The amount of Trump dick sucking surprises me, too. It certainly felt more intelligent 20 years ago.

Speaking of Trump dick sucking, did you figure out yet if he sucked off a CEO, a president, or a horse yet?

He's just being a typical American MORE BIGGER FASTER tool. I drive an 08 Versa with a 1.8l with 122hp and I have absolutely no problem being one of the fastest people on the road, because even a slow ass car by modern standards can do all the things. I never have trouble getting up to speed on a ramp or whatever.

Really shitty. I'm arrogant so I do want to point out the obvious: Trump won the primaries and became the candidate for the Republican team because the Republican party is shitty.

Both parties are really shitty.

Putin is so smart he outsourced his destroy America plan to Trump

That's an example of why they have really bad messaging, because they are more interested in politics than in science/reality. That leaves room for someone like Trump (the reality TV star) to do better messaging.

Biden/Harris were going around saying they wouldn't trust the vaccine. Governor Newsom was throwing large dinner parties after telling everyone to socially isolate. That's a strong indicator of people who don't care about science, and that's why they can't do better messaging than Trump.

The problem with free form worlds is they invariably turn into some kind of crappy reality TV show. That's the only way most people know how to interact with each other.

A clear example is the messaging on vaccines and masks. These aren't a matter of scientific debate: if everyone wears a mask and gets vaccinated, the pandemic will be slowed.

But, somehow it turned into "Biden is forcing us to do ..." whereas with a little better messaging, only crazy people would have minded. The problem wasn't the message, it was the way the message was delivered.

You should probably put more effort into winning the election next time.

Trump is what you get when your party sucks at communicating.

Yeah, it's not personal, I just feel like you've been caught up too much in the AI hype and that clouded your vision. You are definitely a net positive in the conversation: with interesting ideas and a (unfortunately not more common) ability to actually look things up and learn.

The AI problem will resolve itself automatically in the next few years (either the AI hype will die out or strong AI will be invented; one way or another.)

Yeah, it's not even worth considering for something like 15-20kg. A full pallet in this case is 464kg :) Years worth of supply for me.

The current "AI" is a predictive engine.

And *you* are a predictive engine as well; prediction is where the error metric for learning comes from. (I removed the word "search" from both because neither work by "search". Neither you nor LLMs are databases)

It looks at something and analyzes what it thinks the result should be.

And that's not AI why?

AI is, and has always been, the field of tasks that are traditionally hard for computers but easy for humans. There is no question that these are a massive leap forward in AI, as it has always been defined.

It is absolutely crazy that we are all very very soon going to lose access to electricity

Calm down. Total AI power consumption (all forms of AL, both training and inference) for 2025 will be in the ballpark of 50-60TWh. Video gaming consumes about 350TWh/year, and growing. The world consumes ~25000 TWh/yr in electricity. And electricity is only 1/5th of global energy consumption.

AI datacentres are certainly a big deal to the local grid where they're located - in the same way that any major industry is a big deal where it's located. But "big at a local scale" is not the same thing as "big at a global scale." Just across the fjord from me there's an aluminum smelter that uses half a gigawatt of power. Such is industry.

That "ruler study" was ancient. It's mentioned in peer review at least as early as 2018, and might be even older.

Believe it or not, people in the field are familiar with these sorts of things that you just read about.

Most of these new AI tools have gained their new levels of performance by incorporating Transformers in some form or another, in part or in whole. Transformers is the backend of LLMs.

Even in cases where Transformers isn't used these days, often it's imitated. For example, the top leaderboards in vision models are a mix of ViTs (Vision Transformers) and hybrids (CNN + transformers), but there are still some "pure CNNs" that are high up. But the best performing "pure CNNs" these days use techniques modeled after what Transformers is doing, e.g. filtering data with an equivalent of attention and the like.

The simple fact is that what enabled LLMs is enabling most of this other stuff too.

Jevons Intensifies