MurphyA/hacker-news huggingface dataset:
by zahlman | 2026-01-26 17:39:00+00:00
They are. (see e.g. https://www.nbcnews.com/news/us-news/are-cities-ice-raids-ar...) And they have been, the whole time.

ICE has arrested and deported far more people from Texas than Minnesota (e.g. https://www.texasstandard.org/stories/texas-immigration-crac... https://www.newsweek.com/map-shows-states-ice-arrest-immigra... https://www.houstonpublicmedia.org/articles/news/politics/im... many other sources can easily be found).

You don't hear about it so much (unless you go looking) because Texas isn't a sanctuary state. Texas law enforcement supports and assists ICE, and Texas government officials don't encourage protests (and would tell protesters, if asked, not to obstruct and not to resist arrest). So there is no major conflict, minimal protest, and essentially no news coverage.

Minnesota government officials, on the other hand, seem to be interpreting 10A well beyond any precedent I ever heard of, and don't seem particularly interested in the consequences of the Supremacy Clause. In fact they have repeatedly falsely claimed that ICE are "not real law enforcement".
by spamizbad | 2026-01-26 17:39:11+00:00
> AI's / LLM's have already been trained on best practices for most domains.

I've been at this long enough to see that today's best practices are tomorrow's anti-patterns. We have not, in fact, perfected the creation of software. And the your practices will evolve not just with the technology you use but the problem domains you're in.

I don't mean this as an argument against LLMs or vibe coding. Just that you're always going to need a fresh corpus to train them on to keep them current... and if the pool of expertly written code dries up, models will begin to stagnate.
by maxglute | 2026-01-26 17:39:28+00:00
TW missiles can't "concentrate" because TW geography = all missile flight paths travels through boost, midcourse and terminal interceptors gauntlet along PRC easter theatre command which probably has the densest IADS in the world. PRC has like 3-4x more interceptors in eastern theater (8-12x more total) than TW has missiles. That's just land based, there's also 1000s of naval picket interceptors. Imagine if all of US patriot batteries in Florida, multiplied by 3, then asking what Cuba can do to saturate. Then add in USN DDGs and the answer is realistically nothing, because the industrial math is brutally lopsided. That's assuming TW gets to coordinate salvo their entire inventory, realistically most TELs would be glassed first, every part of TW is withing 5-7 min of PRC missiles and mlrs, less if fired from strait or loitering munitions, i.e. basically faster than abbreviated TEL setup cycle TW has for their tunnel to launch strike complex.
by noisy_boy | 2026-01-26 17:39:30+00:00
Are engineers really doing vibecoding in the truest sense of the word though? Just blindly copy/pasting and iterating? Because I don't. It is more of sculpting via conversation. I start with the requirements, provide some half-baked ideas or approaches that I think may work and then ask what the LLM suggests and whether there are better ways to achieve the goals. Once we have some common ground, I ask to show the outlines of the chosen structure: the interfaces, classes, test uses. I review it, ask more questions/make design/approach changes until I have something that makes sense to me. Only then the fully fleshed coding starts and even then I move at a deliberate pace so that I can pause and think about it before moving on to the next step. It is by no means super fast for any non-trivial task but then collaborating with anyone wouldn't be.

I also like to think that I'm utilising the training done on many millions of lines of code while still using my experience/opinions to arrive at something compared to just using my fallible thinking wherein I could have missed some interesting ideas. Its like me++. Sure, it does a lot of heavy lifting but I never leave the steering wheel. I guess I'm still at the pre-agentic stage and not ready to letting go fully.
by tedivm | 2026-01-26 17:40:05+00:00
Hard to talk about what models are doing without comparing them to what other models are doing. There are only a handful of groups in the frontier model space, much less who also open source their models, so eventually some conversations are going to head in this direction.

I also think it is interesting that the models in China are censored but openly admit it, while the US has companies like xAI who try to hide their censorship and biases as being the real truth.
by ryandrake | 2026-01-26 17:40:07+00:00
> So many people in the private sector just wait for the boss to push them around like chess pieces, and I can't understand how they're OK living like that.

