IFD:SMPH SoSe22: Difference between revisions

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Assignment: Please review the following texts: [https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf "Improving Language Understanding
Assignment: Please review the following texts: [https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf "Improving Language Understanding
by Generative Pre-Training"] by Alec Radford et al., [https://www.theguardian.com/commentisfree/2020/sep/08/robot-wrote-this-article-gpt-3 "A robot wrote this entire article. Are you scared yet, human?"] from the Guardian, and [https://www.wired.com/story/ai-write-disinformation-dupe-human-readers/ AI Can Write Disinformation Now—and Dupe Human Readers] by Will Knight.<br />
by Generative Pre-Training"] by Alec Radford et al., [https://www.theguardian.com/commentisfree/2020/sep/08/robot-wrote-this-article-gpt-3 "A robot wrote this entire article. Are you scared yet, human?"] from the Guardian, and [https://www.wired.com/story/ai-write-disinformation-dupe-human-readers/ "AI Can Write Disinformation Now—and Dupe Human Readers"] by Will Knight.<br />
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Revision as of 12:19, 11 May 2022

Projektmodul / Project Module
Synthetic Media for Parallel Hyperrealities
Instructor: Vertr.-Prof. Jason Reizner
Credits: 18 ECTS, 16 SWS
Capacity: max. 12 students
Language: English
Date: Plenum: Tuesdays, 13:30-17:00; Consultations by appointment
Location: Online/Marienstraße 7b
First Meeting: 12 April 2022, 13:30 on BBB
(Link to online meeting will be sent to accepted participants by email.)
BISON Course ID: [TBA]

Description


The simulacrum is never that which conceals the truth
– it is the truth which conceals that there is none.
The simulacrum is true.

– Jean Baudrillard, Simulacres et Simulation, 1981


In a world where machines have become more than capable of autonomously generating (seemingly) credible newspaper articles, danceable techno tracks, adorable cat memes and plausible Nicolas Cage videos, the ability to algorithmically produce and transform digital media forms – so-called deepfakes – has arrived on the desktops and devices of millions. This project module focuses not on the demise of the distinction between real and rendered, but on a future where this distinction becomes increasingly blurred and irrelevant.

Through a series of lectures, workshops and targeted discussions, participants will address topics including human and artificial intelligence, generative and autonomous systems, supervised and unsupervised machine learning, neural networks, GANs and hyperreality, and will engage with state-of-the-art tools and methodologies for the synthetic production of text, images and audiovisual media.

Admission requirements

Enrollment in MKG/MAD MFA or MediaArchitecture MSc programs

Application and registration procedure

Application with CV and Statement of Motivation to jason.reizner [ät] uni-weimar.de

Evaluation

Successful completion of the course is dependent on regular attendance, active participation, completion of assignments and delivery of a relevant semester prototype and documentation. Please refer to the Evaluation Rubric for more details.

Eligible participants

MFA Medienkunst/-gestaltung, MFA Media Art and Design, MSc MediaArchitecture candidates

Platforms and Tools

This Wiki
BigBlueButton (only as necessary)
Cisco WebEx
Are.na
MURAL
Miro
Google Jamboard

Syllabus (subject to change)

12 April 2022 / Week 1
Introduction
Course Organization
Administrative Housekeeping

Assignment: If you have not done so already, for next week please review the following chapter:
"Simulacra and Simulations" by Jean Baudrillard
and prepare for next week's experiment 'New Identity, Who Dis?' by adding your GAN-generated avatar and persona profile to the Miro board



19 April 2022 / Week 2
Fake Synthetic Media
Speculative Narratives

Assignment: Please watch F for Fake (Orson Welles, 1975) and complete part II of the avatar experiment as discussed in class. Be ready to talk for two or three minutes about your preliminary project ideas during next week's roundtable.


26 April 2022 / Week 3
Project Roundtable I

Assignment: For next week, please review the following texts: "Machine learning, explained" by Sara Brown and "What is Machine Learning (ML)?" from the Berkeley School of Information, and view "Deep Learning Basics: Introduction and Overview" from Lex Fridman (accompanying slides available here). Finally, in reflection of today's roundtable discussion, you should add your visual connection element(s) to and from your avatar on the Miro board.



3 May 2022 / Week 4
From Machine Learning to Machine Intelligence
Algorithmic, Computational & Generative Forms

Assignment: Please review the following texts: "Why the Past 10 Years of American Life Have Been Uniquely Stupid" by Jonathan Haidt and "The Cause of America's Post-Truth Predicament" by Andy Norman. Also, in preparation for next week's guest lecture have a look at the following video: "Watch People Realize they're ACTUALLY talking to a DEEPFAKE" from Corridor Crew.



10 May 2022 / Week 5
Guest Lecture with Prof. Mario Verdicchio, University of Bergamo (IT)
We have always lived in a post-truth era.

Deepfakes are videos created by means of machine learning techniques that allow for audiovisuals that depict people in a very realistic, almost impossible to detect yet fake way, while they say and do things that they did not say or do in reality. This has a plethora of potentially dangerous epistemological and ethical consequences. Since deepfakes are a novelty, these issues may appear to stem from the latest technologies, but this seeming attack against the truth has always been there, ever since humans started recording facts. This lecture analyses the technological aspects of deepfakes to show that they are simply the most recent embodiment of a gap between facts and descriptions that is as old as humanity.

Assignment: Please review the following texts: [https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf "Improving Language Understanding by Generative Pre-Training"] by Alec Radford et al., "A robot wrote this entire article. Are you scared yet, human?" from the Guardian, and "AI Can Write Disinformation Now—and Dupe Human Readers" by Will Knight.




17 May 2022 / Week 6
GPT Lab (Live In Physicality!)

Assignment: TBA



24 May 2022 / Week 7
Midterm Presentations

Assignment: TBA



31 May 2022 / Week 8
GAN Lab

Assignment: TBA



7 June 2022 / Week 9
Deepfake Lab I

Assignment: TBA



14 June 2022 / Week 10
Deepfake Lab II

Assignment: TBA



21 June 2022 / Week 11
Guest Lecture with Pablo Silva Saray (architect, Halle/Saale)

Assignment: TBA



28 June 2022 / Week 12
Debug Lab

Assignment: TBA



5 July 2022 / Week 13
No Class: xCoAx2022

Assignment: TBA



12 July 2022 / Week 14
Final Presentations