Nathalie Miebach: sculpture
Sculptures and scores made from weather data about storms.
data  materiality  scores  data_art 
11 days ago
Keras: Deep Learning library for Theano and TensorFlow
Keras is a high-level neural networks library, written in Python and capable of running on top of either TensorFlow or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
ai  Deep_Learning  Keras  TensorFlow  Python 
march 2017
Smart Cities - Free online course
Explore the role of technology and data in cities, and learn how you can participate in the creation of smart cities.
smart_cities  open_university  course 
january 2017
ml4a-guides/audio-tsne.ipynb at master · ml4a/ml4a-guides
This notebook will show you how to create a t-SNE plot of a group of audio clips. Along the way, we'll cover a few basic audio processing and machine learning tasks.
tsne  audio  genekogan  sorting 
december 2016
genekogan/AudioTSNE: audio sample t-SNE in Processing
This is a simple program to display and loop through a t-SNE layout of audio samples in Processing. It also requires the Minim library for Processing which can be installed from the libraries menu.

It comes with an example, Queen's "Bohemian Rhapsody" which has been segmented with the resulting audio chunks analyzed, and t-SNEd.
tsne  audio  genekogan  sorting 
december 2016
Stealth Cell Tower - Julian Oliver
Rogue Cellular Infrastructure Disguised as Office Printer

Stealth Cell Tower is an antagonistic GSM base station in the form of an innocuous office printer. It brings the covert design practice of disguising cellular infrastructure as other things - like trees and lamp-posts - indoors, while mimicking technology used by police and intelligence agencies to surveil mobile phone users.
art  privacy  data 
december 2016
Invisible Images (Your Pictures Are Looking at You) – The New Inquiry
What’s truly revolutionary about the advent of digital images is the fact that they are fundamentally machine-readable: they can only be seen by humans in special circumstances and for short periods of time. A photograph shot on a phone creates a machine-readable file that does not reflect light in such a way as to be perceptible to a human eye. A secondary application, like a software-based photo viewer paired with a liquid crystal display and backlight may create something that a human can look at, but the image only appears to human eyes temporarily before reverting back to its immaterial machine form when the phone is put away or the display is turned off. However, the image doesn’t need to be turned into human-readable form in order for a machine to do something with it. This is fundamentally different than a roll of undeveloped film. Although film, too, must be coaxed by a chemical process into a form visible by human eyes, the undeveloped film negative isn’t readable by a human or machine.
machine_vision  computer_vision  cameras  post-photography 
december 2016
Defining the Sensor Society Conference - Centre for Critical and Cultural Studies - The University of Queensland, Australia
We are surrounded by sensors: our cars collect detailed information about our driving habits and destinations; our smart phones gather a growing array of increasingly detailed and comprehensive information about our communication activities and more. The growing network of sensors contributes to a fast-growing stream of data about everything from the weather to the details of our personal lives and our movements throughout the course of the day.

The resulting shift away from targeted, discrete forms of information collection to always-on, ubiquitous, expanding and accelerating data collection marks important changes in our understandings of surveillance, information processing, and privacy in the digital era. The sensor society therefore raises significant questions about the role of privacy, power and surveillance in the world of the ever-watching, ever-sensing, always-on interactive devices. Control over the sensing infrastructure, the databases, and the response platforms will play a crucial role in how information is used and who benefits.
conference  sensors  surveillance 
november 2016
Defining the Sensor Society
The proliferation of embedded and distributed sensors marks the increasing passive- ication of interactivity. Devices such as smart phones, cameras, drones, and a growing array of environmental sensors (both fixed and mobile) and interactive online platforms have come to permeate daily life in technologically equipped societies. Consequently, we are witnessing a shift from targeted, purposeful, and discrete forms of information collection to always-on, ubiquitous, opportunistic ever-expanding forms of data capture. The increased use of sensors marks important changes to our understandings of surveillance, information processing, and privacy. In this article, we explore the transformations associated with the emerging sensing environment. The notion of a sensor society provides a conceptual basis for understanding the characteristics of emerging forms of monitoring and control.
sensors  computer_vision  multispectral  Mark_Andrejevic  Mark_Burdon 
november 2016
Facewatch enables your business to report incidents quickly and share information with other businesses in your local community and with your local police.

