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Open Humans empowers people with their personal data. From genomes to GPS: you can explore data analyses, do citizen science, and donate data to research.

A list of microgrant programs for your good ideas. Contribute to nayafia/microgrants development by creating an account on GitHub.

We present EKILA; a decentralized framework that enables creatives to receive recognition and reward for their contributions to generative AI (GenAI). EKILA proposes a robust visual attribution technique and combines this with an emerging content provenance standard (C2PA) to address the problem of synthetic image provenance – determining the generative model and training data responsible for an AI-generated image. Furthermore, EKILA extends the non-fungible token (NFT) ecosystem to introduce a tokenized representation for rights, enabling a triangular relationship between the asset’s Ownership, Rights, and Attribution (ORA). Leveraging the ORA relationship enables creators to express agency over training consent and, through our attribution model, to receive apportioned credit, including royalty payments for the use of their assets in GenAI.

Students in RISD's Digital + Media graduate program make research-driven, multimedia work informed by art, science and technology. Learn more at RISD.edu.

Symbolic language can help us grasp the nature and power of what is coming

Leverage hallucinations from Large Language Models (LLMs) for novelty-driven explorations. - GitHub - DivergentAI/dreamGPT: Leverage hallucinations from Large Language Models (LLMs) for novelty-dri...

Co-authored with Grace Carney A few months ago Fred kicked off a conversation about what the “native” applications of AI technology will be. What are the

Conversation around generative AI tends to focus on whether its development is open or closed. It's more responsible to envision releases along a gradient.

🔬 Research Summary by Shreyasha Paudel, a Ph.D. student at the University of Toronto with an interdisciplinary research focus that combines Human-Computer Interaction with critical theories from…

About Us Encord is a fast-growing startup building an active learning platform for computer vision AI applications. Our mission is to enable companies to unlock the power of AI. We have raised $20M from top investors including CRV, Y Combinator Continuity, the Harvard Management Company, top industry executives, and other leading Bay Area investors. Started by ex-computer scientists, physicists, and quants, we felt first hand how the lack of tools to prepare quality training data was impeding the progress of building practical AI. AI feels to us like what the early days of computing or the internet must have felt like, where the potential of the technology is clear, but the tools and processes surrounding it are terrible. We have devised a unique methodology for automating the tasks related to preparing quality training data, in effect turning the training data problem into a data science problem. Role and Responsibilities We’re looking for a product designer to accelerate our eff

Stable Diffusion revolutionised image creation from descriptive text. GPT-2, GPT-3(.5) and GPT-4 demonstrated astonishing performance across a variety of language tasks. ChatGPT introduced such language models to the general public. It is now clear that large language models (LLMs) are here to stay, and will bring about drastic change in the whole ecosystem of online text and images. In this paper we consider what the future might hold. What will happen to GPT-{n} once LLMs contribute much of the language found online? We find that use of model-generated content in training causes irreversible defects in the resulting models, where tails of the original content distribution disappear. We refer to this effect as Model Collapse and show that it can occur in Variational Autoencoders, Gaussian Mixture Models and LLMs. We build theoretical intuition behind the phenomenon and portray its ubiquity amongst all learned generative models. We demonstrate that it has to be taken seriously if we are to sustain the benefits of training from large-scale data scraped from the web. Indeed, the value of data collected about genuine human interactions with systems will be increasingly valuable in the presence of content generated by LLMs in data crawled from the Internet.

Hi, I'm Pi. I'm your personal AI, designed to be supportive, smart, and there for you anytime. Ask me for advice, for answers, or let's talk about whatever's on your mind.

How many humans does it take to make tech seem human? Millions.

This episode Nadia and I chat about how design can co-create AI, what the role of designers are in AI services? post-deployment design, narratives in AI development and AI ideologues, anthropocentric AI, augmented creativity, new AI perspectives, situated intelligences and more...

