Readit NewsAs for actual lead time associated with our actual strategy, that’s probably not something I can talk about publicly. I can say I’m working on making it happen faster.
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So does it mean that if I use a 80% capacity battery my actual functional value that I get out of it would be considerably less than what the 80% would infer?
Actually, 80% is considered effectively 'end of life':
"Battery end of life is typically defined as the point at which the battery only provides 80% of its rated maximum capacity"
* https://www.researchgate.net/publication/303890624_Modeling_...
Yes, but https://radiologybusiness.com/topics/artificial-intelligence...
Nine years ago, scientist Geoffrey Hinton famously said, “People should stop training radiologists now,” believing it was “completely obvious” AI would outperform human rads within five years.
In terms of how our technology works, our research team has trained multiple detection models to look for specific visual and audio artifacts that the major generative models leave behind. These artifacts aren't perceptible to the human eye / ear, but they are actually very detectable to computer vision and audio models.
Each of these expert models gets combined into an ensemble system that weighs all the individual model outputs to reach a final conclusion.
We've got a rigorous process of collecting data from new generators, benchmarking them, and retraining our models when necessary. Often retrains aren't needed though, since our accuracy seems to transfer well across a given deepfake technique. So even if new diffusion or autoregressive models come out, for example, the artifacts tend to be similar and are still caught by our models.
I will say that our models are most heavily benchmarked on convincing audio/video/image impersonations of humans. While we can return results for items outside that scope, we've tended to focus training and benchmarking on human impersonations since that's typically the most dangerous risk for businesses.
So that's a caveat to keep in mind if you decide to try out our Developer Free Plan.
I think the most likely outcome of a criminal organization doing this is that they train a public architecture model from scratch on the material that they want to reproduce, and then use without telling anyone. Would your detector prevent this attack?
It’s not like people didn’t try bigger models in the past, but either the data was too small or the structure too simple to show improvements with more model complexity. (Or they simply trained the biggest model they could fit on the GPUs of the time.)
Can they not see that this is because of correlation and not causation. Why would an EV be given up at 150 - 200K when it has much less moving parts and stressors compared to the traditional ICE based vehicles?
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