I think a lot times, office workers will be reprimanded for taking action if they don't realize their chain of command are not supportive. Have this happen a couple of times, and you will quickly move into this mode of "I'm not going to do anything I'm not told to do." I can recall more than one former company where taking the initiative to perform some action independently was very risky to your career there.
Ask HN: Hosted LLMs to process personal data?
by yboulkaid | 2026-01-26 17:40:11+00:00
There are some good use cases for LLMs to process personal data (think paperless-ngx document scanning or semantic search for personal photos). However, this data should never be saved for future training as it's highly sensitive.

It's not always convenient to self-host LLMs as you'd need a beefy and costly GPU.

What's the best way to have access to good models with the guarantee that your datw won't be touched? AWS Bedrock? Self-host on an EC2 instance? Huggingface Pro?
by smorrow | 2026-01-26 17:40:27+00:00
The most "research" thing I'm aware of 9front (since you're speaking in present tense) doing is that GEFS needed to work out a lot of things for itself that weren't in the Bε-tree proof-of-concept FS that came before.

I dunno how "close to the metal" you'd consider that.

("GEFS" being a disk filesystem that's been discussed on HN.)
by citizenpaul | 2026-01-26 17:40:30+00:00
>build things we never would have attempted

I think there is something here but not much. The majority of business are carrying some SAS products that are an entire marching band when all they want are a drummer and guitar player. Making bespoke efficient tools will surge for sure.

The problem is that the building of these tools is all the same end. Increasing industry control to few players and further widening wealth inequality. Which leads us back to where does everyone go to work at that point?

We are at some sort of societal inflection point where we need new industries but only 20% of degrees are in some sort of science. 80% of degrees are in what is becoming nothing more than resume checkboxing for jobs that no longer will exist. Who is going to make the next big industry breakthough with 20% of degrees in business management? I don't see any push to get people in college for actual meaningful progress.

It seems it did happen, humans have hit post scarcity in survival terms(unevenly distributed). However we have in no way planned for what happens here, fairness has never been a priority. The cuthroat capitalism that made this possible is now eating itself with no plans to change.
by divbzero | 2026-01-26 17:40:52+00:00
> Primary sources:

> Maskelyne’s notes: https://doi.org/10.1098/rstl.1775.0050

> Hutton’s notes: https://doi.org/10.1098/rstl.1778.0034

> Cavendish’s notes on his own experiment: https://doi.org/10.1098/rstl.1798.0022

I got to reproduce Cavendish’s experiment when I was a student. Love that we can easily read the primary source today, archived and indexed by DOI.
by dimitri-vs | 2026-01-26 17:40:54+00:00
Hallucinations are not solved, memory is not solved, prompt injection is not solved, context limits are waaay too low at the same time tokens way too expensive to take advantage of context limits, etc. These problems have existed since the very early days of GPT-4 and there is no clear path to them being solved any time soon.

You basically need AGI and we are nowhere close to AGI.
by storystarling | 2026-01-26 17:40:58+00:00
Agreed. I’ve found the only reliable architecture for this is treating the LLM purely as a high-level planner rather than a controller.

We use a state machine (LangGraph) to manage the intent and decision tree, but delegate the actual transform math to deterministic code. You really want the model deciding the strategy and a standard solver handling the vectors, otherwise you're just burning tokens to crash into walls.
by quietsegfault | 2026-01-26 17:41:05+00:00
1. Xinjiang detention and surveillance (2017-ongoing)

2. Hong Kong National Security Law (2020-ongoing)

3. COVID-19 lockdown policies (2020-2022)

4. Crackdown on journalists and dissidents (ongoing)

5. Tibet cultural suppression (ongoing)

6. Forced organ harvesting allegations (ongoing)

7. South China Sea militarization (ongoing)

8. Taiwan military intimidation (2020-ongoing)

9. Suppression of Inner Mongolia language rights (2020-ongoing)

10. Transnational repression (2020-ongoing)
by somat | 2026-01-26 17:41:17+00:00
For what it's worth, if you want a self hosted replacement for Zoom Galene has worked great for me, The server requirements are remarkably low, especially if you are like me and just need a personal video chat to a few people. I run it on an old apu-2 with openbsd(which is just about the worst combination and it still works great) As a bonus there is no client, that is, the client is just a web page so very low friction to get people to use it.

https://galene.org/
by victor_y | 2026-01-26 17:41:31+00:00
Author here. We built Supabomb (https://github.com/ModernPentest/supabomb) to audit Supabase security and decided to test it against YC companies.

