In the last couple of years, we – and other great companies, have proven just how beneficial this technology is in both consumer and enterprise applications.”Riparbelli adds. “The term ‘deepfake’ comes mostly with negative connotations.
When the company started in 2017 however most investors and people only saw the potential downsides of AI video. Their focus is not on high-end M&E but rather they are aiming at producing vast amounts of video content without needing to film actors.
Synthesia ai 50m kleiner code#
The company aims to replace cameras with code and scale its AI video generation platform. Synthesia’s first commercial product, Synthesia STUDIO launched in public beta in the summer of 2020 and it has seen several significant upgrades already. The final output clip is pre-comped and ready to be used immediately. Backgrounds, animation, and even music can be added as part of this process. The actual production of any new neural rendered clip is then inferred from this training data in a couple of minutes. For the training clips, Mike was filmed delivering the same short script several times. The videos were authored in his office, on a laptop, and were based on training data we shot a couple of days ago. In the test demo above, fxguide’s Mike Seymour introduces two fully digital versions of himself. The footage looks so real it is hard to not believe it is traditional video. In this Lay’s campaign, every video is individualized to the names of the viewer.
Synthesia also powers celebrity campaigns such as Malaria No More with David Beckham or Lay’s Messi Messages. Synthesia’s clients include EY, who use Synthesia for client communications, and WPP, who use Synthesia for personalized training for their 50,000 employees.
Synthesia ai 50m kleiner series#
This builds on their $12.5M Series A financing round in May 2021. The round is the largest investment to date in the synthetic media space. Synthesia now operates the world’s largest AI video platform and has just secured a $50M Series B financing round led by Kleiner Perkins with participation from GV (Google Ventures) and all existing investors. Perhaps then it is no surprise that the company has just secured another massive round of finance. This year, mainly since May, Synthesia in the UK has generated more than 6 million unique neural rendered videos for thousands of clients, ranging from global corporations to small businesses. Synthesia has successfully placed conceptual distance between themselves and the morally and ethically questionable Deep Fakes of 2016/2017. While the popular press may have focused on this broader and frankly unrepresentative use of Neural Rendering, the actual adoption of AI-generated video has skyrocketing especially in the enterprise or organizational context. By allowing for digital human performances or ‘inferences’ at scale, NR is well suited to solve real-world problems and applications. While leading VFX companies are producing exceptional work, traditional technology often relies on expensive and dedicated 4D capture devices, such as Medusa, Light Stages, etc, as well as talented and complex human artistry.
Neural Rendering bridges the domain gap between CGI faces and photo captured imagery. Quickly the term DeepFake grew to encompass not only face-swapping with Machine Learning (ML) but a whole raft of problems including fake news, and general misinformation none of which had anything to do with the underlying brilliant advances in Variational AutoEncoders (VAE) and Generative Adversarial Networks (GANs). The notion of fave swapping that first appeared with fake celebrity porn clips on Reddit and then moved to political satire. Until recently Neural Rendering (NR) discussions were dominated by ‘Deep Fakes’.
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