Old Clips Become Big Hits: AI-Enhanced Videos Script a Success Story

After his AI-enhanced vintage video went viral, Denis Shiryaev launched a startup to bottle the magic. Soon anyone who wants to dust off their old films may be able to use his neural networks.

The story began with a blog on Telegram by the Russian entrepreneur currently living in Gda sk, Poland.

Some years ago I started to blog about machine learning and play with different algorithms to understand it better, said Shiryaev, who later founded the startup known by its web address, neural.love. I was generating music with neural nets and staging Turing tests of chatbots - silly, fun stuff.

Eight months ago, he tried an AI experiment with a short, grainy film he'd found on YouTube of a train in 1896 arriving in a small French town. He used open-source software and AI models to upscale it to 4K resolution and smooth its jerky motion from 15 frames per second to 60 fps.

I posted it one night, and when I woke up the next day, I had a million views and was on the front page of Reddit. My in-box was exploding with messages on Facebook, LinkedIn - everywhere, he said of responses to the video below

Not wanting to be a one-hit wonder, he found other vintage videos to work with. He ran them through an expanding workflow of AI models, including DeOldify for adding color and other open-source algorithms for removing visual noise.

His inbox stayed full.

He got requests from a media company in the Netherlands to enhance an old film of Amsterdam. Displays in the Moscow subway played a vintage video he enhanced of the Russian capital. A Polish documentary maker knocked on his door, too.

Even the USA was calling. PBS asked for help with footage for an interactive website for its documentary on women's suffrage.

They had a colorist for the still images, but even with advances in digital painting, colorizing film takes a ridiculous amount of time, said Elizabeth Peck, the business development manager for the five-person team at neural.love.

NVIDIA RTX Speeds AI Work 60x+ Along the way, Shiryaev and team got an upgrade to the latest NVIDIA RTX 6000 GPU. It could process 60 minutes of video in less time than an earlier graphics card took to handle 90 seconds of footage.

The RTX card also trains the team's custom AI models in eight hours, a job that used to take a week.

This card shines, it's amazing how helpful the right hardware can be, he said.

AI Film Editor in the Cloud The bright lights the team sees these days are flashing images of a future consumer service in the public cloud. An online self-serve AI video editor could help anyone with a digital copy of an old VHS tape or Super8 reel in their closet.

People were sending us really touching footage - the last video of their father, a snippet from a Michael Jackson concert they attended as a teenager. The amount of personal interest people had in what we were doing was striking, explained Peck.

It's still early days. Shiryaev expects it will take a few months to get a beta service ready for launch.

Meanwhile, neural.love is steering clear of the VC world. We don't want to take money until we are sure there is a market and we have a working product, he said.

You can hear more of neural.love's story in a webinar hosted by PNY Technologies, an NVIDIA partner.

LINK:	https://blogs.nvidia.com/blog/2020/10/23/ai-startup-enhances-video/...
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