Devils advocate: Splatting, dlss, neural codecs to name a few things that will change the way we make games

Looks like the Barbican in London to me, it's apartments and a public bar/drinking/working area, nice spot to hang out!

10dw . . .

1 is just going to highlight right?

2, how about 6 words, 10 words, 100 words

3, 4 I use all the time

5 if your edit locations don't line up so that you can alt drag a single column, this is what I mean by jagged. I would use a combination of find and repeat action.

Start from scratch - skill issue :p

Ooh fun, these all take 2-3 key presses

• Delete the contents inside a function delimiter by {
• Delete the next nine words
• Delete the contents inside long text quotes

And these more/less key presses

• Start a regex search with a single button
• Perform the same edit 100 times in a jagged files (good luck not f'ing up your multi cursor)

But it misses the point, of course every editor can do just about anything, but there is a lot more mouse involved and learning it is more difficult because the keybinds aren't combinatorial

I'm with you, I drew the line at calculators though. I can do the damn sums by myself!

I don't really follow your logic, how else would you propose to shape the audio that is not "just an effect".

Your analogy to real life does not take into account that the audio source itself is moving, so their is an extra variable outside of just stereo signal -which is what spatial audio is modelling

And your muffling example sounds a bit over simplified maybe? My understanding is that the spatial stuff is produced by phase shifting the LR signals slightly

Finally why not go further? "I don't listen to speaker audio because it's all just effects and mirages to sound like a real sound, what only 2^16 discrete positions the diaphragm can be in" :p

There's is a huge difference though.

That being one is making hardware and the other is copying books into your training pipeline though

The copy occurs in the dataset preparation.

Privacy preserving federated learning is a thing - essentially you train a local model and send the weight updates back to Google rather than the data itself....but also it's early days so who knows what vulnerabilities may exist

You could try dexed, it's a YamahaDX7 clone https://github.com/asb2m10/dexed/releases

You need rebase instead. Merge just creates useless commits and makes the diffs harder to comprehend (all changes are shown at once, but with rebase you fix the conflicts in the commit where they happened)

Then instead of your branch of branch strat you just rebase daily into main and you're golden when it comes time to PR

For me the infinity subscription bypass stopped working so I finally made the switch