Anyone can become a victim of crime therefore everyone benefits from a system that helps make communities safer and protects business profits.
surveillance  policing 
october 2016
Dan Hon s3e30: The Generative Surplus
Dan on neural networks and generative stuff. Lots of good thinks in here.
danhon  neural_networks  creativity  generative 
october 2016
An open, universal media library
Mediachain automatically connects media to its creator and information about it.
media  copyright  attribution  sharing  images 
october 2016
AI•ON: Artificial Intelligence Open Network
AI•ON is an open community dedicated to advancing Artificial Intelligence by:

Drawing attention to important yet under-appreciated research problems.
Connecting researchers and encouraging open scientific collaboration.
Providing a learning environment for students looking to gain machine learning experience.
ai  opensource  machine_learning 
october 2016
Machine learning: why we mustn’t be slaves to the algorithm | Opinion | The Guardian
I suspect that Wittgenstein would have loved this research: it confirms his belief that the meaning of a word is not to be found in some abstract definition, but in its use in everyday language. Maybe ML geeks should read his Tractatus.
goodbyewittgenstein  machine_learning  ethics  bias 
october 2016
RadarCat for object recognition
Mini radar sensor trained to recognise objects based on their reflective frequencies.
radar  sensor  radarcat  machine_learning 
october 2016
Hexagon Geospatial Smart Cities
Another corporate smart cities thingy
october 2016
Environment Survey Open Data SP08 Birmingham
Downloads of lidar scans and other data for the Birmingham area
lidar  data 
october 2016
Ethical Autonomous Vehicles - Matthieu Cherubini
Many car manufacturers are projecting that by 2025 most cars will operate on driveless systems. While it is valid to think that our roads will be safer as autonomous vehicles replace traditional cars, the unpredictability of real-life situations that involve the complexities of moral and ethical reasoning complicate this assumption.

How can such systems be designed to accommodate the complicatedness of ethical and moral reasoning? Just like choosing the color of a car, ethics can become a commodified feature in autonomous vehicles that one can buy, change, and repurchase, depending on personal taste.

Three distinct algorithms have been created - each adhering to a specific ethical principle/behaviour set-up - and embedded into driverless virtual cars that are operating in a simulated environment, where they will be confronted with ethical dilemmas.
Matthieu_Cherubini  resonate2014  ai  self_driving_cars  ethics  ideology 
october 2016
Sam Altman’s Manifest Destiny - The New Yorker
Y Combinator has even begun using an A.I. bot, Hal9000, to help it sift admission applications: the bot’s neural net trains itself by assessing previous applications and those companies’ outcomes. “What’s it looking for?” I asked Altman. “I have no idea,” he replied. “That’s the unsettling thing about neural networks—you have no idea what they’re doing, and they can’t tell you.”
ai  bias  discrimination  machine_intelligence  y_combinator 
october 2016
ConvNetJS: Deep Learning in your browser
ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat.
machine_learning  Javascript  Neural_Networks  Deep_Learning  karpathy 
october 2016
Deep-Fried Data
If you go searching for patterns in the data, you'll find patterns in the data. Whoop-de-doo. But anything fresh and distinctive in your digital collections will not make it through the deep frier.
data  ai  machine_learning  big_data  Maciej_Cegłowski 
october 2016
adrien segal
Adrien Segal is a sculptural artist based in Oakland, CA. Her work has been exhibited internationally in galleries and museums, and is published in several books and academic journals, including Boom: A Journal of California, Data Flow 2 and Arid Journal. She has been an Artist in Residence at the Bunnell Street Art Center in Alaska, Oregon College of Arts and Crafts in Portland, and at Autodesk's Pier 9 Workshop in San Francisco
artist  portfolio  dataviz  inspiration 
october 2016
Sidewalk Labs
Google's Smart Cities startup
smart_cities  Google 
september 2016
G Suite: intelligent tools designed for teams
Nice overview of where Google are implementing "machine intelligence" in mundane apps like Docs and Photos.
AI  Google  machine_intelligence  G_Suite 
september 2016
Partnership on Artificial Intelligence to Benefit People and Society
Established to study and formulate best practices on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society
ai  advocacy  google  amazon  stacks  corporate 
september 2016
Village Atheists, Village Idiots | Sam Kriss
Sam Kriss on Neil deGrasse Tyson, B.o.B., and the “rational” world of the New Atheists.
sam_kriss  atheism  science  religion 
september 2016
Everybody Freeze! | Corey Pein
Cryonics has regained an undue aura of respectability as the thought leaders of Silicon Valley have trained their vision on the conquest of death.
transhumanism  cryonics  libertarianism  californian_ideology 
september 2016
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