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And then you just use your favorite js framework with Astro and it will still be good. I use Astro with react and heroui a lot. Since the latter does not need any js for many components anymore you still get zero js builds unless you actually need interactivity.

But did you use ChatGPT chat or the work mode? Only the former is unmetered at least for me as well.

We do very much have credit rating in Germany, might be very different than the one in the US, don’t know theirs.

Are you may be comparing the pro model to the non pro model with thinking? Granted it’s a bit confusing but the pro model is 10 times more expensive and probably much larger as well.

You can activate the uv venv from anywhere just fine, just do source path_to_sandbox/.venv/bin/activate. Probably makes sense to define a shortcut for that like activate sandbox. Your conda env is also linked to a directory, it’s just a hidden one, you can also create the uv obe somewhere hidden. But I get it to some extent conda has this large prefilled envs with a lot of stuff in it already that work together. Still if you then end up needing anything else you wait ages for the install. I find conda so unbearable by now that I voluntarily switch every conda thing I have left over to uv the second I need to touch the conda env.

Because the gp comment is not about grapheneos, but its creator and could be taken as insulting (considering none of them is likely to be actually schizophrene).

That might take a few days or weeks, it seems like they put in some decent effort into it this time. From skimming the supplement I wouldn’t be suprised if the speedup is only 100x though. That’s still significant, but clearly less than they claim. For example I am not entirely convinced that 20% flops efficiency is really the upper limit or that the slicing overhead of 5x is really needed here.

But if you happen to have n=2^c, then an algorithm with logarithmic complexity only needs c time. Thats why this is usually referred to as exponential speedup in complexity theory, just like from O(2^n) to O(n). More concretely if the first algorithm needs 1024 seconds, the second one will need only 10 seconds in both cases, so I think it makes sense.

If you replace an n^2 algorithm with a log(n) lookup you get an exponential speed up. Although a hashmap lookup is usually O(1), which is even faster.

The knowledge is stored in the model, the one mentioned here is rather large, the full version needs over 700GB of disk space. Most people use compressed versions, but even those will often be 10-30GB in size.

I think you probably don’t want the application user to inherit from the superuser you may use for migrations since some migrations require a superuser.

It won’t answer questions that are not somehow related to code or computing, I usually don’t need anything else so I didn’t really test the limits of that so far.

For me it really is extremely close to 100% for timers, I barely remember it being wrong and I use it several times per day. Finding my phone via the HomePod also works pretty much every time, may be 90% for me but it doesn’t recognize my wife so for her it basically never works. The others I don’t use enough. But timers and reminders work really well for me and it’s also what I need to most from an assistant.