Key findings:
- 71 companies with accessible databases audited
- 20.1M rows exposed to anonymous access
- 28% leaking PII (emails, names, user data)
- 6 companies exposing auth tokens

This was coordinated with YC and Supabase security teams.

The root cause is almost always the same: developers create new tables and forget to enable RLS. The anon key is public by design—security comes entirely from Row-Level Security policies.

Happy to answer questions about methodology or findings.
by array_key_first | 2026-01-26 17:42:03+00:00
Nobody said it was. But it's not bad because of chemicals, because all bread is created with chemicals.

As for natural versus artificial - that's also bullshit. There's many natural ingredients that are poison, and many artificial ones that are good for you.

I mean, if I eat home made fried chicken everyday, you can bet your ass I'm not gonna live very long.
Show HN: a Rust-based multimodal inference server
by Beefin | 2026-01-26 17:42:17+00:00
We built a production-grade multimodal inference server in Rust for serving vision–language models (image + text → streamed text).

The goal was to explore what a Rust-native control plane looks like for modern multimodal inference: continuous batching, KV-aware admission control, predictable behavior under load, and proper streaming semantics.

The system exposes an OpenAI-compatible API, supports multi-image inputs, and is designed to degrade gracefully under overload rather than OOM or stall. It’s organized as a single monorepo with a gateway, GPU workers, scheduler, and pluggable engine adapters.

We’ve also included a benchmark suite focused on real-world scenarios (TTFT, cancellation, overload, fairness) rather than synthetic tokens/sec numbers.

Would love feedback from folks building or operating inference infrastructure.
by mschuster91 | 2026-01-26 17:42:33+00:00
> I'm not understanding why DHS federal employees are exempt from this standard.

Because the aim of ICE is to terrorize local communities that either have a lot of immigrants/non-white people in general or that vote heavily Democrat like Minneapolis.

And terror doesn't work when you can reliably identify the terrorists and hold them accountable, or do the same to the terrorists as they dish out on their victims.
by kmatthews812 | 2026-01-26 17:42:36+00:00
Beware the two extremes - AI out of the box with no additional config, or writing code entirely by hand.

In order to get high accuracy PRs with AI (small, tested commits that follow existing patterns efficiently), you need to spend time adding agents (claude.md, agents.md), skills, hooks, and tools specific to your setup.

This is why so much development is happening at the plugin layer right now, especially with Claude code.

The juice is worth the squeeze. Once accuracy gets high enough you don't need to edit and babysit what is generated, you can horizontally scale your output.
by roughly | 2026-01-26 17:43:21+00:00
One thing I’m becoming curious about with these models are the token counts to achieve these results - things like “better reasoning” and “more tool usage” aren’t “model improvements” in what I think would be understood as the colloquial sense, they’re techniques for using the model more to better steer the model, and are closer to “spend more to get more” than “get more for less.” They’re still valuable, but they operate on a different economic tradeoff than what I think we’re used to talking about in tech.
by anticorporate | 2026-01-26 17:43:25+00:00
A standardized hammer can just be a carpenter's hammer, though. Putting a nail pull on the back side is making it opinionated in a way that gives users access to a tool that they may not have thought of if they built their own hammer, but very well might appreciate having.

This isn't a defense of enterprise applications, though. They're more like a shed fully of rusty tools with a thirty different coping saws blades and not a single handle because corporate policy only allows for you to have a handle if Joe from accounting says you can, but why would he when his VP confidently said you can just hold the blade between your fingers.
by charlescearl | 2026-01-26 17:43:37+00:00
Over the past 10 years have seen extended clips of the incident which actually align with CPC analysis of Tianamen square (if that’s what’s being referred to here).

