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vrighter

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i recently heard a colleague telling another "vscode can't really help you when writing yaml files". I said that the yaml lsp supports loading a json schema, all you need is just one comment at the top to point the lsp to it, then you get reliable error reporting with red squigglies on every single keystroke.

He just shrugged and said "oh i just use ai".

What takes me one keystroke takes him a full minute. And he didn't even consider the use of actual tools

i still have a gtx 1080 in my machine. But nvidia just dropped support for them, and some games will forever remain glitching (ex 007 first light flickers like crazy on proton)

When I was making an EEPROM programmer with an arduino, I decided to pick up the datasheet, ditch the arduino builtin stuff (I made a separate "board" which stripped the serial code out, and the time functions, because I didn't need them and they fired an interrupt needlessly wasting resources for me), and write your own interrupts for serial. It's obviously more work, but you get to implement whatever you want. You can set up an interrupt for the flow control line. The arduino libraries are shockingly inefficient and limited sometimes.

Or you could do software flow control and use XON and XOFF for a simpler but, imo, clunkier solution

nah, it's just people wanting to pad their resume. And your resume is usually first read by someone who's only impressed by stuff they can see

it is insanely slow. I regularly need to wait for minutes just for the final crate to compile when compiling some tui program from scratch

I think of it like this. Imagine a network with two inputs and one output. What's happening during training is to orient a set of 2d planes in 3d space. Then for each x and y coordinate you can iterate through those planes and figure out where the normal at (x,y) hits them on the z axis, take the highest of your result and that's your network output.

Sometimes the solution needs one of the planes to make a big change to its orientation. and in the process of doing so the fitness will go down. Now if some other plane happened, by luck, to be in a better position to get to that state without lowering the fitness, then it will generally dominate over the other one, and the first one would start to "evolve" to be suppressed by the other one. The first one then becomes (usually, but not always) pretty much dead. Since the network has a fixed number of weights, it can't decide to just "add another plane". It has to make do with a fixed number of them. If too much of them become useless your training can't really recover, you're stuck at that minimum. The overparametrization allows for a bigger chance that some other plane's orientation will happen to be in a position to shadow counterproductive ones.

Why anyone would even consider using an online password manager is beyond me. Keepass works perfectly offline, and it's easy to sync. Just copy one file. I set up syncthing on my pc and phone and I basically just forget about it. For other places I have a particular subdomain (guid) where I serve the current copy of the file, gated by a password. The database itself is protected by both a password and a yubikey.

you forgot that to not have a knowledge cutoff and fall behing, you need to always be training new models. It matters jack shit if inference is cheap, if you are forced to do training anyway to stay "competitive"