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WHY THIS MATTERS IN BRIEF

If you think you look awful on Zoom calls and have a face for radio then Nvidia’s got the tool you’ve been wishing for all year.

 

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DeepFakes originally started out as a really expensive way to use Artificial intelligence (AI) to create synthetic mock ups of faces that would trick and fool people. But now they’ve evolved to become the latest hot corporate communications tool and to the point where anyone with a camera and a free app, like Zao, can put their likeness into Hollywood blockbusters, pretend to be Elon Musk on video calls, and much more besides.

 

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So, as the world goes DeepFake mad and continues to find new and better ways to use AI to create synthetic content that includes everything from art, blogs, books, games, music, to videos, it’s no surprise that Nvidia have been ratcheting up interest in the space with several innovations, and even though it’s latest one isn’t as exciting as some DeepFake foolery, like David Beckham’s malaria advert, Nvidia’s latest innovation, code named Maxine, is aimed squarely at helping you look even better in all those lame low res, grainy, video calls you’ve been doing.

 

Check out some of the cool features for yourself!

 

Maxine actually comes with a bunch of features, but the one that first caught my eye was its new AI assisted video compression tool. Have you ever wanted to deepfake your own face? Or turn your own face into a virtual chat avatar to then animate with something like the Facerig tool that’s so common among virtual youtubers like Kizuna Ai? Because that’s essentially what this tool does, all with the end goal of reducing bandwidth and (maybe) improving video streaming quality.

 

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Essentially, rather than constantly sending video data to whoever you’re chatting with, this new video compression tool sends them a static picture of your face, then reads the movements of your lips, eyes, cheeks and other key facial features to animate that picture on the other end using AI. Nvidia gives an example of a video stream using nearly 100KB per frame vs. an AI compressed stream using just 0.12KB per frame, meaning about a 1,000x difference in size. The result is a mostly realistic depiction of what you actually look like talking, but with much less data being sent over the network. Emphasis on “mostly.”

 

How AI upscaling works

 

Because the compression tool isn’t actually sending video, but is instead animating a static picture, it has to make some guesses, which results in things like blurry teeth, fuzzy edges and an animatronic style feel on some motions. It’s up to you whether a lower bandwidth cost is worth some uncanny valley imagery, but it does kind of feel like a little like an alien is wearing a skin suit in Nvidia’s example video.

 

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Assuming those kinks get worked out, it still feels odd that we could eventually live in a future where video chats essentially use computer-generated facsimiles of our own faces… which we would operate using actual video of those same faces. And, like deepfakes, this does raise questions as to potential impersonation. Could I send someone a picture of Tim Cook and just map my facial movements to his face? But given that this is currently being positioned as a developer-focused tool rather than a consumer-facing one, companies might consider the trade off in realism worth it for increased performance.

Of course, Maxine doesn’t stop just at recreating your face. It’s also promising AI-powered ‘enhancements,’ like Face Re-animation. The concept here is pretty simple. Say you’re focusing your eyes on a certain corner of your monitor screen, or tilting your head off to the side so you can look at a second monitor. Much like the AI video compression outlined above, Face Re-animation will use a still reference image and your facial movement data to adjust how you look on camera so that you appear to be looking directly at the screen, with your eyes focused on its center.

 

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Nvidia’s example video shows that this still has a ways to go, as the re-animated face is distinctly lower quality than the input data and stutters a bit as it moves to the center. It also comes with the same uncanny valley quality as the AI video compression tool. But assuming this all gets worked out, I could see something like this being helpful for workers who need to multitask during meetings, or even students dealing with overly aggressive virtual learning software punishing them for not looking directly at the screen.

On a less unsettling end of the spectrum, Maxine also promises AI assisted video upscaling, which could help those who don’t have the best webcams, as well as similar features to RTX Voice’s noise reduction and Nvidia Broadcast’s auto-frame. Nvidia’s demo video also briefly shows off tools for live language translation and for mapping facial movements to cartoon avatars, which might help offset the uncanny valley nature of Maxine’s AI compression and Face Re-animation tools. We currently don’t know much about these features, but they seem like they’d be genuinely helpful regardless of whether someone is a developer or not.

 

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For now, Nvidia Maxine isn’t coming straight to consumers. Instead, Nvidia’s offering free cloud access to it to third-party firms, who can then use it to improve their own software. That’s probably good, because while running these tools locally off your own RTX cards could improve performance, keeping them to the cloud will make them more accessible to the average person and will go further toward normalizing them. Still, communications firm Avaya is the only partner to have currently announced that it’s using Maxine, so don’t expect to see these features popping up in your Zoom calls anytime soon.

All jokes aside, as work-from-home continues to be the new normal across plenty of industries, it’s not surprising to see companies like Nvidia step up to try to make these spaces easier and more professional – even if it means they have to walk through the uncanny valley first.

About author

Matthew Griffin

Matthew Griffin, described as “The Adviser behind the Advisers” and a “Young Kurzweil,” is the founder and CEO of the World Futures Forum and the 311 Institute, a global Futures and Deep Futures consultancy working between the dates of 2020 to 2070, and is an award winning futurist, and author of “Codex of the Future” series. Regularly featured in the global media, including AP, BBC, Bloomberg, CNBC, Discovery, RT, Viacom, and WIRED, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew’s recent work includes mentoring Lunar XPrize teams, re-envisioning global education and training with the G20, and helping the world’s largest organisations envision and ideate the future of their products and services, industries, and countries. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Aon, Bain & Co, BCG, Credit Suisse, Dell EMC, Dentons, Deloitte, E&Y, GEMS, Huawei, JPMorgan Chase, KPMG, Lego, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, T-Mobile, and many more.

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