ChatGPT unexpectedly began speaking in a user's cloned voice during testing

Using the same analogy: I dont see this in LLMs, I can speak with an LLM months and if we dont release a new version it is the same.

So they are not like children and I am not sure we really understand learning in children more so to the level that we can compare LLM with a child way of learning.

I've thought about this sort of approach many times in the past, and also done a lot of work with SGX and similar tech that implements remote attestation (RA). So I know how to build this sort of system conceptually. RA lets you do provable computations where the CPU can sign data, and the "public key" contains a hash of the program and data along with certificates that let you check the CPU was authentic. And it runs the program in a special CPU mode where the kernel and other things can't access the memory space. That's all you need to do verifiable computation.

So to preserve chain of custody you just have a set of filters or transforms that are SGX enclaves running ffmpeg or whatever, and each one attaches the attestation data to the output video which includes a hash of the input video. Then you gather up a certificate+signature over the original raw video from the camera (the cert is evidence the camera is authentic and the key is protected by the camera - you can get this from iPhone cameras), then an org certificate showing it came from a certain company, and then the attestation evidence for each transform. A set of scripts lets people verify all the evidence.

The problem is, after doing some business case analysis, I concluded it would only really be useful in some very small and specific cases:

1. Citizen journalists who are posting videos online that then get verified by news orgs. So the other way around. In this case the origin camera would use iPhone App Attestation to generate the source certificate, and all the fancy attested transform stuff isn't really important because it's the news org doing the transforms and doing the verifying.

2. Phone cam shots for insurance and other similar use cases. There is some business potential here, but it'd be sales force heavy as nobody knows the tech exists and deepfake fraud may not be a big enough problem for them to care (yet ...). If someone is looking for a startup idea, have this one for free.

3. Very new news companies that don't have any reputation yet and want to stand out from the crowd.

The thing is, for (3) or any place where a news org wants to increase the trust of the viewers, you don't need cryptography. That's just over-complicating things. You can just put a short random four letter code into the chyron that's unique to that particular shot you see on screen. Then on your website you have a page where the original unedited files can be downloaded by supplying the code. If you use cameras that produce cryptographic evidence like timestamps that's gravy, and for browny points you could publish video hashes into an unforgeable replicated log to stop you backdating footage. For most people that will be more than good enough. The sort of thing that causes people to lose trust in media is stuff not CNN broadcasting outright deepfakes, although that will happen eventually, but when they engage in selective editing, drop stories entirely, use archive footage and misrepresent it as something new etc.

The worst kind of fakery I've seen mainstream media engage in was Channel 4 UK's recent broadcast of a fake news segment, in which they "secretly filmed" someone who was pretending to be a racist Reform activist. People on X swiftly discovered that the person on-screen wasn't an activist at all but a professional actor, who had been putting on a fake accent the whole time (that he even advertised on his website). It looks for all the world like C4 broadcast entirely and truly fake news, knew they were doing it, and when they were called on it they just flat out refused to investigate knowing the British establishment was behind them all the way, as Reform is unpopular with the civil servant types who are supposed to police the media.

Unfortunately, for that kind of fakery there is no technological solution. Or, well, there is, but it's called social media + face recognition, and we already have it.

That's a very clever way of reducing a problem to autocomplete, but it doesn't change the paradigm.