Driven by the wave of digitalization, Large-Scale AI Model technology has become a shining star in the global science and technology community, bringing broader imagination and deeper changes to all walks of life. In term of main techniques, natural language processing (NLP) big models make human-computer dialogue scenarios more mature, computer vision (CV) big models become a new path to improve image interpretation accuracy and generalization, and multi-modal big models are expanding towards video generation, three-dimensional scene generation and physical simulation... It is fair to say that Large AI Models are developing rapidly. However, although various basic big models have blossomed everywhere, there is still a long way to go before they can be implemented in vertical fields.
The development of AI technology has brought opportunities for intelligent transformation to the GIS industry. In 2014, the GIS industry first proposed the concept of Geospatial Intelligence (GI). Entering the AI 2.0 era, what new technical roadmap, product forms and application models will Large AI Models bring to geospatial intelligence?
01 What new progress can be expected from the big model of remote sensing intelligent interpretation?
In terms of remote sensing intelligent interpretation, although the traditional deep learning technology has been widely used, the differences in time, space, and resolution of remote sensing images make it complicated to interpret. It is often necessary to train intelligent interpretation models for specific tasks. The overall generalization ability of the model is weak and the migration cost is high. The emergence of Large Models in the CV field such as SAM (Segment Anything Model) has provided a new technical development direction for remote sensing intelligent interpretation. On the other hand, most of the general large models in the CV field are based on daily image training, and their performance in remote sensing image interpretation is limited. Therefore, large models of remote sensing intelligent interpretation suitable for vertical industry applications are highly anticipated.
02 How to apply the general large language model to GIS?
In terms of natural language, OpenAI's GPT series has brought a number of natural language large models (LLMs) to the forefront, but general natural language large models have general problems such as low answer credibility and low value concentration. How to introduce it into the GIS industry? To what extent can large models replace professionals? How to ensure data security and answer controllability? In addition to creation and chatting, what other more advanced uses will the natural language large models have in the GIS industry? These are the directions that guide the future exploration in the GIS industry. With the emergence of various Agent, Copilot, and Assistant, a revolutionary application interaction method in the GIS industry is about to emerge.
AI will be an important driving force for the development of the GIS industry in the next decade. A journey of a thousand miles begins with a single step. In the AI 2.0 era, what new transformative technologies will geospatial intelligence usher in? What sparks can GIS and Large AI Models create?
From June 25 to 26, the 2024 Geospatial Intelligence Software Technology Conference (GISTC 2024) with the theme of "Geospatial Intelligence, Driving Quality Development" will be held at the National Convention Center in Beijing, China. It will focus on new technologies of geospatial intelligence, new achievements of Large AI Models, new ideas for informatization in various industries, etc. We look forward to your participation!
