And both of them are wrong, because they _should_ be trying to figure out what works best for the person; not what worked best for _them_ and forcing it on the person.
There main problem, at least in my experience, is that there's a direct conflict in it
- There are people that work better from home and get more done there
- There are people that work better in the office, with people around them
Regardless of which you pick, you're going to make one of those groups less productive.
I do agree that some people who want one thing but work better with the other. It's on the manager(s) to figure out which works before; for each individual and for the team.
When you look at each dimension in isolation, the difference is fairly small. But the 12” is 60% of the volume and 75% of the weight of the Neo. It’s significantly more portable by these metrics.
> Why are we all whispering about how profitable all this is?
Nobody is whispering about anything. Everyone is loudly assuming what's convenient for their thesis. Even if you have access to the books, the accounting isn't straightforward–there are yet insufficient data for a meaningful answer.
> It is the absolute last thing these firms would keep secret
If you find an optimisation strategy that you don't think your competitors have, you absolutely keep your margins secret for as long as possible. Knowing something is possible is the first step to making it so.
Based on what I said. If e.g. Sonnet (assuming it’s significantly smaller than Opus) is unprofitable why are there a bunch of inference providers on OpenRouter serving very large models way cheaper? They don’t have a pile of money to burn for no reason.
There are plenty of various providers on OpenRouter serving very large Chinese models like GLM for a fraction of what OpenAI/Anthropic. Presumably they are making a profit.
It’s unlikely that Claude is proportionally that bigger and more expensive to serve so profit margins on inference must be pretty decent
Do we know they are making a profit though? They could be subsidizing use to build market share the same way. They might not have billions, but at the volumes they are selling maybe they’ve got the cash to do it.
Even if they are “profitable” how many Uber drivers are “profitable” because they aren’t correctly calculating asset depreciation. Maybe these guys are doing the same thing.
Maybe it’s a lot of people who already had GPUs for crypto mining, and they’ve moved over to this, so that if they need to grow and buy new GPUs the costs would dramatically grow.
also, it's very much possible that the chinese companies get heavy investments from the state. Since it's very hard to get this info we have no idea wether they really make a profit or not.
I agree, and find that very plausible. I mean, for the CCP a few billions to subsidize domestic AI companies is a tiny investment with a potential huge payoff. It prevents (or at least make it harder for) US companies to build a monopoly on LLM tech and it could help popping the bubble which would weaken the US economy. In fact, if I remember correctly, the AI infrastructure build-out is what is keeping the US from a technical recession.
> subsidizing use to build market share the same way
To an extent maybe, but that market is almost entirely commoditized already. Besides Cerebras and maybe Groq (which already charge a slight premium) all the other providers are more less interchangeable.
> Maybe it’s a lot of people who already had GPUs for crypto mining
I’m not sure the type of GPUs that were most popular for crypto are at all useful for LLMs?
If there’s a few providers subsidizing, that’s the price ceiling. Everyone who wants to compete has to subsidize.
Now if this market had been operating for years, I’d say that it’s likely all these companies are profitable or close to it. But the market is so new and there’s so much hype, I find it very plausible that none of these guys are making a profit and they all hope to just hang in until all the subsidies go away.
> I’m not sure the type of GPUs that were most popular for crypto are at all useful for LLMs?
There’s some overlap. I’ve definitely read about people repurposing.
>There is a huge difference between supporting the regulation of algorithmic feeds and other dark patterns and a direct attack on personal privacy.
Normies don't see the difference and politicians don't want there to be a difference. Normies want security and politicians will offer it wrapped in surveilance.
Even a 2015 MacBook for me ran the fan hard almost constantly. First Apple silicon MacBook was silent. Now using an M1 Max MBP from 2021 and external hard drives are the thing making noise on my desk.
It’s hard to believe those type of people actually wanted to replace it with non European immigration, though (which is what happened). Of course cause and effect is a complex concept to wrap ones head around..
Poles return to Poland and get to see results of their hard work. Brexit people get exposed to more cultures. I guess everyone got what they needed and deserved.
I think Zurich is in a slightly different league than London or Amsterdam in that regard but especially if you go down to the median and below (low taxes are helpful as well)
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