As AI becomes both more general and more foundational, it shouldn’t be seen as a disembodied virtual brain. It is a real, material force. AI is embedded into the active, decision making systems of real world systems. As AI becomes infrastructural, infrastructures become intelligent.
As artificial intelligence becomes infrastructural, and as societal infrastructures concurrently become more cognitive, the relation between AI theory and practice needs realignment. Across scales – from world-datafiction and data visualization to users and UI, and back again – many of the most interesting problems in AI design are still embryonic.
Natural Intelligence emerges at environmental scale and in the interactions of multiple agents. It is located not only in brains but in active landscapes. Similarly, artificial intelligence is not contained within single artificial minds but extends throughout the networks of planetary computation: it is baked into industrial processes; it generates images and text; it coordinates circulation in cities; it senses, models and acts in the wild.
This represents an infrastructuralization of AI, but also a ‘making cognitive’ of both new and legacy infrastructures. These are capable of responding to us, to the world and to each other in ways we recognize as embedded and networked cognition.
AI is physicalized, from user interfaces on the surface of handheld devices to deep below the built environment. As we interact with the world, we retrain model weights, making actions newly reflexive in knowing that performing an action is also a way of representing it within a model. To play with the model is to remake the model, increasingly in real time.
How might this frame human-AI interaction design? What happens when the production and curation of data is for increasingly generalized, multimodal and foundational, models? How might the collective intelligence of generative AI make the world not only queryable, but re-composable in new ways? How will simulations collapse the distances between the virtual and the real? How will human societies align toward the insights and affordances of artificial intelligence, rather than AI bending to human constructs? Ultimately, how will the inclusion of a fuller range of planetary information, beyond traces of individual human users, expand what counts as intelligence?
Individual users will not only interact with big models, but multiple combinations of models will interact with groups of people in overlapping combinations. Perhaps the most critical and unfamiliar interactions will unfold between different AIs without human interference.
Cognitive Infrastructures are forming, framing, and evolving a new ecology of planetary intelligence.
core Principles
Rather than approaching Artificial Intelligence as the imitation of the human, Synthetic Intelligence starts with the emerging potential of machine intelligences. Core principles include:
Computation is not just calculation, but the basis of a new global infrastructure of planetary computation remaking politics, economics, culture and science in its image.
The ongoing emergence of AI represents a fundamental evolution of that global infrastructure, from stacks based on procedural programming architectures, to ones based on training, serving and interacting with large models: from The Stack to AI Stack.
Machine intelligence is less a discrete artificial brain than the pervasive animation of distributed information sensing and processing infrastructures.
”Antikythera” refers to computation as both an instrumental technology–a technology that allows us to do new things, as well as an existential technology–a technology that discloses and reveals underlying conditions.
As existing technologies have outpaced legacy theory, philosophy is not something to be applied to or projected upon technology, but something to be generated from direct, exploratory encounters with technology.
Research Briefs
Lectures
Studio Projects
The studio functions as a conduit for projects that turn early weak signals into narratives that inform investment horizons. It produces “foresight media” in the form of collaborative research driven speculative projets; films, papers, interfaces and protototypes operating as propositional tools to build shared vocabularies and scaffold new practices for an era defined by planetary computation.
Antikythera Studio 2024
Studio Researchers
Artificial & Distributed Intelligence Lab, Researcher
PhD Researcher, Lecturer
Engineer, Design Researcher
University of Oxford, PhD Student
MSc Student, AI Researcher
Interdisciplinary Artist, Technologist
DeepMind, Research Engineer, PhD Student
Lecturer, Technical Artist
Cambridge University, MPhil Ethics of AI, Data & Algorithms
Creative AI Lab, PhD Researcher
Artist, Programmer
Computer Vision Researcher
Google, Senior AI Researcher
AI/ML Researcher
Writer, Filmmaker & Researcher
Affiliate Researchers
Google Research Cerebra, Vice President
UC Berkeley, Associate Professor
UC Berkeley, Researcher, Lecturer
Media Artist, Researcher & Performer
DeepMind, Software Engineer, Researcher
Writer, Designer
University of Oxford, Historian, Author
Science Fiction Writer, Author
Arizona State, Astrobiologist, Theoretical Physicist
Studio Interns
Studio Intern
Architect, Designer
University of the Arts London, MA Narrative Environments student
PhD student, multidisciplinary designer
University of the Arts London, MA Narrative Environments student
Antikythera