Here Threedy AI has two different approaches: According to Nima, this gives far better results.Īfter a shape has been found, the second problem becomes finding the material of the object. ![]() Threedy AI so has built a database of 10,000 possible shapes and thanks to a patent-pending machine learning technology, every time it is fed a photo, it tries to reconstruct which mixing of the preset simple shapes can give a projection that is compatible with the photos provided. If an AI could understand what parts a single object is built of, then it could reconstruct the whole shape of the object. So they thought that most objects are made of parts, that usually have a simple shape. They so started thinking about an alternate approach, also because we as humans do not reconstruct in our mind the 3D shape of an object from a photo by imagining a shape that can fit a projection. They started with the usual deep learning approach, where basically you try to infer the 3D shape of an object by creating dynamically a shape whose projection becomes similar to the images that you already have, but the results were pretty unsatisfying. “We had no idea on how to solve this problem after we had raised the money” candidly said Nima to me. This conversion has been made with Threedy AI algorithm (Image by Threedy AI) How does it technically work? From the picture of a table (left) to its 3D model, fully navigable (right). He has worked since then to exploit AI and ML to create 3D models automatically from their corresponding 2D photos, an item that online shops already have. He understood that the world would have needed an automated solution to create 3D models in a fast and cheap way, so he dropped out from Apple, and with a team of talented people, he co-founded the startup now known as Threedy AI. But he immediately realized that “3D content problem would have been the issue”: to offer this AR feature, shops and stores would have needed the 3D models of all their objects, something that most of them lack. Nima Sarshar was working at Apple when ARKit was being developed and he immediately understood the possibilities that AR offered, especially for e-commerce, because AR is great to try things at home, and can make the life of customers better. As a consultant, I’ve found myself in this situation many times, and I lost many customers because just to have an AR shop they had to spend 20-50K upfront only for the 3D models and it was a too big expense for them.īut luckily there are some companies that, like the Portuguese investor, had the intuition of trying to create a bridge between the two different worlds, and among them, one of the most interesting ones is Threedy AI. ![]() And if Amazon can (maybe) have a huge AI in-house do that, medium-sized companies don’t have these means, and they should ask a 3D artist do the work for them, with huge upfront costs. All the most important shops, like Amazon, eBay, etc… have plenty of 2D pictures of their items, but very limited access to 3D models of them, and this is a big problem to implement immersive solutions. This transition can be very painful as well: for instance, we all dream of shops becoming fully virtual, of e-commerce websites all implementing AR, but this has a huge bottleneck: the creation of all the 3D models. Now I think that we are in another transitional moment: from a digital world in 2D to another one that is fully spatial, in 3D, thanks to AR and VR. He told me that he became rich by creating analog/digital converters: he noticed that all the world is analog, but in those years, everything was transitioning to digital, so he had the smart idea of creating the products that could be the bridge between these two worlds and he made a very profitable business out of it. Otherwise, keep reading for the usual summary of the key points of the interview □ The transition from 2D to 3DĪt the European Innovation Academy, some years ago, I met with José, a Portuguese investor. Thanks Nima for taking the time to answer my questions!
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