 Over the last couple of years, one of my goals as a business owner has been to deepen our pool of talent and intellectual properties so that if Linus the guy gets hit by a bus, Linus Media Group, the company, can survive. But I know that for many of you, Linus tech tips just wouldn't be the same without the Linus. Which is why we formulated a plan. We posted this video on our sister channel, ShortCircuit, where I appeared to be the host. But in actual fact, I had no involvement whatsoever. Here's how my team made it, and how monday.com, who generously sponsored this time-consuming, but super fun and very educational journey, made the process a whole lot easier. If you haven't heard of monday.com, it's a productivity tool to help you manage you and your team's work from start to finish. Most deepfakes you see online are made by taking an existing video clip and then using software to replace the face. And only the face. Unfortunately, our team's task was a little bit more complicated because we wanted our final video to not only look like me, but also sound like me. Linus' voice is proof that his balls are the only two things he hasn't dropped yet. This goal meant that we would have to write a script, hire a Linus impersonator to read the script on camera, record and edit that video, and then deepfake it. We used monday.com's recruitment management template with a few tweaks to keep track of everything. One small problem. There are no Linus impersonators. Well, none that are usable anyway that we could find. And even if we did find someone who could do Linus' voice, what are the odds that that guy, or gal, also looks like Linus? And I'm not even talking about facial features, although that helps. No matter how convincing the face swap, the final video simply wouldn't work if the impersonator was, say, built like a brick or had curly hair. Okay, then. So we go the other way then. Get someone who looks like me and then deepfake the face and voice, right? Not quite. You see, deepfake for voice, or high fidelity voice conversion, mostly exists in research papers right now. So we couldn't record a lookalike's take and then morph that audio clip to sound like Linus. Instead, we sent high quality audio and script reference pairs to a company called Resemble AI, who used them to train a neural network to generate the voice from scratch. I give consent to have my voice cloned by Resemble. Meanwhile, James wrote a fresh script for our eventual fake Linus actor to read. A keyboard review for the Cleave from Truly Ergonomic. The machine's first pass was a little rough. Just when you think you've reviewed every ergonomic keyboard on the planet, a new company with a name like Truly Ergonomic launches something like this, the Cleave keyboard, apparently the world's most comfortable keyboard, but with some patience and a ton of help from Resemble. By the way, shout out to Saqib Muhammad. You are awesome. We were able to get several options for each sentence, arrange our selections in Premiere along with some room tone, et voila, an imperfect but definitely recognizable voice clone. Just when you think you've reviewed every ergonomic keyboard on the planet, a new company with a name like Truly Ergonomic launches something like this, the Cleave keyboard, apparently the world's most comfortable keyboard. That is a pretty sexy sounding robot, if I do say so myself. Now for the visuals. We made a casting call on Vancouver Actors Guide looking for someone with my hair type, face shape, skin tone, and, well, stature. And boy, did some people ever not read the ad. But some people did, and we ended up hiring a lovely gentleman named Dylan Thibault. LTTStore.com I surrendered my favorite clothes to help him get into character, and, well, the COVID-19 pandemic had made his hair a little longer than the picture, but we decided to run with it. It's up here now. That's way too far how often I use it. Now instead I have two control keys right next to each other. How is that helpful? Hey Dylan, can you act more unreasonably upset about a small detail? Oh, f*** losing so many keys that your productivity suffers, and it's priced at 300 US dollars, which... Cut! Dylan, I don't want you to break any company property, but do you think you could drop it? Oh my gosh. Armed with the footage from Dylan's shoot, we opted to use DeepFaceLab, a free tool that is surprisingly easy to use. You just supply a video of your source, so that's me, and your destination, so that's Dylan, and then use the various batch files to split the videos into frames, extract faces from the frames, train the AI model, and then convert the final video. Let's look at each of those steps in a bit more detail. Most DeepFakes are made by taking a famous video that already exists, and then swapping a new face onto it. But we're actually making a brand new video, so that gives us a huge advantage. Not only are we able to use a set that Linus has shot on before, but this one has a giant softbox that's always there. That makes matching the lighting between our new video and our existing Linus footage really easy. But just in case, we also took brightness sweeps of Dylan from multiple angles, which helped the AI model become more generalizable. We then grabbed the footage from Linus's ShortCircuit videos, plus a couple LTTs with different lighting and face angles, and put them all on a new timeline in Premiere. It's a good idea to remove any extra b-roll, sponsor spots, or non-Linus faces at this point, to save time later. Next, we exported the video and dropped it into our DeepFake folder with the correct name, so the batch files could point to it. The first batch file splits the video into frames, which you could have actually done in your editing