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Is a Three-Dimensional Search Engine a Reality?
February 8, 2021 News


When it comes to the search engine, Google has been pretty much dominating this area for the longest time. While there are other search engines available as well, Google continues to innovate its search engine to bring better outcomes and experiences to users.

Currently, when we want to search something online, we type it out and look for it, be it an article, a product or a video for example. Google is only able to give us results based on its indexing of 2D data. The reality is though, over 70% of the economy is centred around physical goods but there is less than 1% of software that is capable of handling this 3D data.

This may soon change. Physna, which was originally developed to protect product designs from theft has now evolved into the world’s leading 3D geometric deep learning software technology.

So what is a 3D geometric deep learning software?

According to information on Physna, the company believes that computers should be taught to think in 3D and accurately describe the real 3D world we live in today. By enabling 3D models to be treated and analysed like other code, Physna’s technology bridges the gap between the physical world and the digital world of software.

By democratising the ability to design, interact with and analyse 3D models of the world around them, more people will have the ability to create and drive innovation in product design, 3D printing, augmented and virtual reality, gaming, healthcare and beyond.

Last year, Physna launched Thangs, the world’s first geometric search engine for 3D models. According to reports, just a couple of days after its release, the platform is already deemed the most powerful online community for 3D model creators. Physna integrated its proprietary Artificial Intelligence algorithms into Thangs, in order to revolutionize the 3D printing workflow.

According to reports, using proprietary algorithms and advanced geometric deep-learning technology to codify 3D models into detailed data, the digitised model allows Physna to show specific and precise differences and similarities between models. This also includes incomplete models or models with different file formats. It enables the users to see all the components in complex assemblies, as well as parts contained in other parts.

The beauty of Physna’s AI technology is that it allows businesses to quickly make production predictions, estimate costs, materials and find the best suppliers. The software can predict part performance based on past data and design changes, and uncover design flaws before models are produced.

The picture above shows some of the trending models currently being searched for on the Thangs website. Since launching in August 2020, hundreds of thousands of people have used Thangs to improve their workflow in everything from product design to 3D printing, with AR/VR model compatibility soon to follow.

Why Thangs can be successful is because Google does not have the functions to search for 3D models. While Google only does indexing for 2D data such as text and images, Thangs does the extra with physical objects and 3D models.

By understanding the physical structure of 3D models across a variety of file types, Thangs reveals in-depth information about 3D designs, including complex assemblies and parts within parts.

The Physna team continues to add features at a fast pace with the announcement of significant updates to Thangs including support for more complex content types beyond simple 3D models. Thangs now support assembly files from virtually any platform, allowing users to upload massive assemblies alongside their sub-assemblies and components. Users can see how all the parts go together and through Thangs’ light version of Physna’s core algorithms, see alternative ways to build the model.

And this is where it gets interesting. Upon realising the potential of the technology, investment is pouring in, which is enabling the Physna to speed up its development with the hope of eventually becoming the Google search engine of the physical world. And we are definitely not surprised if they do make it.