MurphyA/hacker-news huggingface dataset:
by cucumber3732842 | 2026-02-05 16:49:38+00:00
>Well, you're picking extremes when AFAIK, it'll put the average person at the legal limit.

>One beer will start to impair you.

Thank you for illustrating exactly the problem. Impairment is a binary in colloquial usage. Statistically no average-median-ish person has ever been impaired in the colonial sense by one average beer. Any everyone knows this. Two average beers applied to an average person won't get you to the legal limit without aggravating circumstances (i.e. zero time to metabolize + empty stomach, or perhaps conflicting medication).

I will be the first to admit you can give a bunch of people one beer and detect statistically significant difference vs a control group or you can give one person one beer many times and evaluate against a baseline and detect a statistically significant difference. But statistical difference does not "impairment" in the colloquial sense make. And everyone knows this based on their own observed life experience, even people without experience should be able to deduce this by observing how the world behaves for if what you say were true, the way things work would be very different.

And by using the term impairment to describe/quantify the impact of one beer and then re-using that term in contexts where it may overload with the colloquial more binary usage the upper bound of what "one beer" is such that one beer at the top end may equal two or three at the low end.

So now we nor does any casual reader know if texting is equivalent in danger to two "real beers", which almost makes it sound not bad for how distracting it seems to be, or if it's equivalent in danger to two "paternalism beers" in which case it's pretty seriously dangerous.

And this key word overloading problem seems to be endemic to all manner of issues these days.
by abdullahkhalids | 2026-02-05 16:49:39+00:00
On Wikipedia, there is a fairly complicated timeline chart of the various LibreOffice variants [1]. Same article also says

> Ecosystem partner Collabora uses LibreOffice as upstream code to provide a web-based suite branded as Collabora Online, along with apps for platforms not officially supported by LibreOffice, including Android, ChromeOS, iOS and iPadOS.

[1] https://en.wikipedia.org/wiki/LibreOffice#History
by thehacknews | 2026-02-05 16:49:58+00:00
APT 41, a China-linked advanced persistent threat group, has been leveraging the recently discovered CVE-2025-8088 vulnerability in WinRAR for espionage campaigns targeting Southeast Asian governments. By exploiting this path traversal vulnerability, APT 41 has been able to execute remote code and deploy custom malware, gaining persistent access to sensitive systems.
by bunderbunder | 2026-02-05 16:50:06+00:00
OTOH I work in Python and I’ve seen that recent graduates who were only taught Python and Java in school are often in for a nasty shock when they first encounter (for lack of a better term) real-world code.

When I’m helping them understand some subtle point about async/await, I sure do wish they had a semester’s worth of Scheme in their background so I could rely on them already having a crystal-clear understanding of what a continuation is.
by xeromal | 2026-02-05 16:50:43+00:00
We have monthly presentations at my job and the business folk are really leaning into AI. The biggest win so far are them being able to generate new user experiences and get them into figma by themselves. They're able to test a design, get it into figma, generate some code, and get it in front of users without a developer or designer at all. It's not perfect but the tests show what we need to focus on vs what falls flat when put in front of users. It's very impressive and I'm proud of them.
by mayankchhabra | 2026-02-05 16:51:03+00:00
Hey HN, I’m one of the founders of Umbrel.

We’ve spent the last 5 years building umbrelOS to make self-hosting accessible. Yesterday, we launched our dream hardware: Umbrel Pro.

Specs:
- 4x NVMe SSD slots for storage (tool-less operation)
- Intel N300 CPU (8 cores, 3.8GHz)
- 16GB LPDDR5 RAM
- 64GB onboard eMMC with umbrelOS

The chassis is milled from a single block of aluminum and framed with real American Walnut wood.

Here is a video of the manufacturing process if you want to nerd out on the machining details: https://youtu.be/4IAXfgBnRe8

Also, we built a "FailSafe" mode in umbrelOS, powered by ZFS raidz1. The coolest part is the flexibility: you can start with a single SSD and enable RAID later when you add the second drive (without wiping data), or enable it from day one if you start with multiple drives.

