AIxDESIGN Bookmark Library

We are a non-profit creating more realistic and inclusive images of artificial intelligence. Visit our growing repository available for anyone to use for free under CC licences, or just to use as inspiration for more helpful and diverse representations of AI.

Data-Driven Exploitation in the Gig Economy

The latest news headlines as seen through a generative image AI. All images are created using real-time New York Times data combined with Big Sleep, VQGAN+CLIP and CLIP Guided Diffusion. Text-to-image generation techniques built on machine learning.

Type of employment: Full time.

Type of employment: Full time.

Image Generation with 0 code

At Random Studio, we create brand and service experiences that trigger a sense of wonder. Our work comes to life in the space where the digital meets the physical. As a studio, we value new ideas, new insight, new ways of seeing the world — and we are currently searching for a User Experience Designer to

A fast, dataset-agnostic, deep visual search engine for digital art history

The role of a designer is to intentionally shape the world around us with the resources we have available. That world is increasingly shaped by data sets, algorithms, and pre-trained models.

The value of a shared understanding of AI models. Model cards: a proposed first step

The Most Likely Machine is an interactive learning prototype by Artefact designed to help pre-teens develop algorithmic literacy through play.

Learn about bias and variance in our second animated data visualization.

Bust writer's block and be more creative with our magical writing AI.

Making Friends with Machine Learning was an internal-only Google course specially created to inspire beginners and amuse experts. Today, it is available to e...

AI Think Tank - Connect, Discuss, Innovate

26-27 November, Amsterdam / Online

Visit https://www.aiaaic.org/aiaaic-repository for information on what this resource is, and how it may be used

When it was first published in 1972, Hubert Dreyfus's manifesto on the inherent inability of disembodied machines to mimic higher mental functions caused an uproar in the artificial intelligence community. The world has changed since then. Today it is clear that "good old-fashioned AI," based on the idea of using symbolic representations to produce general intelligence, is in decline (although several believers still pursue its pot of gold), and the focus of the Al community has shifted to more complex models of the mind. It has also become more common for AI researchers to seek out and study philosophy. For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field.At a time when researchers were proposing grand plans for general problem solvers and automatic translation machines, Dreyfus predicted that they would fail because their conception of mental functioning was naive, and he suggested that they would do well to acquaint themselves with modern philosophical approaches to human beings. What Computers Can't Do was widely attacked but quietly studied. Dreyfus's arguments are still provocative and focus our attention once again on what it is that makes human beings unique.

Our project is a community co-designed critical card game that induces players to reflect on the absurdities of our technological present and imagine futures that are more fair.

Welcome to The Future of Memory, a provocation on algorithmic content moderation, power, profit and the ever shifting nature of language online.

Pointing out the spaces & practices emerging at this intersection.

A simple application that allows you to generate various copy with just a prompt. Its use ranges from summarizing long text, answering questions, completing thoughts and writing articles. The tool is powered completed by OpenAI's GPT-3 algorithm.

A collaboration between Serpentine Galleries R&D Platform and the Department of Digital Humanities, King's College.

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