21–30 of 250 posts
I wonder how many of the current text-to-speech ML models have large parts of leaked or "stolen" data in their training data? Almost none of the TTS releases seem to talk about exactly where they get their training data from, for some reason. I also wonder if we'll see an explosion in SOTA TTS in ~6 months from now.
Even have a nice UI on top.
"My voice is my passport. Verify Me." :)
> Set up a verbal codeword with family and finance contacts. Pick a phrase that has never been spoken on a recording and never typed in chat. Brief the people who handle money on your behalf. If a call ever asks for a transfer, the codeword is mandatory. good luck with this. most finance people deal with hundreds to thousands of clients. they obviously cant remember everyones code word. commonly used finance systems…
> Set up a verbal codeword with family and finance contacts. Pick a phrase that has never been spoken on a recording and never typed in chat. Brief the people who handle money on your behalf. If a call ever asks for a transfer, the codeword is mandatory. good luck with this. most finance people deal with hundreds to thousands of clients. they obviously cant remember everyones code word. commonly used finance systems…
"My voice is my passport. Verify Me." :)
> Set up a verbal codeword with family and finance contacts. Pick a phrase that has never been spoken on a recording and never typed in chat. Brief the people who handle money on your behalf. If a call ever asks for a transfer, the codeword is mandatory. good luck with this. most finance people deal with hundreds to thousands of clients. they obviously cant remember everyones code word. commonly used finance systems…
Someone who has hundreds or thousands of clients presumably couldn't remember every client's voice either, so no meaningful security is lost. They are approximately as secure or insecure as before
there are automated systems for this already. my bank, isp, etc. use them when you call in to skip the traditional verification steps. this fact is also highlighted in the article.
the problem is that there isnt typically a system in place for setting up or validating code words, so the advice given is not practical to implement.
Earlier quoted context omitted.
Data hoarding predates LLMs. There where other machine learning methods which also needed data for training.
“Before LLM’s there was_____” I see this whenever an LLM’s impact is assessed. We know. The issue is scale and the ability for smaller and smaller groups (down to individuals) to execute at scale. Fake news always existed. Now one dude in India can flood multiple sock puppet media accounts with right wing content/images (actual example) at a scale previously unimaginable.
Author here. Wrote this after watching Lapsus$ post the Mercor archive on their leak site earlier this month. The thing that struck me is the combination: voice samples paired with ID document scans. Most breaches leak one or the other. This one ships a deepfake-ready kit. Tried to keep the writeup practical: what an attacker can actually do with this combo (banking voiceprint bypass, Arup-style video calls, insuranc…
Mercer hasn't released many public statements over the incident. Social media posts aren't necessarily public; but I did find this breach notification sample filed with CA - https://oag.ca.gov/ecrime/databreach/reports/sb24-621099 . I guess we'll see if our legislators finally take data privacy seriously.
You could have seen this coming a mile away. So far I have gotten away with never uploading my ID and/or interacting with one of those companies (though one idiot working for some VC thought it was ok to sign a document on my behalf by uploading my signature!!, never mind a bit of fraud) but it is getting harder and harder. Banks and in some cases even governments forcing you to send data to these operators is a very…