Eschatology of the Digital Visage,
Giorgi Vachnadze
fieldware, Ian Margo
Vertigo2, Alexandre Montserrat
third extension, Ian Margo
After Notre Dame, Arash Farhadi
Automemoriel, Alexandre Montserrat
the wet box, Ian Margo
Ruins without nostalgia, Marcos Parajua
Heliodromus, Levi Yitzhak
my beloved new face, Ian Margo
GATE-1, Ian Margo
Touch Down, Entropocene, Shāng Wén Shān
Officially Affiliated Observer, Pavel Polshchikov
Alexandre Montserrat
profile founder researcher artist memory language LLMs AI interface policy cognition ontology
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Alexandre Montserrat (世然) (b. 2000, Shanghai, China) is an artist and researcher working across generative AI, sound, performance, and speculative design. Their practice explores recursive memory, symbolic infrastructure, and the aesthetics of machine cognition. They are a co-founder of 邊界_RG & previously co-founded HALOWARE, a rapid prototyping and experimental manufacturing lab.
Attuned to the politics of perception and the conditions of sense-making, they examine how architectures of remembrance, whether technological, linguistic or mythopoetic, govern historical transmission and co-constitute posthuman modes of attention, agency, and world-making.
They have presented work at various international institutions such as ICA London, OOT Festival and Frontier Tower, San Francisco. Their contributions to a finalist project for the 2024 SOLO AI award included original sound design and installation development. As a writer, Alexandre contributes to platforms including DIFFRACTIONS, investigating emergent forms of technical memory and their reshaping of human temporality across theoretical and policy frameworks.
entries
Vertigo²
Alexandre Montserrat
publication
(...) Historical representation's progressive unmooring from positivist certitude, its recognition as a discursively and mythically shaped domain, discovers a potent contemporary inflection with Large Language Models. Such systems appear, offering less passive archival functions or neutral narrative conduits, more formidable ‘writing machines’ actively operationalising the construction of historical understanding. An LLM, in this capacity, presents an unprecedented historiographical agent. It moves beyond recording or interpreting the past to effectively generate textual instantiations, guided by an intrinsic, data-derived logic...(more)