RE: LeoThread 2024-11-24 12:21
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Building a Large Geospatial Model to Achieve Spatial Intelligence
At Niantic, we are pioneering the concept of a Large Geospatial Model that will use large-scale machine learning to understand a scene and connect it to millions of other scenes globally.
When you look at a familiar type of structure – whether it’s a church, a statue, or a town square – it’s fairly easy to imagine what it might look like from other angles, even if you haven’t seen it from all sides. As humans, we have “spatial understanding” that means we can fill in these details based on countless similar scenes we’ve encountered before. But for machines, this task is extraordinarily difficult. Even the most advanced AI models today struggle to visualize and infer missing parts of a scene, or to imagine a place from a new angle.
#sptaialintelligence #geospatial #ai #technology #niantic
This is about to change: Spatial intelligence is the next frontier of AI models.
As part of Niantic’s Visual Positioning System (VPS), we have trained more than 50 million neural networks, with more than 150 trillion parameters, enabling operation in over a million locations. In our vision for a Large Geospatial Model (LGM), each of these local networks would contribute to a global large model, implementing a shared understanding of geographic locations, and comprehending places yet to be fully scanned.
The LGM will enable computers not only to perceive and understand physical spaces, but also to interact with them in new ways, forming a critical component of AR glasses and fields beyond, including robotics, content creation and autonomous systems. As we move from phones to wearable technology linked to the real world, spatial intelligence will become the world’s future operating system.
What is a Large Geospatial Model?
Large Language Models (LLMs) are having an undeniable impact on our everyday lives and across multiple industries. Trained on internet-scale collections of text, LLMs can understand and generate written language in a way that challenges our understanding of “intelligence”.
Large Geospatial Models will help computers perceive, comprehend, and navigate the physical world in a way that will seem equally advanced. Analogous to LLMs, geospatial models are built using vast amounts of raw data: billions of images of the world, all anchored to precise locations on the globe, are distilled into a large model that enables a location-based understanding of space, structures, and physical interactions.
The shift from text-based models to those based on 3D data mirrors the broader trajectory of AI’s growth in recent years: from understanding and generating language, to interpreting and creating static and moving images (2D vision models), and, with current research efforts increasing, towards modeling the 3D appearance of objects (3D vision models).
Spartial Intelligence well explained man. I believe this will improve the models much more than ever.
I wonder the new tricks chatgpt can pull with spartial 🧠🧠