Not entirely true. You don’t need your own personal data centre, you can use GPU cloud instances for a lot of that stuff. It’s expensive but not so expensive that it would be impossible without being a huge tech company (only 1000s of dollars, not billions). This can be done by anyone with a credit card and some cash to burn. Also, you don’t need to train a model from scratch, you can build on existing models that others have published to cut down on training.

However, to impersonate someone’s voice you don’t need any of that. You only need about 5-10 seconds of audio for a zero-shot impersonation with a pre-trained model. A minute or so for few-shot. This runs on consumer hardware and in some cases even in real time.

Even to build your own model from scratch for high quality voice audio, there doesn’t need to be a huge amount of initial training data. Something like xtts was trained with about 10-15K hours of English audio which is actually pretty easy to come by in the public domain. There are a lot of open and public research datasets specifically for this kind of thing, no copyright infringements necessary. If a big tech company wants more audio data than what’s publically available, they just pay people to record audio, no need to steal it or risk copyright claims and breaking surveillance laws, they have a budget to exploit people to record whatever they want.

This tech wasn’t invented by some evil giant tech company stealing everybody’s data, it was mostly geeky computer scientists presenting things at computer speech synthesis conferences. That’s not to say there aren’t a bunch of huge evil tech companies profiting from this or contributing to this kind of tech, but in the context of audio deepfakes being accessible to scammers, it’s not on them and I don’t think that some kind of extra copyright regulation on data centres would do anything about it.

The current industry leader in this space in terms of companies trying to monetize speech synthesis is elevenlabs which is a private start-up with only a few dozen employees.

The current tech is not perfect but definitely good enough to fool someone who isn’t thinking too hard over a noisy phone call and a scammer doesn’t need server time or access to a data centre to do it.

One thing you gotta remember when dealing with that kind of situation is that Claude and Chat etc. are often misaligned with what your goals are.

They aren’t really chat bots, they’re just pretending to be. LLMs are fundamentally completion engines. So it’s not really a chat with an ai that can help solve your problem, instead, the LLM is given the equivalent of “here is a chat log between a helpful ai assistant and a user. What do you think the assistant would say next?”

That means that context is everything and if you tell the ai that it’s wrong, it might correct itself the first couple of times but, after a few mistakes, the most likely response will be another wrong answer that needs another correction. Not because the ai doesn’t know the correct answer or how to write good code, but because it’s completing a chat log between a user and a foolish ai that makes mistakes.

It’s easy to get into a degenerate state where the code gets progressively dumber as the conversation goes on. The best solution is to rewrite the assistant’s answers directly but chat doesn’t let you do that for safety reasons. It’s too easy to jailbreak if you can control the full context.

The next best thing is to kill the context and ask about the same thing again in a fresh one. When the ai gets it right, praise it and tell it that it’s an excellent professional programmer that is doing a great job. It’ll then be more likely to give correct answers because now it’s completing a conversation with a pro.

There’s a kind of weird art to prompt engineering because open ai and the like have sunk billions of dollars into trying to make them act as much like a “helpful ai assistant” as they can. So sometimes you have to sorta lean into that to get the best results.

It’s really easy to get tricked into treating like a normal conversation with a person when it’s actually really… not normal.

It’s a bit late for that. This particular nuclear reactor is open source, free to download and runs on consumer hardware. Can’t really unfry that egg and the quality is getting better all the time. Identity fraud is already illegal in most places so not sure exactly what regulation would be appropriate here.

“No worries!” means “Yes, that’s fine, there is nothing to worry about.”

He thought it meant “No! You should worry about that!”

This is a really interesting cultural one that always kinda surprises me.

Where I am, cooking has always been a very masculine thing. Cutting up meat with sharp knives, setting things on fire, etc. The chef industry here is very male dominated and men cook together as a social thing when hanging out. In most families I encounter, the dad does most of the cooking with the exception of maybe baking? It’s weird to hear that it would ever be thought of as insufficiently masculine.

In fact I think it would be seen as maybe a bit embarrassing/weak if you were a man who couldn’t cook.