1 00:00:00,000 --> 00:00:07,040 dita fender sponsored this video so i can show you that i can juggle computers 2 00:00:07,040 --> 00:00:13,880 and tell you about our new amazing product Linus strength pills watch as i make david watch all of 2019 3 00:00:15,000 --> 00:00:17,000 not this 4 00:00:30,000 --> 00:00:36,160 Thanks to Linus Pills. 5 00:00:36,160 --> 00:00:42,960 I'm unstoppable. Start your subscription today by emailing me at Linus.Linus.Linus.com. 6 00:00:42,960 --> 00:00:49,080 I don't remember recording any of this. Bitdefender did sponsor a video about protecting yourself from deep phase though. 7 00:00:49,080 --> 00:00:52,600 Because now, these have gotten so good that you didn't even realize that I'm not the 8 00:00:52,600 --> 00:00:55,840 real Linus either. 9 00:00:55,840 --> 00:01:07,520 What are you guys doing? 10 00:01:07,520 --> 00:01:13,520 Fully AI generated videos, at least for now, still have some easy to spot tells, especially 11 00:01:13,520 --> 00:01:20,600 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 12 00:01:20,600 --> 00:01:23,600 all about their latest get rich quick scheme. 13 00:01:23,600 --> 00:01:27,280 Those have gotten shockingly convincing over the last five years. 14 00:01:27,280 --> 00:01:32,840 Let's talk about both how we deepfaked and how we fully generated me for this video using 15 00:01:32,840 --> 00:01:37,320 just commodity hardware. But before we do that, an important message. 16 00:01:37,320 --> 00:01:41,280 If you've got a loved one who's going to need some help recognizing what's AI and 17 00:01:41,280 --> 00:01:44,680 what's not, send them to this timestamp. 18 00:01:44,680 --> 00:01:50,400 We've got you. Starting with our deepfake, the process is still pretty similar to how we did it last 19 00:01:50,400 --> 00:01:53,600 time, just five years refined. 20 00:01:53,600 --> 00:01:56,840 First find an actor with a similar body shape to your target. 21 00:01:56,840 --> 00:02:01,100 You can see why this matters in this test that we did with Ploof, who owns the display. 22 00:02:01,100 --> 00:02:05,440 When you blow it up on a TV, it's pretty easy to spot anomalies like his hat or his 23 00:02:05,440 --> 00:02:12,520 beard leaving a soft outline. But on your phone, especially with poor eyesight, mostly just looks like a guy with a slim face 24 00:02:12,520 --> 00:02:16,840 on a chunky body. Oh my god, am I allowed to say that? It's okay, I wrote the script. 25 00:02:16,840 --> 00:02:23,400 So we parsed the subreddit then for the latest is this Linus meme and chose chase for our 26 00:02:23,400 --> 00:02:31,680 real attempt. We used deepface lab to train a model on about 7000 recent images on my face and boom, much 27 00:02:31,680 --> 00:02:36,880 more convincing. And this is both super cool and super scary. 28 00:02:36,880 --> 00:02:41,160 It was at least a hundred times easier than when we did it last time. 29 00:02:41,160 --> 00:02:45,600 Sinking up the lips with the audio is still pretty tough, but if you keep your clips short 30 00:02:45,720 --> 00:02:50,400 and you edit them together in a punchy manner with alternate angles and close ups, like 31 00:02:50,400 --> 00:02:55,040 you typically would, you can splice together something pretty convincing and pretty long, 32 00:02:55,040 --> 00:02:58,120 one 5-7 second shot at a time. 33 00:02:58,120 --> 00:03:03,040 With that said, I'm sure that a lot of you guys could still tell, because realistically 34 00:03:03,040 --> 00:03:06,680 you dwell the same corners of the internet that I do, and you've been watching with 35 00:03:06,680 --> 00:03:13,040 a sense of awe and with dread as deepfakes and video generation have gone from obviously 36 00:03:13,040 --> 00:03:17,520 fake garbage to oh, this requires a little bit of scrutiny. 