Florian Hartmann

In 2025, I ended up reading 43 books.

Google DeepMind just released the new Gemma 3n family of models.

2024 is coming to an end, so it is again time for me to reflect on what I have read this year.

This post describes my work at Google: https://blog.research.google/2024/03/social-learning-collaborative-learning.html

A fun thing I recently learned about Large Language Models (LLMs) is that they understand base64, a simple encoding of text.

As the year is coming to an end, it is time for me to reflect back on what I read this year.

This post describes my work at Google: https://ai.googleblog.com/2023/03/distributed-differential-privacy-for.html

A habit that I have had for a few years is that I try to focus each year on some particular goal.

Much has been written about how federated learning (FL) can enable training much better models and help build more intelligent systems.

For the past four years, I have been doing yearly reading summaries now.