AIxDesign Library

AIxDesign Library

1622 bookmarks
Newest
Mapping AI in the Global South
Mapping AI in the Global South
A new project to identify sites and vocabularies of digital IDs and AI
·points.datasociety.net·
Mapping AI in the Global South
Guidelines overview - Microsoft HAX Toolkit
Guidelines overview - Microsoft HAX Toolkit
What are the Guidelines for Human-AI Interaction? The Guidelines are a set of 18 generally applicable best practices for designing human-interaction with AI-based products and features. The Guidelines are divided into four groups, based roughly on when they are the most relevant to interaction with an AI system: upon initial interaction, during interaction, when the AI system […]
·microsoft.com·
Guidelines overview - Microsoft HAX Toolkit
Careers (We are hiring!) — yoona.ai
Careers (We are hiring!) — yoona.ai
We are tech, innovative and creative! Sound like your values as well? Then don’t hesitate to get in touch with us. Send us your application with the position and short motivation via email. We are constantly growing and might have an open position for you!
·yoona.ai·
Careers (We are hiring!) — yoona.ai
(1) Spawning (@spawning_) / Twitter
(1) Spawning (@spawning_) / Twitter
Tools for artists to own and manage their AI training data. Opt in or opt out of AI training - https://t.co/2ndEeE3sde Made for artists, by artists 🦾
·twitter.com·
(1) Spawning (@spawning_) / Twitter
Ando - AI Copilot for Designers | Figma Community
Ando - AI Copilot for Designers | Figma Community
Figma Community plugin - Ando AI helps you generate millions of design ideas from prompts, shapes, and images. Note: You will need an ando.studio account for this plugin. Note: This plugin is still in early beta. Many issues are being fixed, please contact antonio@ando.studio for reporting bugs, thank you!
·figma.com·
Ando - AI Copilot for Designers | Figma Community
The Follower
The Follower
How does this work? Recorded a selection of open cameras for weeks. Scraped all Instagram photos tagged with the locations of the open cameras. Software compares the Instagram with the recorded footage. I launched the project on 12 September 2022. The YouTube video was just created with results of 10 days. I will publish new…
·driesdepoorter.be·
The Follower
NEW INC - Production Coordinator
NEW INC - Production Coordinator
Job Title Production Coordinator Department NEW INC FLSA Status Non-Exempt Employment Status Full-Time Hours Per Week 40 hours Union Position Yes Grade Level 1 Salary $50,265 Union Position Yes Reports to NEW INC Director About NEW INC NEW INC is an interdisciplinary program of the New Museum that brings together 100 creative practitioners and entrepreneurs
·nyfa.org·
NEW INC - Production Coordinator
NEW INC - Program Manager
NEW INC - Program Manager
Job Title Program Manager Department NEW INC FLSA Status Exempt Employment Status Full-Time Hours Per Week 40 hours Union Position Yes Grade Level 4 Salary $65,000 Union Position Yes Reports to Associate Director of Public Programs and Operations About NEW INC NEW INC is an interdisciplinary program of the New Museum that brings together 100 creative
·nyfa.org·
NEW INC - Program Manager
The Supporting Act
The Supporting Act
The Supporting Act Foundation is a non-profit organization designed to support emerging artists and community-centered initiatives.
·thesupportingact.org·
The Supporting Act
08: Humans in the Loop
08: Humans in the Loop
Listen to this episode from NerdOut@Spotify on Spotify. Get ready: we’re diving into machine learning. Hear how we’re improving personalization with reinforcement learning (RL), what makes ML engineering so different from other kinds of software engineering, and why machine learning at Spotify is really about humans on one side of an algorithm trying to better understand the humans on the other side of it. Spotify’s director of research, Mounia Lalmas-Roelleke, talks with host Dave Zolotusky about how we’re using RL to optimize recommendations for future rewards, how listening to more diverse content relates to long-term satisfaction, how to teach machines about the difference between p-funk and g-funk, and the upsides of taking the stairs. Then Dave goes deep into the everyday life of an ML engineer. He talks with senior staff engineer Joe Cauteruccio about what it takes to turn ML theory into code, the value of T-shapedness, the difference between inference errors and bugs, using proxy targets and developing your ML intuition, and why in machine learning something’s probably wrong if everything looks right. Plus, an ML glossary: our guests educate us on the definitions for cold starts, bandits, and more. This episode is the first in a series about machine learning and personalization at Spotify. Learn more about ML and personalization: Listen: Spotify: A Product Story, Ep.04: “Human vs Machine” Watch: TransformX 2021: “Creating Personalized Listening Experiences with Spotify” Recent publications from Spotify Research: “Variational User Modeling with Slow and Fast Features” (Feb. 2022) “Algorithmic Balancing of Familiarity, Similarity, & Discovery in Music Recommendations” (Nov. 2021) “Leveraging Semantic Information to Facilitate the Discovery of Underserved Podcasts” (Nov. 2021) “Shifting Consumption towards Diverse Content on Music Streaming Platforms” (Mar. 2021) Read what else we’re nerding out about on the Spotify Engineering Blog: engineering.atspotify.com You should follow us on Twitter @SpotifyEng and on LinkedIn!
·open.spotify.com·
08: Humans in the Loop