However, in deepseek, even asking for bibliography of prominent Marxist scholars (Cheng Enfu) i see text generated then quickly deleted. Almost as if DS did not want to run afowl of the local censorship of “anarchist enterprise” and “destructive ideology”. It would probably upset Dr. Enfu to no end to be aggregated with the anarchists.

https://monthlyreview.org/article-author/cheng-enfu/
by volkercraig | 2026-01-26 17:43:57+00:00
They are text generators, and yes they are pretty good, but that really is all they are, they don't actually learn, they don't actually think. Every "intelligence" feature by every major AI company relies on semantic trickery and managing context windows. It even says it right on the tin; Large LANGUAGE Model.

Let me put it this way: What OP built is an airplane in which a pilot doesn't have a control stick, but they have a keyboard, and they type commands into the airplane to run it. It's a silly unnecessary step to involve language.

Now what you're describing is a language problem, which is orchestration, and that is more suited to an LLM.
by Lerc | 2026-01-26 17:43:59+00:00
>Our current approach with AI code is "draft a design in 15mins" and have AI implement it. The contrasts with the thoughtful approach a human would take with other human engineers. Plan something, pitch the design, get some feedback, take some time thinking through pros and cons. Begin implementing, pivot, realizations, improvements, design morphs.

Perhaps that is the distinction between reports of success with AI and reports of abject failure. Your description of "Our current approach" is nothing like how I have been working with AI.

When I was making some code to do a complex DMA chaining, the first step with the AI was to write an emulator function that produced the desired result from the parameters given in software. Then a suite of tests with memory to memory operations that would produce a verifiable output. Only then started building the version that wrote to the hardware registers ensuring that the hardware produced the same memory to memory results as the emulator. When discrepancies occurred, checking the test case, the emulator and the hardware with the stipulation that the hardware was the ground truth of behaviour and the test case should represent the desired result.

I occasionally ask LLMs to one shot full complex tasks, but when I do so it is more as a test to see how far it gets. I'm not looking to use the result, I'm just curious as to what it might be. The amount of progress it makes before getting lost is advancing at quite a rate.

It's like seeing an Atari 2600 and expecting it to be a Mac. People want to fly to the moon with Atari 2600 level hardware. You can use hardware at that level to fly to the moon, and flying to the moon is an impressive achievement enabled by the hardware, but to do so you have to wrangle a vast array of limitations.

They are no panacea, but they are not nothing. They have been, and will remain, somewhere between for some time. Nevertheless they are getting better and better.
by colechristensen | 2026-01-26 17:44:00+00:00
Tell me you honestly think what is happening in America right now isn't the outcome of long planning by Russian intelligence (and likely other intelligence services). Their plan was to install a leader they had chosen and influenced.

Also Epstein was probably also a spy, but more likely for Mossad. BIG COINCIDENCE he was so close with dear leader?

Then tell me you think that doing things in Russia isn't possible.
by spwa4 | 2026-01-26 17:44:13+00:00
I think you mean sponsored by the UN, whose largest voting block is the "Organization of Islamic countries" and whose second largest voting block is the "Non-Aligned movement" (that really means aligned with Moscow). There's overlap, for example, Iran is in both camps (fitting since it's a theocracy and both the Iranian government and the parent organization of Hamas, the muslim brotherhood, was greatly grown and sponsored by/with the help of the KGB during the cold war. Perhaps also relevant: the PA's original leader, Yasser Arafat El-Masri (translates to: The wise Egyptian) was an Egyptian KGB spy and was sponsored by Moscow with at least a billion dollars)
by tialaramex | 2026-01-26 17:44:21+00:00
Because I'm an old man I found Ebert's actual reviews useful, he was reviewing movies in a period when I watched many more than I do now - and I think the reason they were useful gives us an insight here.

Roger Ebert did not like the same movies I did, not even close - but I was able to triangulate from his perspective to know better how I might feel about the movie before I watched it, based on his brief review.

