3D modelling capabilities are the crux of the metaverse. However, creating photorealistic 3D images is still a time-consuming and resource-intensive process. For instance, Google's DreamFusion typically requires multiple hours and GPUs to generate the images.
At this point in time, the release of point E, with its stupendous magnitude, sounds nothing less than a revolution. Not just for 3D enthusiasts but also for brands and marketers, as the metaverse provides a unique, fresh new way to connect with customers.
Be it a building, an environment, or any objects required to run a business in the virtual world, bolstering the 3D modelling capabilities is crucial. Point E will possibly accomplish this by lessening the time consumption for 3D object creation and enhancing the 3D designers’ productivity.
However, Point-E is not without its share of potential flaw. It shows inaccuracies in creating 3D images from time-to-time and is not yet fully perfect. Nevertheless, its speed and inexpensive optimization procedures outweigh its disadvantages, paving the way for a content-hungry metaverse. With improvements in machine learning algorithms, it can possibly be refined to create realistic 3D models.