The chairman of Popsa, a photo printing start-up, Declan Mellett explained that his company aims to simplify the process of making photobooks. “It’s always been a pain to make photobooks because you had to have your images in certain places on your computer. We’re trying to make that process so simple. The first version of the app reduced the time it took from two hours to five minutes,” he said.
One of the strategic goals since the inception of the company was to integrate algorithms and machine learning. Mellett said: “From day one, it’s been the ambition to bring in a data science team. Otherwise, we would just be a photobook app. To make us different, we have to have machine learning and artificial intelligence, and data in the business. The trick is finding the right people.”
Enter Dr Chanuki Illushka Seresinhe. She has always loved working with neural networks and saw the job opportunity as the lead data scientist at Popsa as an ideal opportunity and perfect connection. Here, she can tackle classic computer vision tasks and use the experience of her PhD in which she was working a lot with neural networks and understanding beautiful places.
She said the focus at Popsa at the moment is the elimination of the tedious tasks involved in creating a photobook, such as finding and deleting the shots that are blurry, too dark, washed out or duplicates, as well as creating groupings by people.
Mellett said: “One of the thoughts we had is to eventually teach the app the image of your mother, therefore when it comes towards Mother’s Day, we can say ‘here’s a beautiful book for Mother’s Day’. It is really to take the process away from having to tap lots of images.”
Another thing Popsa does is create groupings of photos by location. They have to look more closely at behavioural data because many people turn off location services on their phones due to privacy concerns. “We have to be clever with how we find things,” she said.
But what about the human in the loop? How important is human intervention to the photobook curation process? “We suggest things. It’s always a suggestion. It’s not like we’ve definitely got it right. The way I’d like algorithms to work is where they are suggestive, so it is not that algorithms are taking over the work for you. It’s the humans and algorithms working together,” she said.
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