37 00:03:17,520 --> 00:03:21,520 But you savvy viewer are not my concern. 38 00:03:21,520 --> 00:03:25,520 Many, maybe even most people, can't tell anymore. 39 00:03:25,520 --> 00:03:31,200 And online scams and fraud are increasing every year to the point where in 2024 losses 40 00:03:31,200 --> 00:03:34,760 are estimated at over $1 trillion. 41 00:03:34,760 --> 00:03:38,800 That number came from Bitdefender, who is in the business of knowing these things. 42 00:03:38,800 --> 00:03:44,640 And the scariest part is that a huge portion of the scam industry is still using old school 43 00:03:44,640 --> 00:03:51,200 text to voice phone calls. I mean, imagine if you could hit victims with something more like this. 44 00:03:51,200 --> 00:03:54,800 Hey, I'm in a jam. Can I borrow $5,000? 45 00:03:54,800 --> 00:03:59,360 And I know some of you guys are probably thinking, tough break boomers. 46 00:03:59,360 --> 00:04:05,280 You had enough for the wealth anyway. But that's easy to say until it's your family member. 47 00:04:05,280 --> 00:04:09,920 We have multiple people in this office who have had family members impacted. 48 00:04:09,920 --> 00:04:14,880 And again, the scariest part is how easy it was to generate that clip. 49 00:04:14,880 --> 00:04:20,680 All we needed for it and for the ones at the start of this video were start and end keyframes. 50 00:04:20,680 --> 00:04:26,040 Once those were captured, or in many cases just scraped off of an existing video or Facebook 51 00:04:26,040 --> 00:04:31,440 photo. My name is Nicholas Pluff and I hate displays. 52 00:04:31,440 --> 00:04:36,680 We got an advanced subscription to openart.ai and it was off to the races. 53 00:04:36,680 --> 00:04:39,840 Now to be clear, we're not actually recommending openart.ai. 54 00:04:39,840 --> 00:04:46,640 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, 55 00:04:46,640 --> 00:04:51,320 won't let us generate anything with me in it and openart allows us to quickly experiment 56 00:04:51,320 --> 00:04:57,680 with many different models. Choosing a model, by the way, is not as simple as just grabbing the latest one. 57 00:04:57,680 --> 00:05:02,360 While newer models, like Google's VO3, might be generally more convincing, they also tend 58 00:05:02,360 --> 00:05:10,080 to have stricter content guidelines. So for certain prompts, an older model might give a more satisfactory result. 59 00:05:10,080 --> 00:05:15,480 Once we settled on mostly VO3, with a sprinkling of WAN 2.5 and Cling 2.1, we ran into our 60 00:05:15,480 --> 00:05:22,680 second hurdle. A lot of our prompts, completely by accident I assure you, got flagged as not safe for 61 00:05:22,680 --> 00:05:27,760 work. I think it's pretty obvious that I wanted this. 62 00:05:27,760 --> 00:05:32,720 But whether it's from past experience or from the training data, our video generator 63 00:05:32,720 --> 00:05:42,280 thought that I wanted this. Anywho, we got around it by using Cloud AI to help us create more AI-friendly prompts 64 00:05:42,280 --> 00:05:45,280 to help bypass these guardrails. 65 00:05:45,280 --> 00:05:49,660 From there, the biggest constraint was just how much money we wanted to burn on tokens. 66 00:05:49,660 --> 00:05:54,660 We ended up throwing away about five video clips for every one that we were able to use. 67 00:05:54,660 --> 00:05:58,940 Now I'm sure a few of you are wondering, why not just create this on your own hardware? 68 00:05:58,940 --> 00:06:05,500 And that's a totally valid question. With CompFee UI and some of the open source models out there, you can create videos. 