Reverse Contradictionary – Dictionary of New Worlds by @Vuk Ćosić · @iocose · Vladan Joler: book launch event as part of Vorspiel 2026

📍 panke.gallery, Tuesday, 27 January 2026, 7 PM (Gerichtstr. 23, Hof 5, 13347 Berlin)

https://panke.gallery/event/reverse-contradictionary

The entire cultural output of humanity is being fed into AI. Large Language Models are ingesting not only books, articles, and blogs in their entirety, but also the content of our private written and spoken conversations. LLMs are boiling lakes and burning down forests to generate texts based on statistical mediocrity, which we are supposed to worship as the beginning of a great new gilded age.

https://reverse-contradictionary.net

This is where Reverse Contradictionary comes into play — a collaborative effort by critical media titans Vuk Ćosić, IOCOSE and Vladan Joler. Their new Dictionary of New Worlds presents selected confrontational neologisms that, with acute insight and subtle provocation, challenge and overturn the predatory, algorithmic logic embedded in statistical language.

With a preface by Yes Men and a terrifying blurb by real Slavoj Žižek.

Appel à boycott d'entreprises en lien avec ICE, voici la liste :

- Amazon
- AT&T
- Dell
- FedEx
- Home Depot
- Lowe
- LexisNexis
- Motorola Solutions
- Palantir
- UPS

https://www.thenation.com/article/activism/ice-businesses-boycott-campaign/

« Ce n’est pas parce qu’on a des data centers en France qu’on est souverain de quoi que ce soit. »

Ces mots, ce sont ceux de la coprésidente de @dataforgood, qui organisait le 21 janvier un colloque sur les enjeux politiques et stratégiques de l’IA à l'Assemblée nationale.

La veille, une commission mixte paritaire discutait du projet de loi de simplification de la vie économique, dont l'article 15 concerne directement les #datacenters

https://next.ink/220723/data-centers-a-lassemblee-nationale-des-appels-a-questionner-la-course-au-gigantisme

#next #IA #tech

13 SCORES AGAINST TECH FASCISM — Project 3/13

JIAWEN UFFLINE - SORRI, MY DATA IS TOO DIRTY FOR YOUR MODEL @jwn

sorri, my data is too dirty for your model reverses the cleaning heuristics used for large-scale web-crawled datasets to instructions for making our data too dirty to be trained, as a bottom-up opt-out in an age where robots.txt is shamelessly ignored.

Datasets for pre-training large models have been expanded to the volume of (partial) internet, with the idea of "scale averages out noise", these datasets scrape whatever is available on the internet then “cleaned” with a human-not-in-the-loop, cheaper-than-cheap-labor method: heuristic filtering... Heuristics in this context are basically a set of rules came up by some software engineers with their imagination and estimation that are “good enough” to remove “dirty data” of their perspective, not guaranteed to be optimal, perfect, or rational...

If we know, partially, what is considered as dirty, doesn’t it mean that we can make our data “dirty” and get it filtered out by following their rigid estimation� Can we opt out from being trained by becoming unqualified� sorri my data is too dirty for your model came up with a set of anti-heuristic heuristics based on 23 datasets to have our texts and images mingle and stay close to "dirty data", purity is never an option

Exhibition website: https://error417.expectation.fail/13scoresagainsttechfascism/sorri-my-data-is-too-dirty/project
Artist website: https://worrymetaphor.net/