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reflections with machines

implications for future humans with RunwayML

How do we live at the intersection of the critical and the creative through artificial computing?

• 23. September - 28. October 2021
• Online!
• Six-weeks, Thursdays, 8-10PM ET(Note timezone!)
• Small class of participants


Pricing (For tickets click here)
Artist / Student (Full Time)
€175*

Freelancer
€195*

Professional
€215*

Generous Supporter Ticket
€255*

Solidarity ticket
Donation (Limited)*

*plus fees (VAT EU ONLY)


course
description

“Reflections with Machines” offers a low-code/no-code opportunity to create artistic projects using the machine learning (ML) software: RunwayML, Artbreeder, and Teachable Machine. We will highlight the evolution of neural computation and AI’s impact in multiple industries, from computer vision applications to machine learning as an artistic tool. In addition, this course takes a hands-on approach to work with ml-models for object detection, image-to-image transformation, and deep generative models (GANs) for media synthesis.

The course focuses on the best practices for successful model training to create latent space videos and the technical understanding of how these generative models work to have the most artistic control over the results.

In compliment, the class emphasizes the ethical and historical context of machine learning for creativity to equip students with the necessary background to produce progressive critical works that build upon the current trends in the ai creative community. We will teach a beginner-friendly approach for people unfamiliar with code or machine learning for creative use through artistic metaphors and visual explanations. The course will guide students to produce image segmentation and image-generation videos by example and real-world artistic examples.

Finally, through active participation and activities, we will interact with open-sourced machine learning experiments that visually break down the latest ml-models in the industry to project into the future where these technologies are advancing.


course outline

Week 1 - Getting to Know each other

In this first week we will introduce each other and talk about our practices. We will consider how we could combine knowledge about our respective areas and speak from personal experience about how we process the new technologies that surround us every day. We will discuss the expectations of the class, the bibliography, and a glossary for those who do not come from a technical context.

Week 2 - History of Machine Learning

This week, we will explore the evolution of machine learning to deep learning, the types of algorithms in machine learning, and their industry application. By understanding the historical relationships in artificial intelligence, we will equip ourselves with a better intuition about the recent milestones and goals of the industry.

Week 3 - The implications of machine learning models through algorithms

In week three, we’ll focus through critical theoretical analysis on algorithms in our daily life and the socio-political environment we currently find ourselves in. The class will study different machine learning resources from research laboratories. We will transfer this theoretical exercise to practical hands-on training, learning about RunwayML software models for creative purposes.

Week 4 - Are there ethics in data collection?

In this fourth week, we consider our conception of data by analyzing how and where it can be extracted and towards what end. We will rethink how data extraction enables AI in surveillance technology, and through algorithms, how it monitors users on the internet.

Week 5 - Project Development

This week, we will learn to gather, curate, and process a dataset for image generation machine learning with StyleGAN2. Additionally, we'll share project ideas, progress, and receive constructive feedback. Projects can range from essay presentations, practical exercises in RunwayML, or conceptual endeavors with justification.

Week 6 - Presentation of Projects

In our final week we will continue with Ggroup exercises, discussion circles, and project presentations. Students will have the opportunity to present their projects and discuss them with the other participants’ feedback and constructive criticism. This class will end with consideration as to how to take these projects to the next stage, 2.0. We'll also see what other courses on machine learning can complement each project's journey.


who is this
class for?

Artists, sociologists, digital curators, creatives, and people interested in machine learning are creative tools. No programming experience is required.


about live classes

Classes are 'live' meaning that you can directly interact with the instructor as well as with the other participants from around the world. Classes will also be recorded for playback in case you are unable to attend for any reason. For specific questions, please email us and we'll get back to you as soon as we can.


about tickets

Tickets for this class are currently available via Eventbrite. If you would like to avoid Eventbrite fees, please email us for direct payment options.


about vat

For tax purposes, we need to include the 19% VAT on top of ticket price for people living within the EU. IF YOU LIVE IN THE EU AND HAVE A VAT NUMBER— IT IS VAT ZERO! WE ENCOURAGE EVERYONE TO HAVE AND PROVIDE THIS VAT TAX NUMBER. In order to utilise this feature at checkout, under Registration Type & Tax Receipt Information, select Business (which as a freelancer you technically are), then enter in your USt.ID. If you have any questions, feel free to email us.


about solidarity

We realise we're living in uncertain times. During this time, we are offering a limited number of pay-what-you-can solidarity tickets for this online class. These are reserved for women, POC, and LGBTQ+ who would otherwise be unable to attend. We are a small organisation with no outside funding and like many, we are also in survival mode and we ask you to consider this when making your donation. For more information, see the FAQ page here.

We kindly ask that all pay-what-you-can students register through Eventbrite. Due to reduced staffing, we’re unable to handle specific payment requests for these registrations.