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This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA.

You don’t need to be an an academic or to work for a big company to get into AI.

You can just be a guy with an NVIDIA GeForce 1080 Ti and a generative adversarial network.

Jason Antic, who describes himself as “a software guy,” began digging deep into generative adversarial networks earlier this year.

Next thing you know: he’s created an increasingly popular tool that colors old black-and-white shots to make them look good.

“I just thought that colorizing black-and-white footage was just a really cool thing to do,” Antic says in a conversation with Noah Kravitz, who hosts NVIDIA’s AI Podcast.

“I just finished my fast.ai course just two months ago. My plan was to dig deep into this neural network stuff and just hammer out a few projects,” he adds.

Antic, a website developer, was a computer science major in college more than a decade ago. But he says that helped him less than you might think.

“Honestly, artificial intelligence back then didn’t really work,” Antic says.

That changed, dramatically, starting in 2012, he says.

“Eventually I was like I really need to get into this field because it’s mind blowing,” Antic says. “It’s really going to revolutionize the world.”

So Antic dug in, taking a number of courses. He says his AI course at fast.ai really clicked for him. He even began working part time so he could focus on his studies.

When he was done, he decided he would try to create software for colorizing photographs and began putting his training — and his NVIDIA GeForce 1080 Ti — through their paces.

“I thought this would be really ambitious, but it would be really cool if it worked,” Antic says, who adds that he struggled for weeks before ultimately getting it to work.

“It works really well, way better than I thought it would,” he says.

The result — which has been posted to the GitHub code repository — has caused a sensation.

“You don’t have to necessarily know the domain in order to be successful, and that’s really the power of deep learning,” Antic says.

Interested in digging into AI for yourself? Listen and get inspired.

How to Tune in to the AI Podcast

Our AI Podcast is available through iTunes, Castbox, DoggCatcher, Google Play Music, Overcast, PlayerFM, Podbay, Pocket Casts, PodCruncher, PodKicker, Stitcher and Soundcloud. If your favorite isn’t listed here, email us at aipodcast [at] nvidia [dot] com.

 

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