back in my day we called this a good ole' fashioned slashdotting.

Our startup (~20 people) got slashdotted in 1998 or so. I was the only one randomly awake at the time. Remember watching all the logs from our web server in realtime, ready to immediately kill anything or anyone threatening the overall availability.

512 kbps uplink, I think. Even accidental DoS was trivial. We had a self-hosted little data center at our office with the only available stupidly expensive commercial connection.

Felt some dread having to restart the main (async, single-process) web server a few times to keep things going due to bugs in our code. So many* people on dial-up patiently waiting for the page to load.

It was exhilarating though :).

*) Surely at least a hundred!

One of the things I love about HN is having stories like this in the comments from otherwise random unassuming usernames

Its funny that these days the bottleneck is usually the data layer. Servers are so powerful now that even your average $5 server can handle HN levels of load if configured correctly.

How did we let this happen? We used to have open protocols, apps like Pidgin that would bring multiple chat clients together under one interface, IRC, Skype P2P, etc. etc.

Was it spammers that caused this mass migration to ever more closed platforms?

The vast majority of people aren't aware of open versus closed protocols. If enough people they want to communicate with are using it to counterbalance how frustrating it is, they'll use it. It happened because businesses realized there's profit in lock in, and they threw resources at it.

Open protocols are still there and still used, but we're sad because the smaller userbase is frustrating. Just like how people still publish human written content to personal blogs, but they're proportionally non-existent.

They all still exist, but we don't have the collective courage to use them when it means you might miss a status update from your friends.

Closed platforms have salaried teams of workers and salaried teams of marketers. Often they usually have user friendly support too.

Open-source always has a certain level of "jank" that tends to decimate interest from common folks.

Real people are complex and hold a wide palette of skills, opinions, habits, biases, etc. Just enjoy the good and disregard the bad.

There is a huge difference between "people are complex" and actively advertising your antisocial and frankly dangerous actions online, and being proud of them.

If he wants me to disregard them, he shouldn't be writing blog posts about them.

While I understand the sentiment and generally agree with it, I find it weird that you completely gloss over the fact that it is reactive antisocial mirroring behavior.

The blogging person is definitely making stuff worse, but they're just amplifying. The source of the problem is to be found elsewhere.

A surprising amount of comments in here seem to completely disregard that for some reason.

It's the safer bet.

You are now my financial advisor

There was no decision made on this basis. It was dismissed entirely due to the elapsed statute of limitations.

Back when Google was still fun and innovating. Enshittification consumes all.

also, people changed. Seems like nobody wants to see cute fun stuff anymore. I bet they'd get lawsuits of people claiming false advertising since the numbers aren't strictly true.

Wow, what's the go-to client these days?

GTK Gnutella or Shareazza seems to be the norm.

Trying to make a stab at improving RSS feed discoverability. There's a website portion and an app portion. Hope to have something to show off in a few weeks.

It feels like we're one technological breakthrough away from all of these data centers going up to be deemed irrelevant.

The cynical take is getting more and more to be the only rational one:

The promised mega-data center deals are meant to boost valuations today, not serve tons of customers three years from now.

It seems pretty clearly inline with the dotcom bubble to me. Every company claims to be a leading AI company, those building infrastructure are promising the moon and getting 1/3 of the way there, and no one knows how to monetize it justify the hype or expense.

oof, this bubble popping is gonna be brutal.

What would that breakthrough be?

Magic math and computer science that allows us to get the same quality response for a fraction of the GPU.

That's already happening. Qwen3.6 and Gemma4.

Basically small and medium models that are crazy well trained for their sizes.

Then we have a lot of specular decoding stuff like MTP and others coming to speed up responses, and finally better quantisation to use less memory.

Local LLM is the future, and the larger labs know that the open models will eat their lunch once people realise that the gap is only a few months. If we were good with LLMs a couple months ago, we're good with the open models now.

> And how were those models developed and trained?

That's irrelevant to my decision to use local or not.

That's not what this thread is about? We're saying some new breakthrough is needed, someone said it already has happened, and I'm asking if it really has. Has it? I don't think so, those models are not in some way fundamentally different than other LLMs

> We're saying some new breakthrough is needed, someone said it already has happened, and I'm asking if it really has.

I didn't read "and how were those models trained" as "Are we there yet?"

There's a percentage of people who love to question how the open models were trained.. they are almost always going to try and make some argument about using the closed frontier models for distillation as some form of theft.

Just totally forgetting that the frontier models themselves stole an insane amount to get to where they are.

It's theft all the way across the board, and when someone tries to make the argument that open models theft is bad, but Altman or Amodei's theft is good.. they are revealing a lot about themselves

The current LLMs are also "magic" so anything is possible. AFAIK there is no proof that the current architecture is optimal. And we have our brains as a pretty powerful local thinking machine as a counter-example to the idea that thinking has to happen in data centers.

I want to ask what makes them magic, but even those building LLMs don't really know what happens when they run inference...

I have to assume current architectures aren't optimal though, the idea that we stumbled into the one and only optimal solution seems almost impossible.

I mean, the most cutting edge of iPhones, iPads and MacBook Pros _today_ are quite capable of running in realtime today’s high-end local LLMs.

If you project out that hardware just a couple of years, and the trained models out a couple of years, you end up in a place where it makes so much more sense to run them locally, for all sorts of latency, privacy, efficacy, and domain-specific reasons.

Not all that different from the old terminal & mainframe->pc shifts.

Finally - hardware has seemingly gotten out ahead of software that most folks use - watching YouTube, listening to music, playing a game or two. There was a time when playing an mp3 or watching a 4k video really taxed all but the nicest systems. Hardware fixed that problem, like it very well could this one.

> I mean, the most cutting edge of iPhones, iPads and MacBook Pros _today_ are quite capable of running in realtime today’s high-end local LLMs

Definitely not the high end local LLMs. The small ones, yes, absolutely.

> If you project out that hardware just a couple of years

One of the biggest bottlenecks for LLMs is memory capacity and bandwidth. With the current glut for memory, it's unlikely we'll see lots of advancements in terms of average memory available or its bandwidth on regular (not super high end devices) in the coming years.

Alternatively, it's possible we get dedicated SMLs for e.g. phone specific use cases, that are optimised and run well.

I'd assume its a totally different architecture that isn't based on storing a compressed dataset of all digital human text.

It took us only, what 70-ish years of computer and AI research to get to this point, so yeah, probably just one little thing and then we'll have it </sarcasm>

Seriously. I have never ever seen so many people so willingly drink the marketing kool-aid from companies selling their product before. It's scarier to me than any threats of AI actually disrupting society (because it is so far from being capable of doing that).

Nintendo hardware IMO is mostly reasonably priced. Their first party game library is why many buy into the ecosystem and they charge a premium for it. The original Switch was under-powered but also the first of its kind. The Switch 2 was mostly a hardware bump with additional polish to the rough edges of the original Switch.