Author withdrawn from France's Prix Goncourt last month has repeatedly denied using artificial intelligence to write novel The publisher of top-selling Haitian Canadian writer Thélyson Orélien, who was removed from France's most prestigious literary prize list last month, has confirmed the author used artificial intelligence to help write his novel C'était ça ou mourir (It Was Either That or Die). Orélien has denied allegations that he used AI on his breakthrough novel and, last week, Canadian publisher Les Éditions du Boréal said it was standing by the 38-year-old writer. But on Wednesday, Boréal said it had conducted a further investigation into the allegations. "New information, confirmed over the past few days, indicates that artificial intelligence was used in the writing process" of the novel, a statement from Boréal said. The publisher announced it was "ending its professional relationship" with Orélien.

The French book scene is in uproar after a Canadian-Haitian author billed as a sensation was accused of using artificial intelligence (AI) to write his first novel. Thélyson Orélien, 38, has just been awarded the Prix du Roman Fnac - the first of the literary season's prizes - for C'était ça ou mourir (It was either that or die). He is also a finalist for the most prestigious annual French language awards, the Goncourt and the Renaudot, set to be issued soon. But on Tuesday a little-known group called Balance ton Claude (Denounce your Claude, in reference to Anthropic's AI assistant) claimed the book was almost totally written by AI - a charge the author denied. We tested several passages, from different bits of the manuscript, to come up with the identical result: 100 percent AI, the group said on X.

Aurélien Géron is a Machine Learning consultant. A former Googler, he led the YouTube video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, the firm that now manages the electric car sharing service Autolib'. Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Société Générale), defense (Canada's DOD), and healthcare (blood transfusion). He published a few technical books (on C, WiFi, and Internet architectures), and was a Computer Science lecturer in a French engineering school.

Data-stream clustering is an ever-expanding subdomain of knowledge extraction. Most of the past and present research effort aims at efficient scaling up for the huge data repositories. Our approach focuses on qualitative improvement, mainly for "weak signals" detection and precise tracking of topical evolutions in the framework of information watch - though scalability is intrinsically guaranteed in a possibly distributed implementation. Our GERMEN algorithm exhaustively picks up the whole set of density peaks of the data at time t, by identifying the local perturbations induced by the current document vector, such as changing cluster borders, or new/vanishing clusters. Optimality yields from the uniqueness 1) of the density landscape for any value of our zoom parameter, 2) of the cluster allocation operated by our border propagation rule. This results in a rigorous independence from the data presentation ranking or any initialization parameter. We present here as a first step the only assessment of a static view resulting from one year of the CNRS/INIST Pascal database in the field of geotechnics.