reconnecting

WOW! Your FatalVision (1) is absolutely shiny! Wish I'd had it in the 90s.

Respect for the file_id.diz (2)! I thought mine was the last one on GitHub.

1. https://github.com/ssg/fatalvision

2. https://github.com/ssg/fatalvision/blob/master/file_id.diz

Guys, I don't get it.

Were you all node sysops, or did your region just not have that last part — the point?

Zone:Net/Node.Point

Similar situation, except they know from the beginning that I'm 14, and they drink a lot of beer while I don't.

Thanks for letting me know.

Sysop?

FidoNet was my first network. I still remember the sysops and the parties.

An interesting aspect is that it was impossible to obtain an address without providing some service or newsletter on a specific subject to the sysop in return, so it was a privilege to have your own FidoNet address.

The true crime is involving a multinational corporation in a transaction between two private individuals at the local market.

I like cash because it's direct, and where possible I avoid paying by card because I don't want the merchant to pay fees to third parties.

In Europe, most of the time, using cash doesn't imply avoiding taxes on the transaction, but having cash is essentially sovereignty.

Thanks! You probably mean page zoom-out on Android because of the viewport. Should work now.

True. We have a product website (1) built entirely with tables and HTML 4.01 (2) in 2026. Works as expected everywhere.

1. https://www.tirreno.com

2. https://validator.w3.org/check?uri=https://www.tirreno.com/&...

> Fun fact: a chunk of Odysseus was built *from a phone* -- mobile shells (Termux), the PWA install, and on-device agents. So "works on mobile" isn't an afterthought, it's where a lot of it actually happened.

https://github.com/pewdiepie-archdaemon/odysseus/commit/0517...

Perhaps the downvotes come from scammers.

To the platform, the difference shows up exactly in the mitigation math. The 'make it cost more than it's worth' model only works when both sides of that ratio are knowable and bounded. With bonus abuse, the reward is fixed and the math is clear, so you can reliably price the abuser out.

With organized criminals, you can't actually see what the abuse is 'worth' to them. And they can escalate almost infinitely: mimicking real user behavior, routing through residential IP proxies, using email addresses with established reputation, and at the top of the pyramid we've seen full mimics with real social network profiles and activity, they even answer phone calls.

That's why it's worth collecting events before acting: what the account is about, which IP network they use, whether they fake devices, whether there's any warmup prior to registration. Because that's what helps estimate whether your mitigation will actually work, and lets you respond in a balanced manner instead of under- or over-reacting.

You're mixing up bonus abuse here. The people behind phishing are more like hackers, whereas bonus abuse is usually run by non-technical people or bot farms. Scammers are much more dangerous, because they're typically behind operations far wider than just phishing, this might include actual financial fraud, international money laundering, and so on.

Bonus abuse is a small shop, whereas phishing through third-party services is much more likely to be an organized crime group.

Captcha here will only harm your real users' experience and won't protect against this kind of abuse, since it comes from real scammers, not fully automated bots.

I've dealt with these and similar issues over the last 8 years, which led our team to develop a security tool 5 years ago that is now open-sourced.

https://github.com/tirrenotechnologies/tirreno

Nice nickname btw.

There is nothing to Show HN (1).

1. https://news.ycombinator.com/showhn.html

It seems like a perfect ouroboros illustration for the current world.

AI creates a delusional product, people don't trust their own opinion regarding it and follow it, another AI is needed to prove that the product is unreal.

In the loop.

On the other hand, there are 8,400 forks, and it looks very real, so developers seem to have confidence in it.

> I think AI tools are more like Iron Man's suit.

There's an interesting repository with 63600 stars on GitHub (1). The developer of the repository is No 1 at the GitHub's trending contributors list (2). However, it seems like the application isn't what it's described to be (3), and the developers, on their end, are unable to clearly answer whether this is real or not, as it's just messy LLM output.

Proof that the suit alone doesn't make anyone Iron Man.

1. https://github.com/ruvnet/RuView

2. https://github.com/trending/developers?since=weekly

3. https://github.com/deletexiumu/wifi-densepose

> while neither model included your product in it's initial response, when I followed up with "what about open-source"

You just proved that LLMs don't know about the product (which is fine), but they don't even know the category exists.

It's like driving a car whose mirrors show a two-year-old reflection and insisting they work fine.

Until they prefer not to search. Let me explain using the example of the open-source security framework (1) our team is working on.

If you ask Gemini what you should use to integrate fraud prevention or account takeover protection into your product, there will be no mention of our open-source project. Five years in development, 1.3k stars, over 140 pull requests — all this isn't enough to make it into the training data. From this perspective, any technology that emerges after 2024 is simply invisible to LLMs.

The answer is: without being in the training data, LLMs basically don't understand what they're searching for.

1. https://github.com/tirrenotechnologies/tirreno

> it maybe doesn't even matter that the models are using older data.

This actually really does matter. Otherwise, the model simply won't know about your product and will always suggest only a few market leaders.

Searching for information on the Internet became a jungle a decade ago, and to be visible you have to pay Google for sunlight. Now, we risk falling into real darkness — until some paid model eventually emerges. This might be the reason Google is fine with training data from 2024. If the top spot is reserved for whoever pays anyway, why bother?

LLM pre-training models risk being unable to be updated with data from after 2025, as much of it is corrupted with LLM-generated content. We might be locked into outdated knowledge, where only whitelisted sources decide what to include.

Taking into account the sometimes blind belief that 'LLMs know everything', the outcome could be very costly, especially for technologies and businesses unfortunate enough to emerge after 2025.

Knowledge cutoff: January 2025

Latest update: May 2026

I have a very bad feeling about this lag.

Perhaps this was prior to shakti times.

I have a letter from Mr. Whitney, and I'd say he doesn't use the shift key at all, therefore I assume it's k.

I don't see how this codebase could possibly be "inspired on K" (as the author writes). k is known to have ascétique aesthetic.

Also, it's `k` as per Arthur Whitney's website (1).

1. https://k.nyc/

Anytime, buddy!

   DEVICE=C:\DOS\HIMEM.SYS
   DEVICE=C:\DOS\EMM386.EXE NOEMS X=D000-DFFF

   BUFFERS=30
   FILES=40
   FCBS=4,0
   STACKS=9,256
   DOS=HIGH,UMB
   LASTDRIVE=F

Simply because people prior to VC used time to make fun stuff. After VC came in and bought up that time to make more money, the fun stuff disappeared.

Since <BLINK> is gone, `BEHAVIOR=SLIDE` is the closest you'll get.

<MARQUEE DIRECTION="DOWN" BEHAVIOR="SLIDE">Slide</MARQUEE>