Tag: ai

Thinking with machines: Some reflections on LLMs in academia

As somebody who studied computer science in the early 2000s, I find large language models (LLMs) like GPT and Claude an extraordinary, science-fiction-like technology. While sharing many concerns with sceptics like Gary Marcus, I believe LLMs are so disruptive because they truly are amazingly good at understanding natural language and performing countless tasks that used … Continue reading Thinking with machines: Some reflections on LLMs in academia →

SMAU London 2024: AI, geographic data, and the future of innovation

Today, I had the privilege of speaking at SMAU | Italy RestartsUp in London, an event dedicated to the Italian startup scene 🇮🇹🚀 — the panel I contributed to focused on the impact of digitalisation and new technologies. It was a real pleasure to see companies operating in areas close to my academic heart, at … Continue reading SMAU London 2024: AI, geographic data, and the future of innovation →

Technological failures, controversies and the myth of AI

Pleased to have a new book chapter out in a book edited by Simon Lindgren, the leading digital sociologist: 📜 A. Ballatore & S. Natale (2023) Technological failures, controversies and the myth of AI. S. Lindgren (ed.) Handbook of Critical Studies of Artificial Intelligence. Edward Elgar. [web] "In the popular imagination, the history of computing is often represented … Continue reading Technological failures, controversies and the myth of AI →

GeoAI in Urban Analytics

This special issue on GeoAI led by Stef De Sabbata et al. is finally out! 🌍📈🤖🌆. 📜 Stefano De Sabbata, Andrea Ballatore, Harvey J. Miller, Renée Sieber, Ivan Tyukin & Godwin Yeboah (2023) GeoAI in urban analytics, International Journal of Geographical Information Science, 37:12, 2455-2463, DOI: 10.1080/13658816.2023.2279978 [web] (Image from Bing Create) We are writing … Continue reading GeoAI in Urban Analytics →

Computing urban form with graph neural networks

This nice paper led by Stef De Sabbata was presented at the GeoAI workshop in Leeds 🌍📈🤖🌆. 📜 Stefano De Sabbata, Andrea Ballatore, Pengyuan Liu and Nicholas J. Tate (2023) Learning urban form through unsupervised graph-convolutional neural networks. 2nd International Workshop on Geospatial Knowledge Graphs and GeoAI: Methods, Models, and Resources (GIScience 2023, September 12th, … Continue reading Computing urban form with graph neural networks →