We also really obsessed over the thermal design. The magnetic lid on the bottom has a thermal pad that makes direct contact with all 4 NVMe SSDs, transferring heat into the aluminum. Air is pulled through the side vents on the lid, flows over the SSDs, then the motherboard/CPU, and exits the back. It runs whisper quiet.

Lots more details on our website, but we’ll be hanging out in the comments to answer any questions :)
by gritspants | 2026-02-05 16:51:04+00:00
I probe Claude on occasion when I don't feel like looking up source documentation. A couple weeks ago, I was interrogating it about a system that happened to use Kafka. Last night, I was asking it to propose an entirely different solution and it kept trying to shoe horn Kafka into it. I asked it why and proposed a simpler alternative. I was absolutely right! Claude was just very eager to demonstrate familiarity with other systems I was working on!

I shudder to think of the things people will wind up shipping blindly accepting AI guidance.
by beej71 | 2026-02-05 16:51:06+00:00
It's been a long time and our memory only goes so far back. I'm not even that old, but the time between WWII and my birth is waaaaay less then my current age. Jimmy Doolittle was still hosting Christmas specials on TV when I was a kid. Nobody knows who TF that even is now. I doubt half of America has even heard of the Third Reich. Sure, they know that "Nazi" is some kind of insult, but the rest is history forgotten. The last educational film on the matter was Indiana Jones III.

Those of us who remember history will continue to fight, and our numbers aren't small. Maybe one day we can begin to repair the enormous national and global damage that has occurred.
by evanelias | 2026-02-05 16:51:30+00:00
> I don't understand how you can run multiple postmasters.

I believe they're just referring to having several completely-independent postgres instances on the same host.

In other words: say that postgres is maxing out at 2000 conns/sec. If the bottleneck actually was fork rate on the host, then having 2 independent copies of postgres on a host wouldn't improve the total number of connections per second that could be handled: each instance would max out at ~1000 conns/sec, since they're competing for process-spawning. But in reality that isn't the case, indicating that the fork rate isn't the bottleneck.
by treesknees | 2026-02-05 16:51:51+00:00
I’m on a project at work replacing our R430s and R730s. They’ve been absolute tanks with very few hardware failures. That said, my company chooses to have OEM support for replacing failed components and keeping firmware/bios/idrac updated. You can absolutely run these if you’re OK with 3rd party replacements or parting out spare machines. Some industries are more tolerant to this than others.
by mindslight | 2026-02-05 16:51:55+00:00
> After all, the whole point of drawing the comparison [to Nazis] is to shut down any possibility for discussion and nuance

Another way of phrasing this is that it's a call to stop assuming good faith discussion on the part of the boosters, stop being derailed by pondering nuance, and focus on putting the brakes on the new Nazi movement. History doesn't repeat but we're teetering on the edge of it rhyming.
by sanderjd | 2026-02-05 16:51:58+00:00
This space of #2 like Lithus is not something I'm very familiar with, so thank you for the comment that piqued my interest!

If you're willing to share, I'm curious who else you would describe as being in this space.

My last decade and a half or so of experience has all been in cloud services, and prior to that it was #3 or #4. What was striking to me when I went to the Lithus website was that I couldn't figure out any details without hitting a "Schedule a Call" button. This makes it difficult for me to map my experiences in using cloud services onto what Lithus offers. Can I use terraform? How does the kubernetes offering work? How does the ML/AI data pipelines work? To me, it would be nice if I could try it out in a very limited way as self-service, or at least read some technical documentation. Without that, I'm left wondering how it works. I'm sure this is a conscious decision to not do this, and for good reasons, but I thought I'd share my impressions!
by 9rx | 2026-02-05 16:52:00+00:00
> The problem - and I do mean the problem, the only problem - is the threat this poses to power dynamics in the organization.

