Earlier quoted context omitted.
What's the lead time between new generators and a new detection model? What about novel generators that are never made public? 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?
There are three observations that are helpful to know about here: A: High quality, battle tested architectures are sold via an API and samples are therefore easy to retrieve at scale. B: lower quality, novel architectures are often published on GitHub and can be scaled on budget compute resources. C: Often these models perform well at classifying content generated by architectures similar to those they were trained o…
Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
51–60 of 70 posts
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#52Earlier quoted context omitted.
> so, tie content to domains. A domain vouches for content works like that content having been a webpage or email from said domain. Signed hash in metadata is backwards compatible and its easy to make browsers etc display warnings on unsigned content, content from new domains, blacklisted domains, etc. Okay, so I generate an image, open Instagram, take a picture of the generated image on a hi-res screen, and hit uplo…
What problem are you pointing out? The only thing you’ve done is severed the audit trail, which removes any trust in the image that was imbued in it by the original poster. Now when people wonder if the image is authentic, they can only rely on how trustworthy you are, not how trustworthy the original source was. This is working as the GP intended as far as I can see. You can’t add unearned authenticity this way, onl…
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#53Earlier quoted context omitted.
What problem are you pointing out? The only thing you’ve done is severed the audit trail, which removes any trust in the image that was imbued in it by the original poster. Now when people wonder if the image is authentic, they can only rely on how trustworthy you are, not how trustworthy the original source was. This is working as the GP intended as far as I can see. You can’t add unearned authenticity this way, onl…
I pointed out a way to silently sever the audit trail, at which point it sure seems like we've done a lot of work to roll out a whole new system that has such a gaping hole in it that there's no actual benefit.
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#54Congrats on launching. Would be good to have a quick trial on the website for a sample image, rather than going through the SDK route.
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#55Nice. They’ve got a very good reason to keep the model as closed as possible. The second you make it open, it just becomes the fitness signal for the next batch of deepfakes Make sure it works (most of the time) lock it down behind an well-guarded API and charge a lot of money :)
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#56Earlier quoted context omitted.
There are three observations that are helpful to know about here: A: High quality, battle tested architectures are sold via an API and samples are therefore easy to retrieve at scale. B: lower quality, novel architectures are often published on GitHub and can be scaled on budget compute resources. C: Often these models perform well at classifying content generated by architectures similar to those they were trained o…
I don't want to be rude is this not a question you get asked by potential customers? Is that your answer for them? It sounds a lot like 'I guess we will find out.'
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#57Earlier quoted context omitted.
Thank you. As an inference-based detection platform, our models go into every scan with the assumption that all files are both not the original/ground truth AND the files have been likely transcoded. We never say something is 0% or 100% fake because we don’t have that ground truth. That said, our award-winning models are able to say, with a confidence score of 1-99% — the higher being likely manipulated — which, in t…
I’m curious what awards the models have won?
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#58On a 2k desktop using Chrome, your website font/layout is way too big, especially your consent banner--it takes up 1/3 of the screen.
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#59Interesting that fakes text is not an artifact they support. I can understand there isn’t enough entropy for the detection logic to work may be
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#60Are you sure you guys want to tackle this problem? This isn’t the type of thing where you build a product doing a lot of work up front, and then spend the rest of its life offering support and new features and relaxing a bit. You are committing to a cat and mouse game. You will constantly have to stay on top of ever improving tech that gets harder to beat, you will never know peace. You will have to exert more and mo…
Whether it's introducing new models, deprecating old ones, or improving existing ones, there is an element of both staying current but also looking ahead at research. Many of the new models generating hyperreal content we catch on day one because they're based on existing technology and/or research.