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Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

news.ycombinator.com

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Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#11

Post by bpcrd »

candiddevmike wrote: post #8

Are you concerned that your product will inadvertently improve deepfakes? Suddenly you've given them a baseline that they need to be better than, and hackers love challenges. I predict this will turn into a constant arms race like AV or copyright protection, and I don't think this will work in the long run. IMO, KYC needs to go back to in person verification. Everything you can do digitally can be faked or impersonat…

In 2017 deepfakes were pretty crude, today the avg person can’t tell a real face from a deepfake generated on a 5 year old iPhone. We expect the tech to continue moving in this direction. So, similar to anti-virus, we're approaching this problem with an iterative, multi-model solution that can evolve with the threat.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#12

Post by bpcrd »

cphoover wrote: post #5

I believe deep-fakes to be a serious threat to functioning democracies around the world. I would love to be on the front-lines fighting against this threat. I have submitted my resume: https://cphoover.github.io/ Have you also considered either offering a browser plugin to display contextual warnings attached to video elements? Or thought of working with browser makers? The web/social media is where a ton of fake med…

We are adding new roles to our careers page on www.realitydefender.ai but feel free to reach out to career@realitydefender.ai and we can discuss your interest!

We are working with few partners (including Microsoft) who are interested in integrating our solution. We are focused right on supporting large organizations (companies and governments) that need to scan user generated content at scale.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#13

Post by endisneigh »

Imho this is a good product, but wouldn’t it make more sense to simply sign videos cryptographically?

Unfakeable and unbeatable.

So someone uploads a video, you sign it, they display video. If authenticity is in question check the signature.

Deep fake detection is intractable imo. Use cryptography instead.

Hell if you want to be thorough sign each frame and create an extension for YouTube and other providers to literally check to see if a given frame or period was altered.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#14

Post by bpcrd »

candiddevmike wrote: post #9
bpcrd wrote: post #7

Earlier quoted context omitted.

1- Each model looks for different deepfake signatures. By design, the models do not always agree, which is the goal. We are much more concerned with false negatives, and we target a min of 95% accuracy for our model of detection models. 2 - The challenge is educating users about results without requiring a PhD. Our platform is targeted for use by junior analysts in cyber security or trust and safety. 3 - This is a go…

Why would you be more concerned about false negatives? Wouldn't false positives erode trust and value in your product, and considering the applications you're targeting, possibly open you up to lawsuits if you start accusing innocent people of being deepfakes (which, IMO, currently seems unlikely)?

We provide a probabilistic percentage result that is used by a trust and safety team to set limits (ie. flag or block content) so it is not a binary yes/no. We search for specific deepfake signatures and we explain what our results are identifying.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#15

Post by candiddevmike »

bpcrd wrote: post #11
candiddevmike wrote: post #8

Are you concerned that your product will inadvertently improve deepfakes? Suddenly you've given them a baseline that they need to be better than, and hackers love challenges. I predict this will turn into a constant arms race like AV or copyright protection, and I don't think this will work in the long run. IMO, KYC needs to go back to in person verification. Everything you can do digitally can be faked or impersonat…

In 2017 deepfakes were pretty crude, today the avg person can’t tell a real face from a deepfake generated on a 5 year old iPhone. We expect the tech to continue moving in this direction. So, similar to anti-virus, we're approaching this problem with an iterative, multi-model solution that can evolve with the threat.

So the folks at the forefront of deep fake technology (i.e. the attackers you're targeting) will slip through your product because it lags behind the state of the art (like AV, which you said is the approach you're following), while innocent folks will be caught by it due to a new kafkaesque version of "prove you're not a bot" since you focus on reducing false negatives. Hopefully I can avoid companies using your product.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#16

Post by dymk »

candiddevmike wrote: post #8

Are you concerned that your product will inadvertently improve deepfakes? Suddenly you've given them a baseline that they need to be better than, and hackers love challenges. I predict this will turn into a constant arms race like AV or copyright protection, and I don't think this will work in the long run. IMO, KYC needs to go back to in person verification. Everything you can do digitally can be faked or impersonat…

Aren’t you worried that in person KYC will lead to an improvement in latex face masks? Sounds like an arms race.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#17

Post by bpcrd »

domidre wrote: post #6

Hi, congratulations to your launch. I would also like to ask three question. Do you know how well your model generalizes to video/audio deepfakes created by models that are not within your training sets? And also have you investigated whether your model can be used in a GAN setting to improve a deepfake generator towards creating better fakes? Or how robust your detectors are against adversarial attacks?

Great questions.

1 - We include multiple models for GAN and non-GAN related synthetic media.

2 - Models are only as good as the training data, and most training data breaks down in the real world because hackers have access to this same open source training data. So we create our own proprietary training data which we have automated, and we continuously update it based upon emerging deepfakes that we find in the wild.

3 - We target 95% accuracy with all public and proprietary training sets. And we continuously test and iterate both the data sets and the models.

4 - Our policies require a background check on all users to filter out bad actors. We additionally have technology safeguards in place to limit improper use.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#18

Post by [deleted] »

dymk wrote: post #16
candiddevmike wrote: post #8

Are you concerned that your product will inadvertently improve deepfakes? Suddenly you've given them a baseline that they need to be better than, and hackers love challenges. I predict this will turn into a constant arms race like AV or copyright protection, and I don't think this will work in the long run. IMO, KYC needs to go back to in person verification. Everything you can do digitally can be faked or impersonat…

Aren’t you worried that in person KYC will lead to an improvement in latex face masks? Sounds like an arms race.

[deleted]

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#19

Post by bpcrd »

endisneigh wrote: post #13

Imho this is a good product, but wouldn’t it make more sense to simply sign videos cryptographically? Unfakeable and unbeatable. So someone uploads a video, you sign it, they display video. If authenticity is in question check the signature. Deep fake detection is intractable imo. Use cryptography instead. Hell if you want to be thorough sign each frame and create an extension for YouTube and other providers to liter…

We’re fascinated by the potential applications of crypto in content provenance. In this example, a UGC video platform would need a way to initially determine the content hasn’t been manipulated before it’s signed, right? What about a live scenario where a deepfake mimicking an exec calls a manager to wire $10M (https://www.forbes.com/sites/thomasbrewster/2021/10/14/huge-...)

We totally recognize deepfake detection is a big & constantly evolving challenge, but we don't see that as a reason to cede the truth to bad actors :)

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#20

Post by [deleted] »

candiddevmike wrote: post #9
bpcrd wrote: post #7

Earlier quoted context omitted.

1- Each model looks for different deepfake signatures. By design, the models do not always agree, which is the goal. We are much more concerned with false negatives, and we target a min of 95% accuracy for our model of detection models. 2 - The challenge is educating users about results without requiring a PhD. Our platform is targeted for use by junior analysts in cyber security or trust and safety. 3 - This is a go…

Why would you be more concerned about false negatives? Wouldn't false positives erode trust and value in your product, and considering the applications you're targeting, possibly open you up to lawsuits if you start accusing innocent people of being deepfakes (which, IMO, currently seems unlikely)?

[deleted]
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