The Chinese Room

John Searle offers a contrasting point of view to the previous post and its “solve AI and you solve the problems of the world AI” optimism. His Chinese Room thought experiment is a powerful critique of strong AI. There is something wonderfully Borges-esque about Searle’s imagery in this, something akin to the Library of Babel, as one mechanically shifts from input, to database, to code, to output, and the baroque infinitude of such an undertaking. But what about boredom in this, the human (conscious) impulse to introduce humor, playfulness, creativity into the most repetitive tasks?

In this video of a recent talk at Google, Searle expounds on the Chinese Room, as well as his theories on epidemiological- vs. ontological – subjectivity and its critique of the possibility of machine consciousness as a category error. I will need to think about this a bit more, though we might ask, as Hassabis points out, if the question of machine consciousness (at least one predicated on the human/mammalian brain and experience of consciousness) is even an appropriate question for the development of AI.

Searle, a key philosopher in the analytical tradition, is also famous for his not-so-friendly exchange with Derrida over speech-act theory.

Demis Hassabis + DeepMind

Some very interesting emerging work from the leader of DeepMind, now part of Google, and its research into AI, Deep Learning. His incredible background goes from chess master at the age of 13, design of the video game Theme Park at 17, a PhD in neuroscience, and finally the founding of DeepMind and its purchase by Google in 2014. DeepMind recently made the news for its AlphaGo program, which beat the European Go champion. A couple recent lectures:


Thinking Skin

Some great links on the biology, cognition, and behavior of octopus, cuttlefish, and other cephalopods, including the incredible morphology of their arms and skin, and attendant development of their highly distributed neurological system (same number of neurons as a cat, but 2/3 distributed throughout the arms) and associated behavior (mimicry, camouflage, mesmerization, and other nomadic/”soft” tactics).


Marine biologist describing the mechanisms of octopus skin coloration. VERY USEFUL

Great video of octopus and the beer bottle – squeezing and adaptive coloration. VERY USEFUL

Overview of octopus morphology and intelligence. USEFUL, esp. at 3:40

Great overview of octopus neurology.

Arduino Basics (Automated Inflation)

(The first foray into Arduino programming. Pretty much following built-in examples for driving DC motors and reading analog sensors (here a IR distance sensor). The fan here was nowhere near powerful enough to inflate even a small garbage bag, but I think the principle is useful, and hopefully this is the start of a series of experiments.

And a couple useful links for future development:


Hutong Agency

This is a project was developed by student Dongni Lu as part of the Fluid Spaces studio by Profs Sheng Qiang and myself at Tianjin University School of Architecture in the Spring of 2012. It explores the evolving relationship between the production of space and the organization of social activity in the hutong alleyways of Tianjin, China.  This project simulates the process by which these alleyway streets are shaped through the encroachment and decay of house boundary walls into the public space of the street. The patterns of occupation of the public space and the highly localized street topology serve to define one-another through this historic process of accretion. Overall the system seeks a dynamic equilibrium between the conflicting desires for the expansion of private space vs. the need for the constitution of a functional public domain for circulation, social gather, commerce, and play.


Dynamic Bus Routing

Examples of the simulation of a dynamic bus routing system running on the streets of Chicago. Work completed by Profs. Thomas Kearns + Jordan Kanter and students Adam Weissert, Haidong Fei, and Li Gong as part of the Urban Data Model Prototype Studio at IIT in 2013-2014.

whiteboard systems diagram: interaction of bus, rider, and street network objects in simulation
bus routing diagram: indicating the process of describing catchment zones based on an updated voronoi diagram of current bus route to determine which bus in the system to assign a new pick-up to and thus rerouting the buses
process for generating riders (pickup location + destination) based on analysis of demographic data


process of assigning weighted lengths for each edge in the street graph based on various city data and spatial inputs: number of street trees, sidewalk widths, pothole complaints, expected ridership, etc.