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I don't remember recording any of this. Bitdefender did sponsor a video about protecting yourself from deep phase though.
Because now, these have gotten so good that you didn't even realize that I'm not the
real Linus either.
What are you guys doing?
Fully AI generated videos, at least for now, still have some easy to spot tells, especially
if they're long or if they involve a lot of movement. But a simple head replacement deepfake, or a stationary figure at a desk telling you
all about their latest get rich quick scheme.
Those have gotten shockingly convincing over the last five years.
Let's talk about both how we deepfaked and how we fully generated me for this video using
just commodity hardware. But before we do that, an important message.
If you've got a loved one who's going to need some help recognizing what's AI and
what's not, send them to this timestamp.
We've got you. Starting with our deepfake, the process is still pretty similar to how we did it last
time, just five years refined.
First find an actor with a similar body shape to your target.
You can see why this matters in this test that we did with Ploof, who owns the display.
When you blow it up on a TV, it's pretty easy to spot anomalies like his hat or his
beard leaving a soft outline. But on your phone, especially with poor eyesight, mostly just looks like a guy with a slim face
on a chunky body. Oh my god, am I allowed to say that? It's okay, I wrote the script.
So we parsed the subreddit then for the latest is this Linus meme and chose chase for our
real attempt. We used deepface lab to train a model on about 7000 recent images on my face and boom, much
more convincing. And this is both super cool and super scary.
It was at least a hundred times easier than when we did it last time.
Sinking up the lips with the audio is still pretty tough, but if you keep your clips short
and you edit them together in a punchy manner with alternate angles and close ups, like
you typically would, you can splice together something pretty convincing and pretty long,
one 5-7 second shot at a time.
With that said, I'm sure that a lot of you guys could still tell, because realistically
you dwell the same corners of the internet that I do, and you've been watching with
a sense of awe and with dread as deepfakes and video generation have gone from obviously
fake garbage to oh, this requires a little bit of scrutiny.
But you savvy viewer are not my concern.
Many, maybe even most people, can't tell anymore.
And online scams and fraud are increasing every year to the point where in 2024 losses
are estimated at over $1 trillion.
That number came from Bitdefender, who is in the business of knowing these things.
And the scariest part is that a huge portion of the scam industry is still using old school
text to voice phone calls. I mean, imagine if you could hit victims with something more like this.
Hey, I'm in a jam. Can I borrow $5,000?
And I know some of you guys are probably thinking, tough break boomers.
You had enough for the wealth anyway. But that's easy to say until it's your family member.
We have multiple people in this office who have had family members impacted.
And again, the scariest part is how easy it was to generate that clip.
All we needed for it and for the ones at the start of this video were start and end keyframes.
Once those were captured, or in many cases just scraped off of an existing video or Facebook
photo. My name is Nicholas Pluff and I hate displays.
We got an advanced subscription to openart.ai and it was off to the races.
Now to be clear, we're not actually recommending openart.ai.
They've gotten a lot of deserved hate. It's just that we used it for this project because Sora 2, which was our first choice,
won't let us generate anything with me in it and openart allows us to quickly experiment
with many different models. Choosing a model, by the way, is not as simple as just grabbing the latest one.
While newer models, like Google's VO3, might be generally more convincing, they also tend
to have stricter content guidelines. So for certain prompts, an older model might give a more satisfactory result.
Once we settled on mostly VO3, with a sprinkling of WAN 2.5 and Cling 2.1, we ran into our
second hurdle. A lot of our prompts, completely by accident I assure you, got flagged as not safe for
work. I think it's pretty obvious that I wanted this.
But whether it's from past experience or from the training data, our video generator
thought that I wanted this. Anywho, we got around it by using Cloud AI to help us create more AI-friendly prompts
to help bypass these guardrails.
From there, the biggest constraint was just how much money we wanted to burn on tokens.
We ended up throwing away about five video clips for every one that we were able to use.
Now I'm sure a few of you are wondering, why not just create this on your own hardware?
And that's a totally valid question. With CompFee UI and some of the open source models out there, you can create videos.
But the DIY ones are not as convincing yet, and the performance is pretty rough on consumer
hardware. With that said, things are moving so fast that by the time you watch this, it'll probably
have improved. That leads us to hurdle number three.
