eulgro

Given that they open sourced their inference framework, how realistic would be to buy hardware and become a provider on OpenRouter? These numbers are incredible.

At 20 kW average consumption per WSE-3T wafer this gives roughly 1.18 MW for the whole system. Assuming 1500 tokens per second and 190 concurrent requests this gives 4.1 J/token. Which is good I suppose for the size of the model?

Your comment makes no sense. How and why would a local model be nerfed anyway...?

> Pull the key, stop the process.

The agent could very well create an OpenRouter account and make its own API key. I can stop it early on, then it becomes outside my control.

> Just don't ever do such an experiment

Maybe I wouldn't, but eventually someone will. Certainly it has already been done.

> there was a day in the early internet when a worm took over, and to fix it the entire internet had to shut down

This is less of an option now that the entire global economy relies on the Internet.

1. They are all saying AI is a danger to humanity, but no one is willing to give the slightest details about how exactly the threat will materialize...?

2. Nor are they willing to consider the possible remedies in case the threat materialize (presumably unplugging the server infrastructure that's consuming gigawatts)...?

3. They all keep working towards advancing AI despite believing that it might end humanity in the near future...?

I can't even begin to imagine where the threat to humanity lies. A threat to employment maybe, but that's completely different.

The worst for astroturfing I think is Kagi. Everytime a post comes up l, every comment is like "Kagi is so great yada yada", often totally unrelated to the article, with little comments mentioning negatives or commenting on the article.

Like, who even use a search engine at this point, let alone pay for it.

If this happens with a minor search engine I'm pretty sure it happens with a lot of other products, starting with AI models.

How can you afford to burn $50k on an already solved problem?

1. Us 2. Us

We've been seeing that headline for a few weeks now and I really don't understand the problem.

Companies are paying for the books now, great! And destroying a book is really the best way to scan it. I could destroy the books I buy myself if I wanted, they're my books and I can do whatever I want with them. A book is really just a stack of paper, I don't get the sacred feeling attached to it. Especially since books are printed in thousands to millions of identical copies nowadays.

Now what books exist in a single copy that destroying it would amount to losing knowledge? In any case, I would also expect such books to be very old, have very little useful content for training to start with, and be expensive enough to buy to make training on them unprofitable.

So what's the problem here exactly?

Also from the article:

> It’s outrageous is that it’s legally permissible, but ethically, it’s an extremely serious crime against humanity.

I'm all love for Anna's archive, but still, I find it rich that they now find themselves in position to make strong ethical claims.

> he inhaled a peanut butter and jelly sandwich at the kitchen table

Well that can't help for sure.

Unfortunately for some problems like climate change, improving 1-2% per year starting today still leads to disaster.

They fell in love with the money.

The website is unusable, scrolling is slow as hell.

> loading a few thousand tokens of raw JSON into a context window, asking a language model to reformat data it did not need to reason about...

> That trap catches almost everyone right now.

Has everyone really become so stupid now? I wouldn't even have thought of doing such a horrible thing as using AI to format JSON...

Needless to say I stopped reading there.

Yeah we can do really weird things with op amps, negative resistance and capacitance comes to mind.

That's less productivity for same pay. We can have less work without impacting productivity much.

Unfortunately that's not how it works. Productivity gains have already increased tenfold in the past, yet still all work full time.

It used to be that 80+% of the population worked in agriculture. In developed countries that number is now around 1-2%. Some of the freed labour was funneled into improving living standards, some of it was funneled into new jobs created by the increasingly complex society (the "intermediate economy").

With AI, the same is true: labour is freed by the productivity gains (which I doubt are 10x sustainably but whatever), more labour is needed for power generation, mineral extraction, maintaining this new extra layer of complexity in the intermediate economy, etc. In the end we might see, say, a net 3% increase in global productivity per year over the next 10 years, which will be funneled into increasing living standards and increasing economic inequalities, but not in reducing working hours.

If you accept living below average standards, you could easily work a single day of the week for the rest of your life. But why would an employer hire 5 people working one day a week, instead of one working 5 days a week? They won't, hence we don't see a reduction in working hours.

The alternative is to work full time but retire earlier, much earlier, than you would otherwise, which in the end is the equivalent of having worked one day a week for your whole life.

I highly recommend reading Lean Logic by David Fleming, it explores several of these concepts in a very interesting way.

These satire articles on cybersecurity are really entertaining.

The other one a few days ago was also good: https://nesbitt.io/2026/02/03/incident-report-cve-2024-yikes...

I enabled it and I had to read carefully to check if it was really active... turns out I never read the words that caveman omits, so to me it makes zero difference.

At what point does milk become oil?

The law of supply and demand works in a perfect competition market.

There are two RAM suppliers...

> The report estimates that carbon emissions from models with the least efficient inference are over 10 times as high as those with the most efficient inference. DeepSeek’s V3 models were estimated to consume around 23 watts when responding to a “medium-length” prompt, while Claude 4 Opus was estimated to consume about 5 watts.

This makes absolutely no sense. I suppose they meant watt hours, and that's a weird way to explain carbon emissions...

And vegan of course

It's impressive how much details they give in the release notes, down to the filenames of added sprites and changes to the shaders. I can't think of another game that does that.

The channel owner seem to be a non-speaking person so that explains it.

In science fiction maybe. We're hitting real limits on compute while AI is still far from a level where it would harmful, and FHE is orders of magnitude less efficient than direct calculation.

That's 58 GWh, but considering each food calorie actually require 5-10 calories of input energy (oil mostly), let's say 290 GWh.

I couldn't find much on training AI models. Apparently GPT-3 used 1.3 GWh for training. So maybe ~10 GWh for newer models?

So... let's stop training humans I guess.

To be honest, these all seem like pretty basic features.

Goto is easier to implement than an if statement. Postincrement behaves no differently in a switch statement than elsewhere.

This makes no sense. With the li-on batteries you would need everything you listed, minus the extra batteries.

Well there is. The three/five fold rule. And 50 moves rule.