I founded a UG and a GmbH in 2024. It took me 3 months total including visits to the notary (who charges a non-insignificant sum for their services).
I did this as a subsidiary for a US company and literally had to email and call people every few days to move the process along (mostly, it was the banks who somehow expected us to be a multi-national company and wanted to charge an arm and a leg just to let us open a bank account. Most banks outright refused us).
When the notary finally filed the paperwork to the court, the court replied after a few weeks with additional clarifications for which we had to go AGAIN to the notary to do the whole song and dance of them chanting at us in German at 1000 words per minute.
Everything took painfully long and delayed investment for while. People have absolutely no idea how painful it is to merely have the incorporated entity available. Then, it takes a few weeks to get your tax ID - this is when you can start employing people / accepting payments etc.
The bank issues/refusals may have something to do with FATCA. If you have anything to do with the US in terms of taxes, many EU banks don’t want you as their customer. If it’s a subsidiary of a foreign company, then a lot of paperwork is required to prove that the foreign owners actually exist.
My dev friends could find English speaking jobs but everyone else is struggling. Some are moving away, compromising, or nervously watching the end date of their unemployment insurance. The salaries actually went down since last year if I'm not mistaken.
Most people actually using python do not start off in scripts. Usually, I would mess around in IPython / Jupyter for a couple days until I have something I'm happy with. Then I'll "productionize" the project.
tbh this has been a sticking point for me too with uv (though I use it for everything now). I just want to start of a repl with a bunch of stuff installed so I can try out a bunch of stuff. My solution now it to have a ~/tmp dir where I can mess around with all kinds of stuff (not just python) and there I have a uv virtualenv installed with all kinds of packages pre-installed.
> Usually, I would mess around in IPython / Jupyter for a couple days until I have something I'm happy with. Then I'll "productionize" the project.
Right, it's this. I get the feeling a lot of people here don't work that way though. I mean I can understand why in a sense, because if you're doing something for your job where your boss says "the project is X" then it's natural to start with a project structure for X. But when I'm going "I wonder if this will work..." then I want to start with the code itself and only "productionize" it later if it turns out to work.
>tbh this has been a sticking point for me too with uv (though I use it for everything now). I just want to start of a repl with a bunch of stuff installed so I can try out a bunch of stuff.
I hope the people behind UV or someone else adress this. A repl/notebook thing that is running on a .venv preinstalled with stuff defined in some config file.
> A repl/notebook thing that is running on a .venv preinstalled with stuff defined in some config file.
So, create a project as a playground, put what you want it to include (including something like Jupyter if you want notebooks) in the pyproject.toml and... use it for that?
What do you want a tool to do for that style of exploration that uv doesn't already do? If you want to extract stuff from that into a new, regular project, that maybe could use some tooling, sure, that would take some new tooling.
Do you need a prepackaged set of things to define the right “bunch of stuff” for the starting point? Because that will vary a lot by what your area of exploration is.
Until the rug inevitably gets pulled on those as well. It's not in your interest buy a $200/mo subscription unless you use >$200 of tokens per month, and long term it's not in their interest to sell you >$200 of tokens for a flat $200.
> It's not in your interest buy a $200/mo subscription unless you use >$200 of tokens per month
This is only true if you can find someone else selling them at cost.
If a company has a product that cost them $150, but they would ordinarily sell piecemeal for a total of $250, getting a stable recurring purchase at $200 might be worthwhile to them while still being a good deal for the customer.
The pricing model works as long as people (on average) think they need >$200 worth of tokens per month but actually do something less, like $170/month. Is that happening? No idea.
Maybe that is what Anthropic is banking on, from what I gather they obscure Max accounts actual token spend so it's hard for subscribers to tell if they're getting their moneys worth.
Well, the $200/mo plan model works as long as people on the $100/mo plan is insufficient for some people which works as long as the $17/mo plan is insufficient for some people.
I don't see how it matters to you that you aren't saturating your $200 plan. You have it because you hit the limits of the $100/mo plan.
I don't know about for people using CC on a regular basis, but according to `ccusage`, I can trivially go over $20 of API credits in a few days of hobby use. I'd presume if you are paying for a $200 plan then you know you have heavy usage and can easily exceed that.
No way to measure it directly, but it did write 4kLOC of mostly working angular... whether non-max would manage the same feat in the same time is an open question.
It depends on the salary, right? If you're in Silicon Valley paying 500k TC it probably makes sense to let your employees go wild and use as much token spend as they like.
RLHF is not the "RL" the parent is posting about. RLHF is specifically human driven reward (subjective, doesn't scale, doesn't improve the model "intelligence", just tweaks behavior) - which is why the labs have started calling it post-training, not RLHF, anymore.
True RL is where you set up an environment where an agent can "discover" solutions to problems by iterating against some kind of verifiable reward AND the entire space of outcomes is theoretically largely explorable by the agent. Maths and Coding are have proven amenable to this type of RL so far.
