Electric speech is a clouds reading machine which is able to translate abstract cloudy shapes into a proper english. It’s a part of an ongoing speculative transmedia documentary started in respublica Tuva in 2015 and it’s also a web publishing and the remain of one of the first machine happening.

Inspired by both Do android dream of electric sheep? from Philip K. Dick and the relationship between datas, speeches and images in politic and contemporary mass medias as defined by Adam Curtis in Hypernormalisation as a part of a risks management system initiated with Aladdin, a super computer dedicated to the risk management division of the world largest investment management corporation, BlackRock, Inc. Electric speech is attempting to turn a useful system, which is used to shape our financial and digital realities, into a poietic counter-system.

In the early begining, we used Andrej Karpathy’s torch implementation of the models proposed by Vinyals et al. from Google (CNN + LSTM) and by Karpathy and Fei-Fei from Stanford (CNN + RNN). Both models take an image and predict its sentence description through a Recurrent Neural Network (either an LSTM or an RNN). Firstly, we trained the models by using a custom dataset made from 1 million images and related hashtags as labels from Flickr. This solution leaded the language structure to gracefully fails at express complex concepts in a proper English but, at the same time, it was absorbing as a poetic proposal and process. Finally, we decided to use im2txt and the Inception v3 model which was released on Github in 2016. We used a pretrained checkpoint on the Imagenet dataset and finetuned it for months on the MS-COCO dataset. We wanted to use an “alternative intelligence” as close as possible as its used in industrial and competitive contexts.

Firtsly, we wanted to present a live streaming of the A.I performing but since the learning phase is separated from the performing phase on actual neural network solutions we didn’t see any reasons to go that way and decided to present a recorded stream of a machine happening occured on 03/01/2017 at 5:17pm (Paris Time).