Christian Schmidts & Prof. Daniel Hromada
daniel@udk-berlin.de / c.schmidts@udk-berlin.de

presented at

UdK Berlin Campus Kollisionen 2025, Aula Medienhaus, 6.1. - 10.1 10:00 - 16:00

Outcome

A symposium during which "artificial avatars" (AAs) of Your making will discuss with us humans the question "What is art ?"

Synopsis

DAY 1 :: 6.1. :: Introduction of main concepts (avatarization, generative AI) introduction of technologies (language models, Loras, retrieval-augmented generation) & tools (Flowise, text-webui) we will use.

DAY 2 :: 7.1. :: Introduction of additional tools (Unreal engine, voice cloning). Group formation. Bringing an exemplar AA into existence.

DAY 3 :: 8.1. :: Bringing other AAs into existence

DAY 4 :: 9.1. :: Making AAs communicate among themselves & with us, room preparation

DAY 5 :: 10.1. :: 1st UDK.AI Symposium on Artificial Avatars

Day 0 :: 6.1.2025 :: AE550106

Today we will tell You what this Kollisionen seminar should be about, what technologies we will use and where do we will, ideally, get...

Introduction

Introduction of main concepts (avatarization, generative AI) introduction of technologies (language models, Loras, retrieval-augmented generation) & tools (Flowise, text-webui) we will use.

Definitions

Generative KI

Generative künstliche Intelligenz (KI) widmet sich der Erstellung neuer, oft unvorhergesehener Daten oder Inhalte, die das Ergebnis des Lernens aus bestehenden Daten sind. Diese Modelle 'verstehen' irgendwie die Struktur und Verteilung der Daten, auf denen sie trainiert wurden, und versuchen, neue Muster zu erstellen, die mit diesen erlernten Mustern übereinstimmen. Generative Modelle können für verschiedene Zwecke verwendet werden, wie zum Beispiel die Erstellung von Bildern, Texten, Tönen oder Videos und werden oft in Bereichen wie der künstlichen Inhaltsproduktion oder Sprachsynthese eingesetzt.

Neuronale Netze

Neuronale Netze im Kontext der KI sind keine echten Nervenzellen, sondern softwarebasierte Modelle, deren Architektur von der Art und Weise inspiriert ist, wie das menschliche Gehirn Informationen verarbeitet. Diese Modelle bestehen aus "Schichten" von Datenstrukturen, die "Neuronen" genannt werden. Die Neuronen sind miteinander verbunden und ihre Verbindungen haben ein bestimmtes "Gewicht". Im Lernprozess passt das System diese Gewichte - auch "Parameter" genannt - allmählich an, um den Fehler zwischen seiner Vorhersage und dem, was vorhergesagt werden soll, zu verringern.

model

A trained neural network is stored in a file. This file is called "a model". When You want to use it - either for inferencing or training or both - You need to load the model from the disk into memory.

Based on the amount of "parameters" (e.g. numbers which represent the synaptic weight) the model contains, the process of loading into memory shall be or shall not be succesful ;)

lora

Lora is like a small "adapter" model which You can train as an addition to Your main "big" model. Training of a Lora is much faster than fine-tuning of the big model itself.

With a properly trained Lora, You will give Your avatar a unique personality.

training & inferencing

In machine learning and AI, we speak about

"training" when the AI is learning from the data we provide it

"inferencing" when the AI is using its current "knowledge" to solve new problems (e.g. problems which maybe weren't in the training data at all)

Avatar (etymology)

"descent of a Hindu deity to earth in an incarnate or tangible form," from Sanskrit avatarana "descent" (of a deity to the earth in incarnate form), from ava- "off, down" (from Proto-Indo-European root *au- (2) "off, away") + base of tarati "(he) crosses over" (from PIE root *tere- (2) "cross over, pass through, overcome").

The meaning "concrete embodiment of something abstract" is from 1815. In computer use, it seems to trace to the novel "Snowcrash" (1992) by Neal Stephenson.

(Idea) Avatarization

Within the "idealist" philosophical tradition, it is not necessarily the physical person but rather a "pure idea" (e.g. protection, justice, wisdom, friendship etc.) which is to be "avatarized".

'I'-Avatarization

"I"-Avatarization is the process whereby a living human H consciously creates, develops, fine tunes and optimizes (his|her) own generative AI avatar datasets & models.

That is, using datasets (mails, chat transcripts etc.) to create a generative AI copy of one's self (an "I-Avatar") which could provide information in situation when H (her|him)self is not alive anymore.

Cybrid

dall-e 3: "provide a picture of cybrid of john keats speaking with Ummon, the oldest AI in the technocore. ummon does not have a form of human, it is a radiant monolith"

A cybrid is an entity resulting from the fusion of an AI consciousness with a human body. (Dan Simmons, Cantos Hyperion)

What You need to create the avatar

Raison d'etre / Idea

Name

Description

Text dataset

Voice recording

Face / Appearance

Technologies

Language Models:::Ollama:::Flowise:::Text-to-speech:::Unreal:::Metahuman:::Audio2Face

Audio2Face

Metahuman

Unreal

Text-to-speech

amsel.udk.ai/tts

Flowise

flow.udk.ai

Ollama

Language Models

amsel.udk.ai/llm

0th Avatar

Participants

at%20least%20one%20non-human%2C%20non-artificial%20being%20will%20also%20attend%20the%20Symposium

at least one non-human, non-artificial being will also attend the Symposium

all open-minded individuals (that is: YOU) who wish to learn more about open-source generative AI

Christian Schmidts & Daniel D. Hromada

cybrid of romantic poet John Keats (Avatar issued out of 0th symposium)

AAs of Your own making

all species welcome !