
AIxDESIGN Bookmark Library
Conversation Designer, User Experience
Google | Mountain View, CA, USA; Kirkland, WA, USA; New York, NY, USA

ML Art Colabs
by dvschultz | A list of cool Colabs on Machine Learning Imagemaking or other artistic purposes

Everyday Experiments — Neverending Catalogue
Neverending Catalogue is a technical prototype which would create computer-generated bedrooms to act as an inspiration database, essentially taking on the role of an interior designer for you to consult at your leisure.

Intro to AI for Architectural Design Explorations
From Engineering ArchiTECHture | An exploration into how AI is used in architectural design hosted by AIxDesign member Mayur (who hosts amazing sessions like this on regular basis)!

VQGAN+CLIP (with pooling) on Google Colab

6: State of the Game
Listen to this episode from This Study Shows on Spotify. AI has come a long way (it even named this episode) but what does it have to do with science communication? We find the line between the present and the future as we explore how AI will affect science communication, and how has it already taken hold, with Mara Pometti, lead data strategist at IBM, and Professor Charlie Beckett, lead of JournalismAI at the London School of Economics. We want to know what you think about This Study Shows! Take a short survey and help us make this podcast the best it can be.

Generative Engine | RunwayML Experiments
A storytelling machine that automatically generates synthetic images as you write new words and sentences. Made with RunwayML

Artist Statement in AttnGAN
Typing in my artist statement 2020 to AttnGAN - text to image generator

VisualEyes - Optimize your UX via Attention Heatmaps and Clarity
Analyze user behavior, enhance UX, and optimize designs by utilizing AI generated Attention Heatmaps and Clarity score.

dvschultz/dataset-tools
Tools for quickly normalizing image datasets. Contribute to dvschultz/dataset-tools development by creating an account on GitHub.

Paper Kingdom
Digital collages based on public domain scientific illustrations of plants and animals from the Biodiversity Heritage Library.

Hugging Face – The AI community building the future.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Anatomies of Intelligence
An artistic research initiative seeking to make connections between the formats and collections of anatomical knowledge and investigations into the “anatomy” of computational learning and prediction processes, datasets and machine learning models by Joana Chicau and Jonathan Reus.

Should AI Models Be Explainable? That depends.
By Katherine Miller | A Stanford researcher advocates for clarity about the different types of interpretability and the contexts in which it is useful.

UX/UI Design Lead at Capital One - US
UX/UI lead for Capital One's Machine Learning Platform design team in VIenna.

Together
We call for collaborative practitioners in art, design and technology to explore Artificial Intelligence (AI) & Machine Learning (ML), data & networks.

Head of Design - Learn @ Datacamp
The days of learning data science by passively consuming video lectures are over. Real learning takes place when a student’s hands are on the keyboard, writing code, working with data, and solving problems. If you agree, keep reading!

Recognition
Recognition was an artificial intelligence program that compares up-to-the-minute photojournalism with British art from the Tate collection.

trekhleb/machine-learning-experiments
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo - trekhleb/machine-learning-experiments

bwang514/awesome-HAI
A curated list of awesome Human-AI Interaction. Contribute to bwang514/awesome-HAI development by creating an account on GitHub.

alsino/creative-applications-ml
All code and materials for the DAAD introductory workshop on machine learning - alsino/creative-applications-ml

yining1023/machine-learning-for-the-web
Repository for the "Machine Learning for the Web" class at ITP, NYU - yining1023/machine-learning-for-the-web

Learn Artificial Neural Networks on Brilliant
This interactive course dives into the fundamentals of artificial neural networks, from the basic frameworks to more modern techniques like adversarial models.
You’ll answer questions such as how a computer can distinguish between pictures of dogs and cats, and how it can learn to play great chess.
Using inspiration from the human brain and some linear algebra, you’ll gain an intuition for why these models work – not just a collection of formulas.
This course is ideal for students and professionals seeking a fundamental understanding of neural networks, or brushing up on basics.

HR-CMGT/Machine-Learning-Readinglist
Reading List for Machine Learning sources, API's, ideas and tutorials. - HR-CMGT/Machine-Learning-Readinglist

Wekinator | Software for real-time, interactive machine learning