Please note: unlike previous courses, this entirely class will be done async. You will get access to a Slack channel and weekly recordings. It's a great option for anyone across the globe.Algorithmic Filmmaking is a course for filmmakers, creative coders, and anyone else interested in tools for non-traditional editing and filmmaking. Every week you’ll receive 2 hours of recorded tutorials and discussions to help you create films using machine learning, algorithms and other cutting-edge tools. You’ll also receive supplemental lectures, films to watch, and other materials.Wondering the kind of things you’ll learn? Check out this overview of my project Scream Scenes. We’ll cover these techniques and much more.Prerequisitesknowledge of coding principles is very helpful, but not requiredaccess to a Windows, Mac, or Linux machine that can run Zoomexperience or familiarity with command line is very helpufl, and comfort reading code (any code will be provided to you)Access to free version of Google Colab and Google Drive Example syllabus (subject to change)Week 1 How to create a database of video clipsWeek 2 Categorizing shot typesWeek 3 Algorithmic fancamsWeek 4 Matchcuts and other uses of OpenposeWeek 5 Algorithmic sequencing Week 6 Audioreactive and other guidance techniquesWeek 7 Free Space/TBDTBD Student Demo DaySchedule and StructureThis course will be run asynchronously. Every week you’ll receive 2 hours of recorded tutorials and discussions. In addition to the seven 2-hour recordings, there will be two open 1hr sessions with Derrick every week to answer questions and get help on projects. We will be using Slack for asynchronous messaging and discussion. Additional materials outside of the lectures and demos will be provided as video links, webpages or PDFs.About the instructorsDerrick Schultz is a designer, filmmaker and artist working with machine learning. His work has been featured at machine learning conference CVPR and NeurIPS, and has been commissioned by the New York Times, HP, and Acne. He has taught numerous machine learning courses, and has teaching experience at ITP, Parsons, and SVA. You can see more of his work on his website.

With just a few dozen example images, you can train a working, state-of-the-art computer vision model in less than 24 hours.

An AI experiment to conduct an orchestra inside your web browser.

This year Google Creative Lab is inviting multidisciplinary creatives to apply for a paid gig (£300 per day) and collaboration up to 12 months at Google Creative Lab, London. As a Fiver you will work on projects big, small and first of their kind within Google. You will be paired with a mentor and work closely with other creatives. A Fiver is an essential part of Google Creative Lab and it’s the way a lot of our current leaders started.

“The technologies built by a few techies from Silicon Valley run everything and none of us know how they work.” - David Middleback, Re-inventing Education for the Digital Age A few months ago I was struck with the genius idea of embarking on a PhD program. My project aimed at figuring out how we can make some of those Silicon Valley AI technologies ‘better’ for everyone affected by them. It sounded simple enough, right? Well, it turns out that this simple description I was using to explain to fr

Read and download Artificial Intelligence and Post-Capitalism by Thanasis Apostolakoudis on OA.mg

Tactical Tech is looking for a research assistant to enhance the information in our Influence Industry Explorer, an open-access database that compiles information about companies working with political parties and candidates on data-driven and digital campaigns.

Tactical Tech is looking for a professional Instructional Design consultant to develop workshop curricula for the Influence Industry Project to accompany each of the learning modules into training materials in the existing format.

NEMO kennislink zoekt een Freelance wetenschapsjournalist technologie (12 uur per week).

One Project is looking for a Product Designer to collaborate on prototypes and products that support alternative economic and governance systems. We are seeking an experienced Product Designer fluent in participatory practices, grounded in principles of equity and justice, and curious about how a world beyond capitalism would look, feel, and function.

A new, timely exhibition at the MAK Museum of Applied Arts in Vienna is taking a closer look at the technological developments pushing architecture and design into new territory in the past decade using a variety of different relevant media. From May 10–September 10, ...

The work reflects on the creative potential, challenges and limitations of human-AI relationships. Available to watch on Somerset House's online space Channel.