New AI tools ready to revolutionize 3D engineering

After decades of hope, hype and false starts, it seems that artificial intelligence (AI) has finally moved from throwing sparks to catching fire. Tools like DALL-E and ChatGPT have grabbed the spotlight and the public imagination, and this latest wave of AI looks poised to be a game-changer across multiple industries.

But what impact will AI have on the 3D engineering space? Will designers and engineers see significant changes in their world and their daily workflows, and if so, what will those changes look like?

Design assistance and simulation

It’s like a law of the universe: AI brings value wherever there’s a huge amount of data, and the 3D engineering space is no exception.

Thanks to the huge datasets that many technical software vendors already have at their disposal – in many cases we are talking about millions of models — AI has a wealth of data to draw from for design guidance and design optimization.

For example, if an architect wants to put a certain type of room – perhaps a laundry room – in a house or apartment with a certain floor plan, the AI ​​in the Building Information Modeling (BIM) software has seen plenty of successful examples. of this is done in other situations to know exactly how to make this happen seamlessly.

AI can also start carrying some of the burden when it comes to finalizing a design. For example, by typing a prompt to “make this building look more attractive,” a designer could prompt AI to populate an architectural drawing with 3D models of perhaps just the right type of furniture, or some perfectly manicured trees and hedges . front side. All the designer needs to do is approve the AI’s proposed additions. This kind of help will make the real human’s life in front of the computer screen much, much easier.

We will see more and more roles like this for AI, where it serves as an assistant embedded in computer-aided design (CAD) programs, working side-by-side with the designer and springing into action when prompted .

Similarly, AI’s ability to learn from large data sets and understand what it learns can help in simulation. In both design aid and simulation, these capabilities are still evolving and will take years to realize their full potential, but they will gradually be able to take more and more items off the human plate – significantly increasing the productivity of individual designers and engineers . the process.

New ways of 3D visualization

AI also has some interesting implications when it comes to reconstructions and digitizations of the physical world. Example: We are now at a stage where we can give AI some basic 2D images of a given building or object, and it will create a full 3D, volumetric representation (i.e. not just a superficial surface model) of that item.

This is thanks to neural radiation fields (aka NeRFs), AI-powered rendering models that take in multiple 2D viewpoints and then do some internal calculations and extrapolations to generate a 3D model from those 2D images.

3D object recognition

Of course, as photos and 2D images become increasingly useful source material for creating a 3D model, point clouds – which are created by scanning objects or structures – will still remain a valuable source of data.

AI also has some great potential applications here. Similar to how AI has become quite adept at recognizing features in photos – identifying the furry, four-legged thing in a photo as a “dog” while identifying the rectangular object as a “couch” – it can offer similar capabilities to pointable cloud data, which helps track down hyperspecific features in the sea of ​​scanned points or triangles. Examples include the ability to identify the walls and ceiling of a scanned building or holes and other features in a complex CAD assembly.

However, amid all these AI-assisted developments in visualization and object recognition, there are implications for the graphics capabilities of engineering software. Many products already manage both mesh and point clouds, but in the near future they may need to manage NeRFs and other representations, while also finding a way to coexist between the different representations.

Of course, that’s part of the beauty of breakthrough innovations like AI: As its impact ripples through the larger ecosystem, other technologies should similarly respond to the new world it creates, spurring even more innovation.

Uncertainty and opportunity in 3D engineering

After a slow build, AI has reached a tipping point – and the 3D engineering world will feel its impact in ways that range from extensions of what is already possible to surprising new capabilities and functionality. For the designer or engineer, this is nothing to be afraid of. While AI may be the number one game-changer for years to come, bringing massive change and uncertainty, it also promises to change the game in interesting ways, helping designers and engineers tackle their work and transform the world. shape us more efficiently. more creativity and new levels of virtuosity.

Eric Vinchon is VP of Product Strategy at Tech Soft 3D.