69 00:06:05,500 --> 00:06:12,060 But the DIY ones are not as convincing yet, and the performance is pretty rough on consumer 70 00:06:12,060 --> 00:06:17,100 hardware. With that said, things are moving so fast that by the time you watch this, it'll probably 71 00:06:17,100 --> 00:06:20,900 have improved. That leads us to hurdle number three. 72 00:06:20,900 --> 00:06:28,300 See a generated actor, unlike a deepfake actor, doesn't actually speak. 73 00:06:28,300 --> 00:06:33,220 So you've got to line up your clips with separately generated audio. 74 00:06:33,220 --> 00:06:36,220 That is enough of a challenge when the subject is stationary. 75 00:06:36,220 --> 00:06:41,500 You throw in some walk and talk or walk and carry your colleague and things get pretty 76 00:06:41,500 --> 00:06:46,980 rough. Unlike this WAN desk pad from lttstore.com, we use it all the time and it's still nice 77 00:06:46,980 --> 00:06:50,460 and soft to the touch. But back on subject, look at this clip. 78 00:06:50,460 --> 00:06:55,500 Not too bad. Add audio so I can show you that I can juggle computers. 79 00:06:55,500 --> 00:06:59,020 Ooh, that's the yikes. 80 00:06:59,020 --> 00:07:04,340 Now we tried lip syncing services, but those completely fell apart when it wasn't a simple 81 00:07:04,340 --> 00:07:11,500 talking headshot. So our editing supervisor extraordinaire Emily used fish audio to generate a bunch of different 82 00:07:11,500 --> 00:07:14,620 audio versions, and then we picked the closest matches. 83 00:07:14,620 --> 00:07:20,620 Perfect. No. But this was a just for fun video to see what we could do with limited time and with the 84 00:07:20,620 --> 00:07:26,620 tools at hand. Scammers on the other hand, they can spend a lot more time and money on these clips if 85 00:07:26,620 --> 00:07:31,140 they think they can make money on them. That's where the sponsor of today's video comes in. 86 00:07:31,140 --> 00:07:37,460 That is one thing fake liners was right. It's bit defender. And their message today is pretty simple, but very important. 87 00:07:37,460 --> 00:07:42,580 And it's one that I agree with. Common sense is not always enough anymore. 88 00:07:42,580 --> 00:07:46,540 What we showed you guys today is just the beginning for bad actors out there. 89 00:07:46,540 --> 00:07:51,820 Scammers are constantly innovating their tactics and rapidly adopting AI, making it more difficult 90 00:07:51,820 --> 00:07:56,540 than ever to distinguish between what's a real emergency and what's a manufactured 91 00:07:56,540 --> 00:08:03,020 call that might fool a scared loved one. If you're interested in protecting yourself and your loved ones from all sorts of scams, 92 00:08:03,020 --> 00:08:07,300 you can get 90 days of bit defenders premium security product absolutely free at the link 93 00:08:07,300 --> 00:08:12,580 below, which includes scam protection, your AI powered defense against online fraud. 94 00:08:12,580 --> 00:08:16,900 Now let's talk about how to spot a deep fake or a generated scam video. 95 00:08:16,900 --> 00:08:21,020 Professor Hany Fareed does this for a living and gave a pretty cool TED talk earlier this 96 00:08:21,020 --> 00:08:26,180 year here in Vancouver, highlighting cutting edge strategies for detecting AI imagery. 97 00:08:26,180 --> 00:08:30,780 Some of them, like analyzing image noise, probably not going to help the average person 98 00:08:30,780 --> 00:08:36,740 that much. But what we can do is look at things like shadows and vanishing points. 99 00:08:36,740 --> 00:08:41,740 See we live in a 3D space, whoa. 100 00:08:41,740 --> 00:08:48,620 But AI is creating 2D images in an attempt to simulate a 3D space, and it's doing that 101 00:08:48,620 --> 00:08:54,180 without really a proper understanding of the laws of physics that govern light. 