Congrats on launching. Would be good to have a quick trial on the website for a sample image, rather than going through the SDK route.
Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
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Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#42I feel like a much easier solution is enforcing data provinence. Ssl for media hash, attach to metadata. The problem with AI isnt the fact its ai, its that people can invest little effort to sway things with undue leverage. A single person can look like 100's with signficantly less effort than previously. The problem with ai content is it makes abuse of public spaces much easier. Forcing people to take credit for wor…
> 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, only remove it.
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#43I feel like a much easier solution is enforcing data provinence. Ssl for media hash, attach to metadata. The problem with AI isnt the fact its ai, its that people can invest little effort to sway things with undue leverage. A single person can look like 100's with signficantly less effort than previously. The problem with ai content is it makes abuse of public spaces much easier. Forcing people to take credit for wor…
Data provinence would be neat and a big benefit. But any solution that requires virtually all content publishers to change approach (here: add signing steps to their publishing workflow) is doomed to fail. There is no alternative way to do this than what OP is doing, which is to try to filter the fire hose of content into real vs not.
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#44Congrats on launching. Would be good to have a quick trial on the website for a sample image, rather than going through the SDK route.
I'am also a bit shocked by this SDK approach, why not a simple API
where you upload a file, get an ID and wait till it's done?
Beside that, sometimes it works, sometimes not:
{
"request_id": "9622a21f-37bf-4404-ac84-8728977a5272",
"status": "ANALYZING",
"score": null,
"models": [
{
"name": "rd-context-img",
"status": "ANALYZING",
"score": null
},
{
"name": "rd-pine-img",
"status": "ANALYZING",
"score": null
},
{
"name": "rd-oak-img",
"status": "ANALYZING",
"score": null
},
{
"name": "rd-elm-img",
"status": "ANALYZING",
"score": null
},
{
"name": "rd-img-ensemble",
"status": "ANALYZING",
"score": null
},
{
"name": "rd-cedar-img",
"status": "ANALYZING",
"score": null
}
]
}Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#45Nice. 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
#46Are 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 more effort each year.
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#47Yeah but does it actually work, though? There have been a lot of online tools claiming to be "AI detectors" and they all seem pretty unreliable. Can you talk us through what you look for, the most common failure modes and (at suitably high level) how you dealt with those?
Give it a try for yourself. It's free! We have been working on this problem since 2020 and have created an trained an ensemble of AI detection models working together to tell you what is real and what is fake!
I tried, It required making an account to use.
In this day and age, everybody realises that forcing people to make an account does not count as free. It is paying with personal information.
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#48First want to say that I sincerely appreciate you working on this problem. The proliferation of deepfakes is something that virtually every technology industry is dealing with right now. Suppose that deepfake technology progressed to the point where it is still detectable by your technology, but is impossible for the naked eye. In that scenario (which many would call an eventuality), wouldn't you also be compelled to…
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
#49Earlier quoted context omitted.
We've actually deployed to several Tier 1 banks and large enterprises already for various use-cases (verification, fraud detection, threat intelligence, etc.). The feedback that we've gotten so far is that our technology is high accuracy and a useful signal. 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 gene…
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 on, even if that architecture is not identical.
As 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.
Re: Launch HN: Reality Defender (YC W22) – API for Deepfake and GenAI Detection
#50But can't the bad actors use the same APIs to ensure that it's passing this first?