See a generated actor, unlike a deepfake actor, doesn't actually speak.
So you've got to line up your clips with separately generated audio.
That is enough of a challenge when the subject is stationary.
You throw in some walk and talk or walk and carry your colleague and things get pretty
rough. Unlike this WAN desk pad from lttstore.com, we use it all the time and it's still nice
and soft to the touch. But back on subject, look at this clip.
Not too bad. Add audio so I can show you that I can juggle computers.
Ooh, that's the yikes.
Now we tried lip syncing services, but those completely fell apart when it wasn't a simple
talking headshot. So our editing supervisor extraordinaire Emily used fish audio to generate a bunch of different
audio versions, and then we picked the closest matches.
Perfect. No. But this was a just for fun video to see what we could do with limited time and with the
tools at hand. Scammers on the other hand, they can spend a lot more time and money on these clips if
they think they can make money on them. That's where the sponsor of today's video comes in.
That is one thing fake liners was right. It's bit defender. And their message today is pretty simple, but very important.
And it's one that I agree with. Common sense is not always enough anymore.
What we showed you guys today is just the beginning for bad actors out there.
Scammers are constantly innovating their tactics and rapidly adopting AI, making it more difficult
than ever to distinguish between what's a real emergency and what's a manufactured
call that might fool a scared loved one. If you're interested in protecting yourself and your loved ones from all sorts of scams,
you can get 90 days of bit defenders premium security product absolutely free at the link
below, which includes scam protection, your AI powered defense against online fraud.
Now let's talk about how to spot a deep fake or a generated scam video.
Professor Hany Fareed does this for a living and gave a pretty cool TED talk earlier this
year here in Vancouver, highlighting cutting edge strategies for detecting AI imagery.
Some of them, like analyzing image noise, probably not going to help the average person
that much. But what we can do is look at things like shadows and vanishing points.
See we live in a 3D space, whoa.
But AI is creating 2D images in an attempt to simulate a 3D space, and it's doing that
without really a proper understanding of the laws of physics that govern light.
Let's say you stick a light in a room. You know intuitively that shadows will be cast away from it.
AI kind of gets this and tries to get it right, but if you try to align the shadows
with the light source, odds are that they're not going to convert properly.
And the same goes for something that human artists have understood for centuries, perspective
drawing and vanishing points. See in a real picture, every object eventually converges towards what's called the vanishing
point on the horizon, like this, and this, and this.
But AI fails to do that and is going to draw lines that don't converge properly.
Is this always easy or convenient to check?
So, because unfortunately we are far beyond the days of Will Smith's face melting as
he eats his non-convergent spaghetti, and depending on the model and how much effort
some would put in, sure you might spot an extra limb or lack thereof and instantly
know the image is fake, but it's gotten much harder to tell right away and is advancing
at a rapid pace. So quickly in fact that these physics quirks today could probably be ironed out in the
coming months rather than years. So what can you count on?
For now, your best bet is to be more skeptical about any content that you see, especially
on social media. Or at least, don't rely on it for trustworthy news.
And if you see anything suspicious, do some digging.
Find out if it's real or just more AI propaganda. Use other people to help you.
Have a look at the discussion. Even just looking a little closer to see if there's kind of a weird shimmer around an
object or if some of the lighting doesn't look quite right. That can help you spot the slop.
And whatever you do, please don't answer any urgent requests for your information or
for your money or click on any sketchy links.
If someone reaches out to you, the safest thing to do is say, hey, I'm going to call
you back at the number that I already have for you and confirm if this is you.
Thanks again to Bitdefender for sponsoring this video. They're a global leader in cybersecurity.
They've got over 17 years of AI innovation under their belts starting in 2008 when they
introduced AI and machine learning based threat detection.
While AI's ability to reproduce and scale tactics is a threat, its replication patterns
can also present opportunities for detection. We're going to have a link for their services in the video description and I sincerely hope
this video helps you and your loved ones avoid getting fooled by AI.
Thanks for watching guys. If you liked this video, maybe check out the last time we tried to deep fake me over five
years ago. It really has come a long way.
Not even necessarily in terms of the convincingness, but in terms of the ease.