I’m stressed and running late, because what do you wear for the remainder of eternity? 

This makes it sound like I’m dying, nevertheless it’s the other. I’m, in a way, about to live eternally, due to the AI video startup Synthesia. For the past several years, the corporate has produced AI-generated avatars, but today it launches a brand new generation, its first to make the most of the most recent advancements in generative AI, and so they are more realistic and expressive than anything I’ve ever seen. While today’s release means almost anyone will now have the option to make a digital double, on this early April afternoon, before the technology goes public, they’ve agreed to make certainly one of me. 

After I finally arrive at the corporate’s stylish studio in East London, I’m greeted by Tosin Oshinyemi, the corporate’s production lead. He’s going to guide and direct me through the info collection process—and by “data collection,” I mean the capture of my facial expression, mannerisms, and more—very like he normally does for actors and Synthesia’s customers. 

He introduces me to a waiting stylist and a makeup artist, and I curse myself for wasting a lot time preparing. Their job is to make sure that people have the form of clothes that look good on camera and that they give the impression of being consistent from one shot to the subsequent. The stylist tells me my outfit is (phew), and the makeup artist touches up my face and tidies my baby hairs. The dressing room is decorated with lots of of smiling Polaroids of people that have been digitally cloned before me. 

Aside from the small supercomputer whirring within the corridor, which processes the info generated on the studio, this feels more like going right into a news studio than entering a deepfake factory. 

I joke that Oshinyemi has what might call a job title of the longer term: “deepfake creation director.” 

“We just like the term ‘synthetic media’ versus ‘deepfake,’” he says. 

It’s a subtle but, some would argue, notable difference in semantics. Each mean AI-generated videos or audio recordings of individuals doing or saying something that didn’t necessarily occur in real life. But deepfakes have a foul status. Since their inception nearly a decade ago, the term has come to signal something unethical, says Alexandru Voica, Synthesia’s head of corporate affairs and policy. Consider sexual content produced without consent, or political campaigns that spread disinformation or propaganda.

“Synthetic media is the more benign, productive version of that,” he argues. And Synthesia desires to offer one of the best version of that version.  

Until now, all AI-generated videos of individuals have tended to have some stiffness, glitchiness, or other unnatural elements that make them pretty easy to distinguish from reality. Because they’re so near the actual thing but , these videos could make people feel annoyed or uneasy or icky—a phenomenon commonly generally known as the uncanny valley. Synthesia claims its recent technology will finally lead us out of the valley. 

Due to rapid advancements in generative AI and a glut of coaching data created by human actors that has been fed into its AI model, Synthesia has been in a position to produce avatars which might be indeed more humanlike and more expressive than their predecessors. The digital clones are higher in a position to match their reactions and intonation to the sentiment of their scripts—acting more upbeat when talking about pleased things, as an illustration, and more serious or sad when talking about unpleasant things. In addition they do a greater job matching facial expressions—the tiny movements that may speak for us without words. 

But this technological progress also signals a much larger social and cultural shift. Increasingly, a lot of what we see on our screens is generated (or a minimum of tinkered with) by AI, and it’s becoming an increasing number of difficult to tell apart what’s real from what just isn’t. This threatens our trust in every thing we see, which could have very real, very dangerous consequences. 

“I believe we would just must say goodbye to checking out concerning the truth in a fast way,” says Sandra Wachter, a professor on the Oxford Web Institute, who researches the legal and ethical implications of AI. “The concept which you could just quickly Google something and know what’s fact and what’s fiction—I don’t think it really works like that anymore.” 

So while I used to be excited for Synthesia to make my digital double, I also wondered if the excellence between synthetic media and deepfakes is fundamentally meaningless. Even when the previous centers a creator’s intent and, critically, a subject’s consent, is there really a approach to make AI avatars safely if the top result is similar? And will we actually need to get out of the uncanny valley if it means we are able to not grasp the reality?

But more urgently, it was time to seek out out what it’s prefer to see a post-truth version of yourself.

Almost the actual thing

A month before my trip to the studio, I visited Synthesia CEO Victor Riparbelli at his office near Oxford Circus. As Riparbelli tells it, Synthesia’s origin story stems from his experiences exploring avant-garde, geeky techno music while growing up in Denmark. The web allowed him to download software and produce his own songs without buying expensive synthesizers. 

That research was conducted by Matthias Niessner, a professor on the Technical University of Munich, who cofounded Synthesia with Riparbelli in 2017, alongside University College London professor Lourdes Agapito and Steffen Tjerrild, whom Riparbelli had previously worked with on a cryptocurrency project. 

