Women also undergo voice change, just less pronounced.
Now the problem turns into being able to tell men from women.
EDIT: this of course isn't a serious proposition.
Then again I wonder what effect this would have implemented on e.g. a porn site. Women also watch porn, but with enough tuning I think it shouldn't produce too many false positives - if only due to the demographic of the users.
Surely the vocal cords and larynx of an adult woman are on average larger than those of a 10yo boy?
> AGEWARDEN is an age estimation tool. It does not verify identity and does not guarantee 100% accuracy. Customer is responsible for determining whether AGEWARDEN satisfies the legal requirements applicable to its business and jurisdiction.
I'll be honest: I don't have experience with audio stuff/age verification, but wouldn't it be far easier to bypass this than even face (live video) verification, let alone full KYC with ID? At that point it's not that much better than a "I'm over 18" button, or am I missing something?
EDIT: The website itself partially answers my question:
> Self-declaration, the "I am over 18" checkbox, is explicitly prohibited by every major regulator in the UK, EU, and Australia.
But then:
> Facial scanning works, but it builds infrastructure that outlasts the check. A system that estimates your age today can identify you tomorrow. Platforms that rolled it out met immediate backlash and reversals. Users do not trust platforms with their face.
How would we trust your platform to not store voice fingerprints, then?
(On a side note, all descriptions all LLM-written, but that's expected in 2026)
> How would we trust your platform to not store voice fingerprints, then?
This is a good question. Other than having it be more expensive to keep this data, and if it were true, destroy the company whose core tenant is literally that... you can't.
If you have suggestions for an independent audit, more than happy to add that to our stack where applicable.
When I say it's hard to not collect data, woof. Any fresh AWS account just LOVES to slurp it up by default.
> wouldn't it be far easier to bypass this than even face (live video) verification... or am I missing something?
Missing the experience of learning just how much information is in a clip of audio; replay/synthetic attack mitigation is baked in, and more cost-effective to run vs. video, and less creepy.
The mission: make the process easy (and inexpensive) as possible so that people can be verified at scale, without giving away their personal data and being the product.
It might not help in your case, but usually LLMs are far more likely to help if you have source code available, or if the service is running on localhost. Ideal if you have a source code where the LLM can make a lab setup and test vulnerabilities by itself. Normal GPT-5.5 with KYC is enough for this.
I think what they're saying is that this prompt/jailbreak only lets Mythos discover some really easy vulnerabilities that it probably fixes from a simple "Find and fix bugs in this code" and that this can be easily done by other models like GPT-5.5. Which is very different from targeted security research.
But it’s not that different from the whole premise of their red team scaremongering which was “we pointed the model at a source file and told it to find an exploit.”
Last update over a year ago, so I hope (2025) gets added to the title:
> [2025/05/26] (Step 1 completed!) We release Mixture-of-Thoughts--a curated reasoning dataset of 350k verified traces distilled from R1. The dataset spans tasks in mathematics, coding, and science, and is designed to teach language models to reason step-by-step. We also provide a recipe to train OpenR1-Distill-7B, which replicates the reasoning capabilities of deepseek-ai/DeepSeek-R1-Distill-Qwen-7B and marks the completion of step 1 in the Open R1 project.
Doesn't look like they managed to actually reproduce R1, and only stopped on Step 1 out of their 3-step plan.
One of my favorite code comments of all time is still in the src:
"# TODO: implement a proper validator to compare against ground truth. For now we just check for exact string match on each line of stdout." [1]
This was one of my chief complaints about the entire R1 news cycle, it felt like no one actually read the technical report. They were being heralded for their openness, but they left out the most meaningful details that you'd need to reproduce their work.
I had some contract work years ago helping some PhD program astrophysicists write scripts to make their research algorithms compute their data before their great grandchildren retire and one of the action items we never implemented was because someone wrote an “…etc” in the middle of the math.
They knew that everything was verifiably correct on the input, and verifiably correct on the output, and they swore they had figured it out at one point and just never wrote it down. I was asked if I could “just extrapolate it” and had to explain that computer programs work the same as math - I can give you a literally infinite number of ways to reach an output from an input.
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