software, which also means less compression, while the next one extracts faces from those frames. Now for the all-important step of massaging our data set for both size and quality. monday.com's shareable boards helped us work through all the things we needed. You need at least a couple thousand images for your source and your destination. But the thing is, you don't want too much, so somewhere between 2 and 10,000 pictures of each face will do nicely, depending on how much time you have. And for quality, you want to remove any faces that are blurry, are of other people, or are not actually faces at all. It can be a bit tedious to go through so many images, even if they are of someone so handsome. But fortunately, DeepFace Labs has some built-in sorting tools to help it go faster. With that done, it's finally time to train the model. There are a number of knobs to adjust in the training step to ensure that our hardware is being used to its maximum potential, and a few that have to be tweaked over the course of training so that our faces have detail in the eyes, teeth, and skin tone, for example. It's basically a matter of turning up the key parameters until you get an out-of-memory error, and then backing off to the point where you're confident it won't crash. To get the best possible results, we needed to build a pretty badass deepfake rig. We started with the unlimited budget PC from a previous video. It's equipped with a 9900KS at 5.1 GHz, along with 64 GB of RAM. But since video memory is everything when it comes to deepfakes, we upgraded the gaming video cards to an RTX Quadro 8000 with a tier-inducing 48 GB of video memory. And while we do have two of these cards, we were actually worried that SLI would hurt our performance rather than help, because DeepFace Lab really isn't optimized for it. So I guess, rip SLI. Fast forward a couple of days, or weeks rather, actually, and our model previews were starting to look pretty detailed. That means it's time to merge. This can be done automagically, or you can use the interactive converter to go through your video frame by frame and tweak settings like super resolution, the blur of the mask edge, or the face scale. After that, our settings were used to output a final video, and... Just when you think you've reviewed every ergonomic keyboard on the planet. A new company with a name like Truly Ergonomic launches something like this, the Cleave keyboard, apparently the world's most comfortable keyboard. Pfft. Well, the face swap is good, but the lip sync? Pretty far off, the body language doesn't look very Linus-y, my hair is curly, and the voice sounds, frankly, just kind of tacked on. At this point, I thought we were pretty screwed. But fortunately, while this video was being made, a new version of DeepFace Lab came out that supports whole head swaps, meaning we no longer needed an actor with similar hair. So I took it upon myself to don the Costco jeans, slather dipty-doo in my hair to make it as small and shiny as possible, and talk with exaggerated facial expressions. LTTstore.com. And we also used this opportunity to collect some Foley. This is the ambient noises you'd expect to hear when the host handles packaging, for example. The new model showed promise, but it had its own new issues. Number one, see how the hair derps out when he turns his head? That's because our source dataset contained images from multiple LTT videos, meaning multiple, slightly different gelled hairstyles. That limits the machine to low-detail approximations of my hair. To make it crispier, we removed most of the images from our dataset, keeping only stills from the original short-circuit video. But that didn't end up solving it. The hair looks great when I'm facing forward, but since I actually never turned my head in that video, we had no data for my right side. So I did some detective work, and I learned that Linus shot that short-circuit video on November 29th, 2019. So I looked through our internal email and chat history to try to find out if he shot anything else that same day. And as luck would have it, he did, including multiple takes where he turns the correct way over and over again. Issue number two, you can still see some remnants of James in there. Handsome, but not necessary. To fix that, we ran the merge three times to create three different masks, then brought those into Premiere and created a composite that completely removed James while preserving the background and the new generated Linus. Not new and improved, just new and generated. I see you there. And I see a result that I'm honestly really proud of. I can't believe what the team accomplished here. Like, it's not perfect. James could have spent a little bit more time mastering my cat-like grace. But given that this was our first attempt and we learned so much doing it, not to mention had a ton of fun, I am glad that we completely blew our time budget for this project. Because hey, at least we had monday.com to help us keep that under control. monday.com made it way easier to keep track of tasks, recruit actors, and delegate assignments across departments. monday.com is built for the way you want to use it, with tons of customization. You can import any data you need, track progress among team members, and automate tasks so you can focus on getting work done. Don't take my word for it though, give it a try with a 30-day free trial at monday.com when you sign up today at the link below, which is monday.com. It's really easy when your service is the same as your URL, monday.com, right? It's easy to find. Guys, if you haven't seen it already, the finished, fully deepfaked video is up on our ShortCircuit channel, so go have a look. Thanks for watching. Is this really me? You'll never know.