102 00:08:54,180 --> 00:09:00,020 Let's say you stick a light in a room. You know intuitively that shadows will be cast away from it. 103 00:09:00,020 --> 00:09:05,460 AI kind of gets this and tries to get it right, but if you try to align the shadows 104 00:09:05,460 --> 00:09:10,060 with the light source, odds are that they're not going to convert properly. 105 00:09:10,060 --> 00:09:14,940 And the same goes for something that human artists have understood for centuries, perspective 106 00:09:14,940 --> 00:09:22,220 drawing and vanishing points. See in a real picture, every object eventually converges towards what's called the vanishing 107 00:09:22,220 --> 00:09:27,660 point on the horizon, like this, and this, and this. 108 00:09:27,660 --> 00:09:33,180 But AI fails to do that and is going to draw lines that don't converge properly. 109 00:09:33,180 --> 00:09:36,540 Is this always easy or convenient to check? 110 00:09:36,620 --> 00:09:41,180 So, because unfortunately we are far beyond the days of Will Smith's face melting as 111 00:09:41,180 --> 00:09:45,460 he eats his non-convergent spaghetti, and depending on the model and how much effort 112 00:09:45,460 --> 00:09:50,260 some would put in, sure you might spot an extra limb or lack thereof and instantly 113 00:09:50,260 --> 00:09:55,060 know the image is fake, but it's gotten much harder to tell right away and is advancing 114 00:09:55,060 --> 00:10:01,260 at a rapid pace. So quickly in fact that these physics quirks today could probably be ironed out in the 115 00:10:01,260 --> 00:10:05,940 coming months rather than years. So what can you count on? 116 00:10:06,020 --> 00:10:11,380 For now, your best bet is to be more skeptical about any content that you see, especially 117 00:10:11,380 --> 00:10:16,060 on social media. Or at least, don't rely on it for trustworthy news. 118 00:10:16,060 --> 00:10:19,500 And if you see anything suspicious, do some digging. 119 00:10:19,500 --> 00:10:24,180 Find out if it's real or just more AI propaganda. Use other people to help you. 120 00:10:24,180 --> 00:10:29,340 Have a look at the discussion. Even just looking a little closer to see if there's kind of a weird shimmer around an 121 00:10:29,340 --> 00:10:33,860 object or if some of the lighting doesn't look quite right. That can help you spot the slop. 122 00:10:33,860 --> 00:10:38,620 And whatever you do, please don't answer any urgent requests for your information or 123 00:10:38,620 --> 00:10:41,740 for your money or click on any sketchy links. 124 00:10:41,740 --> 00:10:46,020 If someone reaches out to you, the safest thing to do is say, hey, I'm going to call 125 00:10:46,020 --> 00:10:50,380 you back at the number that I already have for you and confirm if this is you. 126 00:10:50,380 --> 00:10:54,180 Thanks again to Bitdefender for sponsoring this video. They're a global leader in cybersecurity. 127 00:10:54,180 --> 00:10:58,740 They've got over 17 years of AI innovation under their belts starting in 2008 when they 128 00:10:58,740 --> 00:11:02,340 introduced AI and machine learning based threat detection. 129 00:11:02,340 --> 00:11:07,540 While AI's ability to reproduce and scale tactics is a threat, its replication patterns 130 00:11:07,540 --> 00:11:13,420 can also present opportunities for detection. We're going to have a link for their services in the video description and I sincerely hope 131 00:11:13,420 --> 00:11:18,620 this video helps you and your loved ones avoid getting fooled by AI. 132 00:11:18,620 --> 00:11:23,580 Thanks for watching guys. If you liked this video, maybe check out the last time we tried to deep fake me over five 133 00:11:23,580 --> 00:11:27,620 years ago. It really has come a long way. 134 00:11:27,620 --> 00:11:31,620 Not even necessarily in terms of the convincingness, but in terms of the ease.