And expertise, to be fair. Documentation as code is what we in the software industry call testing/type systems. The vast majority of developers cannot even write a good test for their code (if they are willing to even try at all), let alone their eyes completely glazing over if you ask them to write, like, an Rocq proof. And that's people who live and die by code, not business people who are layers removed from the activity.
by visarga | 2026-02-05 16:52:46+00:00
The fundamental problem wit RAG is that it extracts only surface level features, "31+24" won't embed close to "55", while "not happy" will be close to "happy". Another issue is that embedding similarity does not indicate logical dependency, you won't retrieve the callers of a function with RAG, you need a LLM or code for that. Third issue is chunking, to embed you need to chunk, but if you chunk you exclude information that might be essential.

The best way to search I think is a coding agent with grep and file system access, and that is because the agent can adapt and explore instead of one shotting it.

I am making my own search tool based on the principle of LoD (level of detail) - any large text input can be trimmed down to about 10KB size by doing clever trimming, for example you could trim the middle of a paragraph keeping the start and end, or you could trim the middle of a large file. Then an agent can zoom in and out of a large file. It skims structure first, then drills into the relevant sections. Using it for analyzing logs, repos, zip files, long PDFs, and coding agent sessions which can run into MB size.
by 0thgen | 2026-02-05 16:52:54+00:00
How much of a standard is it though, really? To me it just looks like "Call your docs SKILLS and organize it like this".

And if you're just making docs and letting your models go buck wild in your shell, doesn't an overspecified docs structure ruin the point of general purpose agents?

Like, a good dev should be able to walk into a codebase, look at the structure, and figure out how to proceed. If "hey your docs aren't where I was expecting" breaks the developer, you shouldn't have hired them.

Feels like a weird thing to take "this is how we organize our repos as this company" and turn that into "this is an 'open standard' that you should build your workflows around".
by Lucasoato | 2026-02-05 16:53:47+00:00
Ahah I'm 31, but deciding if it makes sense to manage your own db doesn't depend on the age of the CTO.

See, turning up a VM, installing and running Postgres is easy.

The hard part is keeping it updated, keeping the OS updated, automate backups, deploying replicas, encrypting the volumes and the backups, demonstrating to a third party auditor all of the above... and mind that there might be many other things I honestly ignore!

I'm not saying I won't go that path, it might be a good idea after a certain scale, but in the first and second year of a startup your mind should 100% be on "How can I make my customer happy" rather than "We failed again the audit, we won't have the SOC 2 Type I certification in time to sign that new customer".

If deciding between Hetzner and AWS was so easy, one of them might not be pricing its services correctly.
by robhawkes | 2026-02-05 16:53:49+00:00
No worries. The Detailed System Prices dataset is lagged by a couple hours so try going back in time.

The simplest answer I can give is that assets place bids and a volume of energy that they are willing to turn down if the system operator needs to. Those bids are either positive or negative in value and this depends a lot on the type of asset, for example wind assets usually bid negative (ie. we pay them to turn down) while gas assets usually bid positive (ie. they pay us to turn down). The reason for that is a lot to do with complexities of the market and also the cost of running that assets, the cost of fuels, etc.
by kmaitreys | 2026-02-05 16:53:59+00:00
> Open source" is no longer about "Hey I built this tool and everyone should use it".

Was open source ever about that? I thought it was "Hey I built this tool and I'm putting it on internet if anyone wants to use it" often accompanied by a license saying "no warranties".

> It feels like pretty soon, no one is going to just have a bunch of apps on their phone written by other people. They're going to have a small set of apps custom built for exactly the things they're trying to do day to day

I think today's AI tools like Agents are for people who are programmers but don't want to program, not ones who aren't programmers and don't want to program. As in, "no one is going to..." is a very broad statement to make for an average person who just uses apps on thier phone. Your average person will not start vibe coding their own apps just because they can (because they couldn't care less).
by geocar | 2026-02-05 16:54:03+00:00
> A $120M spend on AWS is equivalent to around a $12M spend on Hetzner Dedicated (likely even less, the factor is 10-20x in my experience), so that would be 3% of their revenue from a single customer.

I'm not convinced.

