All of my long-form thoughts on philosophy, music, programming, and more, collected in chronological order.
World models are supposed to give AI agents common sense and understanding. This seminar paper measures Yann LeCun's H-JEPA against Stachowiak's theory of models and Baumberger's account of understanding, and asks whether predicting the consequences of actions is already enough to understand the world.
What does it mean to think? This seminar paper explores the philosophy of mind, the problem of intentionality, and what it takes for a mental state to be "about" something — drawing on cognitive psychology, symbolic AI, and Frances Egan's deflationary account of mental representation.
In the world of knowledge representation and retrieval, querying structured data remains a challenge for many users, especially those without extensive technical backgrounds. My bachelor's thesis, Query by Graph, aims to bridge this gap by introducing a Visual Query Builder for SPARQL queries, making it easier to extract information from Wikibase systems like Wikidata and FactGrid.
Recent advances in the implementation of implants that enable mind reading are causing a stir and bringing long-awaited visions of transhumanists into realistic proximity. The fusion of human and machine seems inevitable. But who will control whom?
This talk on artificial intelligence is meant to introduce the listener to artificial intelligence (machine learning and symbolic AI) without making use of mathematics.
Large Language Models (LLM) werden bereits heute von 100 Millionen Menschen täglich genutzt. Es stellt sich nun die Frage: wie fähig ist diese Technologie, welche bösen Absichten könnten Nutzer leichter mithilfevon ChatGPT umsetzen und kann man LLMs regulieren?
I have been on a long journey to find a good mechanical keyboard. I am not yet fully where I want to be, but I have made interesting findings.
Observing the current hypes around Large Language Models (LLMs), especially OpenAI's GPT-3 and -4, I want examine what the buzz-words refer to and especially what sets humans apart from LLMs.
This is a project for a module on machine learning. Using different word mapping methods, I tried to predict the sentiment of tweets.
Collection of all recordings I have.
My advice to newcomers.