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

And full of junkies shooting up in the bathrooms…at least that was my experience in 2nd class.

Never tried 1st class, maybe it’s better

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

Relative point to point

• which Blockchain are we talking here? How does it compare to the current banking infrastructure?
• again, which one? How does it compare to the current pricing?
• escrow is a thing, someone can build up a PayPal equivalent on top of a Blockchain, the list goes on
• the current system doesn’t do great here, some Blockchains makes it way more traceable, in fact
• skill issue, but also solvable with a PayPal equivalent
• not a fact, what does this even mean?
• does it?

You could say the Linux kernel is an astronomically terrible idea because it doesn’t do anything…but it is just the platform, the good comes from what people build on top of it that add all these quality of life features you miss

Buy ydy

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

Before becoming president

I don’t think the story implies clout was used for this. Just a play on words to make the conductor think there would be a crowd boarding rather than an individual

Do you read a song on demand when you are singing the lyrics verbatim?

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It’s definitely not indexed, we use RAG architectures to add indexing to data stores that we want the model to have direct access to, the relevant information is injected directly in the context (prompt). This can somewhat be equated to short term memory

The rest of the information is approximated in the weights of the neural network which gives the model general knowledge and intuition…akin to long term memory

You seem a bit troll-y too but I’ll bite.

The only one suggesting to add women because they are women is the edgy beb. The change I want to see is edgies being made to feel small. I have achieved based on their anemic come back :)

The person starting this thread wants to see the world you’re suggesting I create. And in doing so has opened a whole new class of YouTuber for our dear OP to explore…the analogy about fish, fishing and teachers come to mind

Ooh edgy, say more

This is an extremely odd outlook to have. Good luck with it.

Unfortunately the answer to your question is to not post at all, though if your contributions are worthwhile then that is not an excellent solution

This sounds like a fun project “samples of chemistry”

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