype and what not. I think they pushed that on their landing page back in the day too.

It was basically Twitter but redone specifically for developers, and focus on code rather than random thoughts.
by chimeracoder | 2025-09-06 13:44:55+00:00
> More importantly, it is cheap enough to be always used as a baseline verification

> It's like unit testing vs full user acceptance testing. You can and should do both, but the latter isn't for every PR.

You say all this as if it weren't already happening. OP was surprised human testing was being conducted at all, not that non-human testing wasn't being done (which is a claim nobody made, and which isn't true).
by lucyjojo | 2025-09-06 13:45:07+00:00
online music playing is HEAVILY latency sensitive. (for instance an online jazz session)

then you have online video games. increasing the area where you can get good connections increase quadratically (or more, if we hit step function = big city get in range) the viability of niche multiplayer video games and it is thus a boost to creativity.

there are probably many more niches... (need to think of reachable area, quadratic, instead of 1-to-1 link linear)
by Mistletoe | 2025-09-06 13:46:04+00:00
> It bought the medium and took an entire community hostage in the process just for the sake of profit.

Counterpoint is that is what companies are supposed to do. They are made to make money, the end. The only hope against this for humans is regulation, and that has fallen off the face of the earth. It’s like humans are doomed to repeat the late 19th and early 20th century era over and over.
by hedora | 2025-09-06 13:46:17+00:00
Though note that redhat is doing this with all GPL software, but without a CLA.

They retaliate against customers that share source code, and claim that this doesn’t fall under the “without further restrictions” clause in the redistribution of source code phrase in the GPL.

Anyway, rug pulls are apparently possible, even with the GPL, at least until this is taken to court and IBM loses.
by mixedbit | 2025-09-06 13:46:27+00:00
Musk's argument also ignores intelligence of humans. The worst case upper bound for reaching human level driving performance without LIDAR is for AI to reach human level intelligence. Perhaps it is not required, but until we see self-driving Teslas performing as well as humans, we won't know this. Worst case scenario is that Tesla unsupervised self-driving is as far away as AGI.
by Strom | 2025-09-06 13:46:52+00:00
30 fps was not the norm, at least not with competitive games. Like Counter-Strike in 2000 on a CRT. Yes 1024x768 was common, but at 100 fps. Alternatively you would go to 800x600 to reach 120 fps.

It’s only when LCDs appeared that 60 Hz started being a thing on PCs and 60 fps followed as a consequence, because the display can’t show more anyway.

It’s true that competitive gaming has pushed the priority of performance, but this happened in the 90s already with Quake II. There’s nothing fake about it either. At the time a lot of playing happened at LANs not online. The person with the better PC got better results. Repeatedly reproduced by rotating people around on the available PCs.
by jay-baleine | 2025-09-06 13:47:24+00:00
What tends to get overlooked is the actual development speeds these projects achieve.

The PhiCode runtime for example - a complete programming language with code conversion, performance optimization, and security validation. It was built in 14 days. The commit history provides trackable evidence; manual development of comparable functionality would require months of work as a solo developer.

The "more work" claim doesn't hold up to measurement. AI generates code faster than manual typing while systematic constraints prevent the architectural debt that creates expensive refactoring cycles later. The 5-minute setup phase establishes foundations that enable consistent development throughout the project.

On scalability, the runtime demonstrates 70+ modules maintaining architectural consistency. The 150-line constraint forced modularization that made managing these components feasible - each remains comprehensible and testable in isolation. The approach scales by sharing core context (main entry points, configuration, constants, benchmarks) rather than managing entire codebases.

Teams can collaborate effectively under shared architectural constraints without coordination overhead.

This isn't about training wheels or learning syntax. The methodology treats AI as a systematic development partner focused on architectural thinking rather than ad-hoc prompting. AI handles syntax perfectly - the challenge lies in directing it toward maintainable, scalable solutions at production speed.

Previous attempts at structured AI collaboration may have failed, but this approach addresses specific failure modes through empirical measurement rather than theoretical frameworks.

The perceived 'strictness' provides flexibility within proven constraints. Developers retain complete freedom in implementation approaches, but the constraints prevent common pitfalls like monolithic files or tangled dependencies - like guardrails that keep you on the road.

The project examples and commit histories provide concrete evidence for these development speeds and architectural outcomes.
by micahdeath | 2025-09-06 13:47:44+00:00
Personally, I've been using Click-Once with a daily auto-update.

In the past, we didn't use auto-updates and manually updated those. Now days we are mostly web apps.

There is one app that we deploy through MECM. It's not our app, but it's used on enough PCs that MECM manages the deployment of it.
by arduanika | 2025-09-06 13:47:48+00:00
We are gods, we are very smart, we make our own rules, says the cult. We define what safety is, not you. Safety is protecting you from imagined monsters for your own good, not protecting you from getting robbed by us. And anyways, property rights are just made up, man, a social construct.

But investors, please give us billions of dollars worth of that imaginary social agreement. We need it so that we can build the inevitable future. We're gonna do it more ethically than those guys over there.

What a swindle.
by yunwal | 2025-09-06 13:47:51+00:00
The other explanation is that it’s everywhere because AI pushers would like to integrate it with everything in order for it to be its most useful. Most of them don’t own your OS and your password manager, so they push it instead into a million different little places.

Doesn’t change the fact that it’s stupid, annoying, and bad design, but I don’t know that outright deception is needed to explain it.
by skydhash | 2025-09-06 13:49:34+00:00
By that point I would have already produced the 20 line diff for the ticket. Huge commits (or change requests) are usually scaffolding, refactoring, or design changes to support new features. You also got generated code and verbose language like CSS. So stuff where the more knowledge you have about the code, the faster you can be.

The daily struggle was always those 10 line diffs where you have to learn a lot (from the stakeholder, by debugging, from the docs).
by cmiles74 | 2025-09-06 13:49:38+00:00
The less I know about a thing the more useful an LLM seems to be. I’m working with a new-to-me enterprise code base, the LLM helps me find related (and duplicate) code. Even here it’s usefulness has an expiration date, eventually I’ll know where stuff lives and I’ll use it less and less. Life experience tells me I’m not unique and I suspect the constant cram-AI-into-the-thing is because the vendors are hoping, eventually, they’ll find a use-case for LLMs that sticks.
by monkeyelite | 2025-09-06 13:50:00+00:00
> tackling really hard long term projects, but not as good at self promotion

Fabrice is one of my examples. Walter Bright (who does spend effort on promotion). Anyone who works on the V8 compiler at Google, or query engine on Postgres who we have never heard of.

> It seems to me like the evidence points to "if you tackle really hard, long term, and foundational software projects successfully, people will use it,

That’s a common belief among engineers. If you have worked at a large company you know that’s just now how big efforts like switching from Objective-C to Swift get done.
by DennisP | 2025-09-06 13:50:03+00:00
Huawei has a self-driving system that uses three lidars, which cost $250 each (plus vision, radar, and ultrasound). It appears to work about as well as FSD. Here's the Out of Spec guys riding around on it in China for an hour:

https://www.youtube.com/watch?v=VuDSz06BT2g
by crote | 2025-09-06 13:50:28+00:00
I'm getting quite sick of how it is forced on you. It's not just yet-another useful feature, they are shoveling it into everything, and giving it the most prominent place possible.

I don't want AI getting in the way on Github. I don't want an unremovable AI button in my Office 365 mail client. I don't want to get nagging AI popups every. single. time. I open the GCP console.

A year or two I was ambivalent about AI, and willing to give it a try. These days? I actively hate it. Like all nagging ads: if you have to force it on me this badly, how can it be anything but complete garbage?