Large language models have broken take-home exams. Students generate polished work they cannot explain under follow-up questioning. Oral examinations are a natural countermeasure -- they require real-...

We are all having to keep revising upwards our assessments of the mathematical capabilities of large language models. I have just made a fairly large revision as a result of ChatGPT 5.5 Pro, to whi…

As artificial intelligence (AI) tools, particularly large language models (LLMs), enable the rapid production of large quantities of relatively high-quality text and other forms of content, human language may also be facing a revolution comparable to industrialization. However, automated and standardized language generation faces many issues, such as insufficient diversity, which may lead to risks like knowledge collapse. In this paper, I introduce the concept of language industrialization to refer to this phenomenon. While the short-term effects of language industrialization have already become evident in certain fields (e.g., academia), its long-term effects in other areas will require careful monitoring and thorough analysis.

Behind the rapid progress of artificial intelligence lies a growing concern: the environmental footprint of AI systems. From the energy demands of large-scale model training to the extraction of criti...

Coding remains one of the most fundamental modes of interaction between humans and machines. With the rapid advancement of Large Language Models (LLMs), code generation capabilities have begun to sign...

In this paper, we present a thorough analysis of the impact of Large Language Models (LLMs) on Wikipedia, examining the evolution of Wikipedia through existing data and using simulations to explore po...

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Large language models (LLMs) are increasingly impacting human society, particularly in textual information. Based on more than 30,000 papers and 1,000 presentations from machine learning conferences, ...