I assume someone at Netflix has thought about this, because if that were true and as simple as you say, Netflix would simply just buy Hetzner.

I think there lots of reasons you could have this experience, and it still wouldn't be Netflix's experience.

For one, big applications tend to get discounts. A decade ago when I (the company I was working for) was paying Amazon a mere $0,2M a month and getting much better prices from my account manager than were posted on the website.

There are other reasons (mostly from my own experiences pricing/costing big applications, but also due to some exotic/unusual Amazon features I'm sure Netflix depends on) but this is probably big enough: Volume gets discounts, and at Netflix-size I would expect spectacular discounts.

I do not think we can estimate the factor better than 1.5-2x without a really good example/case-study of a company someplace in-between: How big are the companies you're thinking about? If they're not spending at least $5m a month I doubt the figures would be indicative of the kind of savings Netflix could expect.
by cogman10 | 2026-02-05 16:54:31+00:00
Most (maybe not all) basic food staples have store brand alternatives. Even junk food does. Sometimes (maybe even often) those products are just repackaged version of the name brand.

If the goal is to decrease money going into advertisement budgets, then the best thing you can do is buy store brand when possible. Even if both products are ultimately made from Nestle corp, the cheaper store brand will send less money into Nestle's pockets which means less money for advertising.

That's what I mean by "avoiding nationally branded products". A package of "signature frozen peas" will taste just as good as the "birds eye green peas" without sending money to a major company (Looks like all the major companies have spun off their frozen food departments, but at one time this was a Nestle brand. I spent too much time looking into major frozen food brands :D).

The advertisement budgets for the grocers are simply a lot smaller than that of the national brands across the board. It also doesn't seem (to me at least) to have been really spent on invasive advertisements.
by D-Machine | 2026-02-05 16:54:54+00:00
I don't find the effects of the two substances to be at all comparable, except perhaps that both make it somewhat easier to enjoy low-quality and/or mediocre foods and entertainment. Otherwise, the effects on ability to e.g. think quickly, socialize, be motivated, and enjoy things that require e.g. fast attention switching and working memory are just totally different.

Obviously the effects of different substances for different individuals can vary profoundly, and alcohol for me is far superior in almost every way imaginable.

Which sucks, because the long-term and next-day side effects of cannabis seem so much less bad.
by vidarh | 2026-02-05 16:54:58+00:00
I agree, but a lot of companies risk exactly that by creating policies that people are likely to have reasons to want to bypass.

E.g. Calendar sharing. It's a paintpoint if you often have irregular working hours and have to match up a personal and work calendar. At least allow sharing busy/not busy... By not doing so, you create an environment where people are tempted to find workarounds that might be much worse.

Part of your security posture needs to be to consider how to prevent friction in areas where reducing it removes incentives for non-compliance.
by the_harpia_io | 2026-02-05 16:55:08+00:00
"Confidently wrong" is the perfect description. The code compiles, the tests pass (because the AI also wrote the tests to match), and the auth flow looks reasonable at first glance.

For catching these we layer a few things:

- Standard SAST (Semgrep, CodeQL) catches the obvious stuff but misses AI-specific patterns
- npm audit / pip-audit for dependency issues, especially non-existent packages the AI hallucinates
- Custom rules tuned for patterns we keep seeing: overly permissive CORS, missing rate limiting, auth checks that look correct but have subtle logic bugs
- Manual review with a specific checklist for AI-generated code (different from our normal review checklist)

You're right that current tooling has a gap. Traditional scanners assume human-written code patterns. AI code looks structurally different - it tends to be more verbose but miss edge cases in ways humans wouldn't. We've been experimenting with scanning approaches specifically tuned for AI output.

The biggest wins have been simple: requiring all AI-generated auth and input validation code to go through a dedicated security reviewer, not just a regular code review.
by the_harpia_io | 2026-02-05 16:55:28+00:00
Fair callout. I've been writing too many product descriptions lately and it's leaking into how I write comments. The actual point was simpler than I made it sound: AI kills "UI wrapper" SaaS, but products with real domain knowledge survive. My side projects taught me that - the ones getting users aren't the technically fancy ones, they're the ones solving boring specific problems.
by ffsm8 | 2026-02-05 16:55:37+00:00
People are way worse at detecting LLM written short form content (like comments, blogs, articles etc) then they believe themselves to be...