Initially the corporate built lip-synching and dubbing tools for the entertainment industry, nevertheless it found that the bar for this technology’s quality was very high and there wasn’t much demand for it. Synthesia modified direction in 2020 and launched its first generation of AI avatars for corporate clients. That pivot paid off. In 2023, Synthesia achieved unicorn status, meaning it was valued at over $1 billion—making it certainly one of the relatively few European AI firms to accomplish that. 

That first generation of avatars looked clunky, with looped movements and little variation. Subsequent iterations began looking more human, but they still struggled to say complicated words, and things were barely out of sync. 

The challenge is that folks are used to other people’s faces. “We as humans know what real humans do,” says Jonathan Starck, Synthesia’s CTO. Since infancy, “you’re really tuned in to people and faces. what’s right, so anything that’s not quite right really jumps out a mile.” 

These earlier AI-generated videos, like deepfakes more broadly, were made using generative adversarial networks, or GANs—an older technique for generating images and videos that uses two neural networks that play off each other. It was a laborious and complex process, and the technology was unstable. 

But within the generative AI boom of the last yr or so, the corporate has found it could actually create significantly better avatars using generative neural networks that produce higher quality more consistently. The more data these models are fed, the higher they learn. Synthesia uses each large language models and diffusion models to do that; the previous help the avatars react to the script, and the latter generate the pixels. 

Despite the leap in quality, the corporate remains to be not pitching itself to the entertainment industry. Synthesia continues to see itself as a platform for businesses. Its bet is that this: As people spend more time watching videos on YouTube and TikTok, there will likely be more demand for video content. Young individuals are already skipping traditional search and defaulting to TikTok for information presented in video form. Riparbelli argues that Synthesia’s tech could help firms convert their boring corporate comms and reports and training materials into content people will actually watch and interact with. He also suggests it may very well be used to make marketing materials. 

Don’t be garbage

In AI research, there’s a saying: Garbage in, garbage out. If the info that went into training an AI model is trash, that will likely be reflected within the outputs of the model. The more data points the AI model has captured of my facial movements, microexpressions, head tilts, blinks, shrugs, and hand waves, the more realistic the avatar will likely be. 

Back within the studio, I’m trying really hard to not be garbage. 

I’m standing in front of a green screen, and Oshinyemi guides me through the initial calibration process, where I even have to maneuver my head after which eyes in a circular motion. Apparently, it will allow the system to grasp my natural colours and facial expression. I’m then asked to say the sentence “All of the boys ate a fish,” which can capture all of the mouth movements needed to form vowels and consonants. We also film footage of me “idling” in silence.

DAVID VINTINER

He then asks me to read a script for a fictitious YouTuber in several tones, directing me on the spectrum of emotions I should convey. First I’m purported to read it in a neutral, informative way, then in an encouraging way, an annoyed and complain-y way, and at last an excited, convincing way. 

“Hey, everyone—welcome back to along with your host, Jess Mars. It’s great to have you ever here. We’re about to tackle a subject that’s pretty delicate and truthfully hits near home—coping with criticism in our spiritual journey,” I read off the teleprompter, concurrently trying to visualise ranting about something to my partner through the complain-y version. “Regardless of where you look, it looks like there’s all the time a critical voice able to chime in, doesn’t it?” 

“That was really good. I used to be watching it and I used to be like, ‘Well, that is true. She’s definitely complaining,’” Oshinyemi says, encouragingly. Next time, possibly add some judgment, he suggests.   

We film several takes featuring different variations of the script. In some versions I’m allowed to maneuver my hands around. In others, Oshinyemi asks me to carry a metal pin between my fingers as I do. That is to check the “edges” of the technology’s capabilities relating to communicating with hands, Oshinyemi says. 

Historically, making AI avatars look natural and matching mouth movements to speech has been a really difficult challenge, says David Barber, a professor of machine learning at University College London who just isn’t involved in Synthesia’s work. That’s because the issue goes far beyond mouth movements; you’ve got to take into consideration eyebrows, all of the muscles within the face, shoulder shrugs, and the many different small movements that humans use to precise themselves. 

DAVID VINTINER

Synthesia has worked with actors to coach its models since 2020, and their doubles make up the 225 stock avatars which might be available for patrons to animate with their very own scripts. But to coach its latest generation of avatars, Synthesia needed more data; it has spent the past yr working with around 1,000 skilled actors in London and Recent York. (Synthesia says it doesn’t sell the info it collects, even though it does release a few of it for educational research purposes.)

The actors previously got paid every time their avatar was used, but now the corporate pays them an up-front fee to coach the AI model. Synthesia uses their avatars for 3 years, at which point actors are asked in the event that they wish to renew their contracts. If that’s the case, they arrive into the studio to make a brand new avatar. If not, the corporate will delete their data. Synthesia’s enterprise customers may also generate their very own custom avatars by sending someone into the studio to do much of what I’m doing.