On the opportunities and challenges of foundation models for geospatial artificial intelligence
Large pre-trained models, also known as foundation models (FMs), are trained in a task-
agnostic manner on large-scale data and can be adapted to a wide range of downstream …
agnostic manner on large-scale data and can be adapted to a wide range of downstream …
[PDF][PDF] Artificial general intelligence (AGI) for education
Artificial general intelligence (AGI) has gained global recognition as a future technology due
to the emergence of breakthrough large language models and chatbots such as GPT-4 and …
to the emergence of breakthrough large language models and chatbots such as GPT-4 and …
Multimodality of ai for education: Towards artificial general intelligence
This paper presents a comprehensive examination of how multimodal artificial intelligence
(AI) approaches are paving the way towards the realization of Artificial General Intelligence …
(AI) approaches are paving the way towards the realization of Artificial General Intelligence …
Sphere2Vec: A general-purpose location representation learning over a spherical surface for large-scale geospatial predictions
Generating learning-friendly representations for points in space is a fundamental and long-
standing problem in machine learning. Recently, multi-scale encoding schemes (such as …
standing problem in machine learning. Recently, multi-scale encoding schemes (such as …
Knowledge graphs: introduction, history and, perspectives
Abstract Knowledge graphs (KGs) have emerged as a compelling abstraction for organizing
the world's structured knowledge and for integrating information extracted from multiple data …
the world's structured knowledge and for integrating information extracted from multiple data …
[PDF][PDF] Symbolic and subsymbolic GeoAI: Geospatial knowledge graphs and spatially explicit machine learning.
The field of Artificial Intelligence (AI) can be roughly divided into two branches: Symbolic
Artificial Intelligence and Connectionist Artificial Intelligence (or so-called Subsymbolic AI) …
Artificial Intelligence and Connectionist Artificial Intelligence (or so-called Subsymbolic AI) …
Explainable GeoAI: can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection
Improving the interpretability of geospatial artificial intelligence (GeoAI) models has become
critically important to open the 'black box'of complex AI models, such as deep learning. This …
critically important to open the 'black box'of complex AI models, such as deep learning. This …
Exploring new frontiers in agricultural nlp: Investigating the potential of large language models for food applications
This paper explores new frontiers in agricultural natural language processing (NLP) by
investigating the effectiveness of food-related text corpora for pretraining transformer-based …
investigating the effectiveness of food-related text corpora for pretraining transformer-based …
Agi for agriculture
Artificial General Intelligence (AGI) is poised to revolutionize a variety of sectors, including
healthcare, finance, transportation, and education. Within healthcare, AGI is being utilized to …
healthcare, finance, transportation, and education. Within healthcare, AGI is being utilized to …
Performance benchmark on semantic web repositories for spatially explicit knowledge graph applications
Abstract Knowledge graph has become a cutting-edge technology for linking and integrating
heterogeneous, cross-domain datasets to address critical scientific questions. As big data …
heterogeneous, cross-domain datasets to address critical scientific questions. As big data …