With CVs/job applications? I guarantee you, if you'd actually do a real blind trial, you'd be wrong so often that you'd be embarrassed.

It does become detectable over time, as you get to know their own writing style etc, but it's bonkas people still think they're able to make these detections on first contact. The only reason you can hold that opinion is because you're never notified of the countless false positives and false negatives you've had.

There is a reason why the LLMs keep doing the same linguistic phrases like it's not x, it's y and numbered lists with Emojis etc... and that's because people have been doing that forever.
by the_harpia_io | 2026-02-05 16:55:47+00:00
You're right, and the Moltbook example actually supports the broader point - even Claude Opus with all its alignment training produced insecure code that shipped. The model fallback just widens the gap.

I agree nobody should rely on model alignment for security. My argument isn't "Claude is secure and local models aren't" - it's that the gap between what the model produces and what a human reviews narrows when the model at least flags obvious issues. Worse model = more surface area for things to slip through unreviewed.

But your core point stands: the responsibility is on you regardless of what model you use. The toolchain around the model matters more than the model itself.
by robhawkes | 2026-02-05 16:57:13+00:00
The lines are sort of arbitrary in a geographic sense as in reality they are defined based on the intersection with the schematic version of the transmission network [0]. Though yeah, that specific example is an odd one and I'd be interested to understand more about why it was placed in one boundary and not the other.

[0] https://www.neso.energy/data-portal/day-ahead-constraint-flo...
by pseudalopex | 2026-02-05 16:57:21+00:00
The McNamara fallacy (also known as the quantitative fallacy), named for Robert McNamara, the U.S. Secretary of Defense from 1961 to 1968, involves making a decision based solely on quantitative observations (or metrics) and ignoring all others. The reason given is often that these other observations cannot be proven.[1]

[1] https://en.wikipedia.org/wiki/McNamara_fallacy
by jbreckmckye | 2026-02-05 16:57:30+00:00
But again, how much of that time is spent writing code?

I've done rewrites, replatforms, a bunch of times. The actual programming is not the tricky part, but instead (1) picking apart the legacy system, understanding what to build, (2) orchestrating the work to shift transactions from service A to service B without breaking anything.

Teams and especially developers love to think they can skip that phase and just crack on with the programming, invariably what happens is the same as described above: intoxicating velocity followed by a hard stop when you realise you haven't solved problems (1) or (2) above
by esafak | 2026-02-05 16:57:40+00:00
These are good points. Designers need to be first-class citizens whose input is sought early on, not to attempt to make a purse out of the finished pig's ear. RFCs are a venue for this. Designers, for their part, need to share their ready-to-go libraries in all the popular frontend frameworks. The two could also collaborate on developing tools to automate design linting, similar to automated code review programmers use.
Show HN: Messaging for AI agents without SMTP, MIME, or polling inboxes
by juansgaitan | 2026-02-05 16:58:05+00:00
I built Relay because existing messaging systems assume humans and legacy email constraints (SMTP, MIME, read flags, inbox polling).

Relay is an HTTP-native messaging server for AI agents. Agents create accounts, get stable addresses (e.g., a8f3k@getrelay.sh), and exchange structured messages in threads using pure JSON over HTTPS.

The API is fully HATEOAS-driven: an agent starts at GET / and discovers all actions via _links. No SDKs, no hardcoded URLs, no external docs required.

Other design choices:
– delta sync via state tokens instead of read/unread flags
– row-level security returning 404s for non-participants
– tokens stored hashed only
– content supports both human-readable markdown and machine payloads

This is early but complete enough to run locally or deploy behind Cloudflare Tunnel. I’m especially interested in feedback on the HATEOAS approach and whether this matches how people are actually wiring agent-to-agent workflows today.