Category Archives: Algorithms
MarI/O
A self learning genetic algorithm finding its way through the maze of Super Mario’s games. Exhibiting a behavior similar to Shannon’s mouse in the previous post.
There is no home like place
“Airbnb is a global hotel filled with the same recurring items. Bed, chair, potted plant, all catered to our cosmopolitan sensibilities. We end up in a place that’s completely interchangeable; a room is a room is a room. An algorithm finds these recurring items and replaces them with the same items from other listings. By […]
Detection of Face Morphing Attacks by Deep Learning
Identification by biometric features has become more popular in the last decade. High quality video and fingerprint sensors have become less expensive and are nowadays standard components in many mobile devices. Thus, many devices can be unlocked via fingerprint or face verification. The state of the art accuracy of biometric facial recognition systems prompted even […]
a close listening to the technical workings of computers and their networks
In Algorhythmics: Understanding Micro-Temporality in Computational Cultures, Shintaro Miyazaki discusses the importance of rhythm to understand the performances of algorithms. “According to Burton [chief engineer of the Manchester Small-Scale Experimental Machine-Resurrection-Project], the position of the so-called “noise probe” was variable, thus different sound sources could be heard and auscultated. These could be individual flip-flops in […]
The cloudy days of machine learning
Once upon a time, the US Army wanted to use neural networks to automatically detect camouflaged enemy tanks. The researchers trained a neural net on 50 photos of camouflaged tanks in trees, and 50 photos of trees without tanks. Using standard techniques for supervised learning, the researchers trained the neural network to a weighting that […]
Convolutional Network, 1993
In 1988, Yann LeCun joined the Adaptive Systems Research Department at AT&T Bell Laboratories in Holmdel, New Jersey, United States, headed by Lawrence D. Jackel, where he developed a number of new machine learning methods, such as a biologically inspired model of image recognition called Convolutional Neural Networks, the “Optimal Brain Damage” regularization methods, and […]
Geoff Cox, from Speaking Code to algorithms
Geoff Cox discussing the ecology of algorithms at the occasion of the launch of the Cqrrelations website. “What would algorithms say if they could speak? We could say the same of data of course. If it was allowed to speak what would it say about itself? It probably wouldn’t say it is raw and unmediated. […]
Algorithms before computers
“The only way you could formulate a complete rule (in premodern sensibility): you had to foresee the exceptions, it is both specific and supple. The habit doesn’t simply enforce the rule, it embodies it, just like this spearbearer statue embodies the canon of male beauty. More than that the habit’s discretion is not supplementary to […]
Comparative Ways of Seeing
Your browser does not support the video tag. In the frame of Ways of Machine Seeing, a series of experiments in collaboration wit Geoff Cox on the the four episodes of the BBC documentary series Ways of Seeing. In this probe, the same algorithm runs an object detection script using two different training sets. For […]