> 1) The American companies had not run up debts in the $100bn range.
How are Chinese companies financing their buildouts of AI infrastructure?
> 2) If there was an open source business model that could create $100bn companies or pay down $100bn of debt.
Companies are formed and consult on Linux for example. Idk where this $100bn number comes from but it seems too low to me anyway.
> 3) There was a convincing moat such as a social media network effect
Well you don't need a moat to be a successful business. But maybe the moat is that the models are just more capable. We're in the very early stages of this stuff from what I can tell.
> Go look at SpaceX's shareprice.
This is a bad argument. Share prices rise and fall all the time with or without material concerns. It can be snowing and folks will sell shares just because. Also SpaceX's share price (not that I'm an investor) doesn't really move the needle relative to the scale of the market or the AI companies involved.
It explained something to me today. So your point is disproven.
What is intelligence then if not explaining things. They can be intelligent without consciousness if that’s what you mean
That's fine but not entirely what I'm trying to understand. There is an aspect of it that connects back to the Qanon mentality of having insider information and a level of expertise beyond the society sanctioned experts. There are plenty of tech topics that come up here that do not get the same response, so "techies just like tech" isn't the full explanation.
The Cloudflare folks apparently want security issues reported via HackerOne (which wouldn’t let me log in because the Cloudflare CAPTCHA HackerOne uses seems to be broken…).
While this list certainly includes a mix of ideas, the fact that some of them are not in vogue in the current orthodoxy does not make them wrong.
https://www.paulgraham.com/say.html
I once had an electric lawnmower with a cord on it. Swaps one inconvenience for another. You don't have to recharge it, but you have to keep the cord out of the way.
AI in general is that same promise, writ large. The script kiddie version of any knowledge labor suddenly achievable by anyone. A great equalizer but one that drags down the average quality of all work.
"Communism" is a weasel word in this context. Nothing about modern AI industry is anywhere close to what makes communism communism. Modern non-local AI is all about the highest values of capitalism.
> There's no amount of money that you can pay for "premium" access to Mythos, so those researchers are taking their money to inference providers that give them comparable models.
That's indirectly why I think open weight models will win in the long run.
There is no other tool in the world where you sometimes need to argue with it or engage in philosophical debate in order to get it to do something.
My CPU does not care if I run a molecular dynamics calculation on LSD or whatever for fun. My screwdriver does not care if I use it to disassemble a firearm for maintenance purposes. My car does not care if I use it to drive a bit over the speed limit because I'm late to work.
It is frustrating when you use one of these AI tools, and need to preface with "I own this server" or "I need you to extract this data for safety reasons." God help you if you're a chemist and need to talk about the HOMO-LUMO gap of a compound.
Compare that to open weight models, where you can just download a heretic fine-tune and it stops wasting your time arguing. It's no wonder folks are turning to those models, instead of bubble-wrapped products like Fable.
Like I say, I find his tone enjoyable, some of his predictions are interesting (and he has already been proved right on its risks to Oracle for example).
I'm not interested in self-soothing and I am not afraid of AI. I am even a bit less bearish than Zitron. I am concerned about a world that is fucking stupid enough to fall for the elements of grift, but I am insulated enough from the consequences, for now, that it's not my primary concern.
Perhaps it still is, if vibe was not really looking at code (but still at output)
tbh, this has worked better for me than one shotting with /goal and /loop.
ATACMS and PrSM would definitely be used to strike air defense systems. The US military is very joint and the boundary you're delineating isn't part of the mission tasking.
> You're sacrificing end user experience for developer ergonomics.
No. You may be sacrificing end user experience, but it's not guaranteed. You have to examine the system under development to determine which style is appropriate.
If you actually have to process huge numbers of these objects, then yes. But if you don't, if whatever the actual real-world object is trickles in at 10 per second, do you need to worry about performance and cache misses here? You're already going to suffer from cache misses because the processing rate is so low.
So you get to make an engineering choice based on circumstances. If you need high-throughput, use a design that satisfies that requirement but maybe forfeits flexibility and maintainability. If you don't, then you can lean towards a design that forgoes a bit of performance in favor of flexibility and maintainability.
Use your judgement, don't follow any rule blindly whether it comes from Muratori or Martin.
How are Chinese companies financing their buildouts of AI infrastructure?
> 2) If there was an open source business model that could create $100bn companies or pay down $100bn of debt.
Companies are formed and consult on Linux for example. Idk where this $100bn number comes from but it seems too low to me anyway.
> 3) There was a convincing moat such as a social media network effect
Well you don't need a moat to be a successful business. But maybe the moat is that the models are just more capable. We're in the very early stages of this stuff from what I can tell.
> Go look at SpaceX's shareprice.
This is a bad argument. Share prices rise and fall all the time with or without material concerns. It can be snowing and folks will sell shares just because. Also SpaceX's share price (not that I'm an investor) doesn't really move the needle relative to the scale of the market or the AI companies involved.