Competences and interests
Things that I like.
- Implementing web applications using various technologies.
- Perfecting and iterating user experience in collaboration.
- Helping to determine requirements and user stories and how to implement them.
- Making users, stakeholders and designers content with the UX of their web application.
- Passionate about accuracy.
- Structuring complex data to achieve a simple and understandable result.
- Basic knowledge about algorithms, complexity theory and general computer science (studied at University of Bonn).
Know when to look things up and which data structures to use to avoid unneeded complexity. - Love long debugging sessions with a happy end.
- Respect for page performance, maintainability and SEO from the start: good UX and DX is hard to add retroactively.
- Through working on web projects, I also can estimate when it is worth optimizing things and when it is not.
That being said, I am allergic to a certain threshold of unneeded complexity. - Staying up to date with the latest developments in web technology and general IT.
- Taking care of frictionless development processes and web applications that are maintanable in the long-term.
- Learning from better developers to constantly improve my skills.
- …
- I music (especially electronic and classical), nature, and people
- Languages:🇩🇪and🇺🇸 🇬🇧
AI
Like many people, I am fascinated by the progress made in AI and especially the recent leaps in Deep Learning and Large Language Modeles. I enjoy following the advancements and tinkering with publicly available technologies.
That being said, I am not an AI or machine learning expert.
I am mostly a curious and fascinated end user, especially of generative modeles, ever since GPT-2 emerged in simple-to-use forms for the general public in 2019. I still sometimes enjoy tinkering with pre-trained models that everyone can use and especially like the possibility to run models locally (StableDiffusion, locally installable text LLMs...)
As a "bird's-eye" introduction for people like me, I enjoyed the book "You look like a thing and I love you" by Janelle Shane.
More...
I use some spare time now and then to try and try various locally installable models, I enjoy their current emergence and improvement, from StableDiffusion to various text LLMs, also the self-contained and easy-to-use frontends for them.
An especially exciting new development are the quantized and otherwise down-scaled text LLMs that can run on laptop hardware.
Another thing that blew my mind conceptually was riffusion, this really emphasizes the universality of "language" in some sense.
I also use OpenAI's products, although only rarely and mostly for fun so far.
What LLMs and other ML developments will bring in the future – apart from humour, disruption, doomsday predictions – I think few people can already tell, if anyone at all.
There's quite a bit of crazy emergent behavior and capabilities that I didn't consider possible when first trying GPT-2 and GPT-3.
And of course the question of when something can be considered emergent behavior at all.
I can recommend AI research papers about newer LLL developments as they are often entertaining and accessible, and my interest in the topic tends to rise and fall periodically.
TL;DR:
AI has been mostly a creative tool and toy for me, and funny dialogues with AI have been helping me to find humor in dark times. I also like to test more useful capabilities and test unconventional prompts and contexts.
I learned a little bit about AI at university, even about neural networks, but unfortunately did not finish this course at the time.
On a darker note, re-reading this great short story in light of the actual release paper for GPT-4 is quite a confusing experience after having spent too much time on the internet.
For eagle-eyed readers: I like AI too, I'm just not an AI expert.
By now, editing this page and writing about my limited personal experience can hardly keep up with the crazy-fast developments in generative AI.