I think that in a similar respect reviews by Yahtzee Croshaw work for me. I don't experience games the same way, but I get a better idea of how I would find the game from his video review than some random game journo 4/5 stars rating.
by amenhotep | 2026-01-26 17:44:24+00:00
This is a sort of interesting point, it's true that knowingly-metaphorical anthropomorphisation is hard to distinguish from genuine anthropomorphisation with them and that's food for thought, but the actual situation here just isn't applicable to it. This is a very specific mistaken conception that people make all the time. The OP explicitly thought that the model would know why it did the wrong thing, or at least followed a strategy adjacent to that misunderstanding. He was surprised that adding extra slop to the prompt was no more effective than telling it what to do himself. It's not a figure of speech.
by ameliaquining | 2026-01-26 17:44:28+00:00
I'm not sure I would characterize this as "Ebert recanted" so much as "Ebert decided it was a bad idea to wade into this debate".

If you want to read a thoughtful, non-snobbery-based argument that video games aren't art, I recommend the GDC talk "An Apology for Roger Ebert" by Brian Moriarty (who designed a number of classic adventure games circa the late 1980s, and now teaches video game design at my alma mater, where I had the good fortune to hear him give a version of this talk).

https://web.archive.org/web/20120510115932/https://www.gamas...

I don't agree with all of it, but it's thought-provoking and I learned a lot about the history and philosophy of art.
by legitster | 2026-01-26 17:44:42+00:00
The author makes it sound like such a binary choice, but there's a happy middle where you are having AI generate large blocks of code and then you closely supervise it. My experience so far with AI is to treat it like you're a low-level manager delegating drudgework. I will regularly rewrite or reorganize parts of the code and give it back to the AI to reset the baseline and expectations.

AI is far from perfect, but the same is true about any work you may have to entrust to another person. Shipping slop because someone never checked the code was literally something that happened several times at startups I have worked at - no AI necessary!

Vibecoding is an interesting dynamic for a lot of coders specifically because you can be good or bad at vibecoding - but the skill to determine your success isn't necessarily your coding knowledge but your management and delegation soft skills.
by fragmede | 2026-01-26 17:45:37+00:00
> self driving cars are still not here

Yeah they are, even if you don't have one yet. We can rathole into whether the need to hit level 5 before it "counts", but Waymos drive around multiple cities, today, and Tesla FSD works well enough that I'd rather drive next to a Tesla with FSD than a drunk driver.

If your evidence that AI isn't something to be worried about is saying self-driving cars aren't here, when they are, will then, we're fucked.

The future is here, it's just unevenly distributed. For cars, this manifests as they're physically not available everywhere yet. For programming, it's unevenly distributed according to how much training data there was in that language and that domain to scrape across the whole Internet.
by Pinus | 2026-01-26 17:45:40+00:00
From what I have understood, a significant part of the reason why Sweden scrapped its nuke program last time around, was that we found out that nukes pose more questions than they answer. Obviously, you need the nukes themselves, and a reliable delivery mechanism. Neither are cheap. Preferably, you want second-strike capability, which is kind of tricky. And you want some way of balancing things so that the enemy does not take a chance on that second-strike capability and nuke you first anyway. Then you need something to use them for. At the time, the targets would probably have been ports in the Baltic states, then (involuntary) parts of the Soviet union and likely starting points for the hypothetical Soviet invasion fleet. Could we really stomach the idea of killing a few thousand Estonian civilians, probably not too happy about being used as stepping stones by the Soviets? For most military targets, there are better weapons.

Of course, it has later been argued that by entering into various more or less hidden agreements with the US, we made ourselves nuclear targets anyway, with no formal guarantees whatsoever to show for it...
by CodingJeebus | 2026-01-26 17:46:08+00:00
I don't think that's really an apt comparison. Most software people who are in it purely for the craft are deep in open source, and open source doesn't necessarily build the most user-friendly tooling. If it did, you'd see apps like GIMP seriously challenging Adobe, etc. So much of the software layer built for enterprise and consumers relied on VC. I can only speak for myself, but I'd be willing to bet that 95+% of developers I've worked with would not build user-facing software for free. We are all in it for the money.