Solving the Fork Dilemma: How We Built a Maintainable Matrix Messenger (matrix-conf-2025)

Tammy is a multiplatform Matrix Messenger designed to be redefined by you. Want a different room list layout? Need a messaging interface tailored to a specific use case? Tammy’s extensible architecture makes that not only possible - but easy. In this talk, we’ll showcase how Tammy empowers developers to create radically customized Matrix experiences through its extension system. We’ll walk you through how we’re using Tammy to build Timmy, a TI-Messenger variant tailored for a very specific user group, with a completely different look and feel - all without forking or rewriting the core client. Expect...

39C3 — Community-Bühnen: Alles bleibt anders

Sicher erinnert ihr euch noch an die beiden Community-Bühnen auf dem 38C3 und das tolle Programm, das dort, von der Community eingereicht und von den Habitaten kuratiert, auf die Beine gestellt wurde. In diesem Jahr wird es die Community-Bühnen nicht mehr geben. Stattdessen haben wir uns dazu entschlossen, das Hauptprogramm um einen neuen Community-Track und eine vierte Bühne zu erweitern und zusätzlich im Rahmen der Self-Organized Sessions eine eigene Bühne für Talks zur Verfügung zu stellen.

Warum diese Änderung?

Kurz gesagt – ihr wart einfach zu gut!

Länger gesagt: Die Qualität der Talks auf den Community-Bühnen stand denen im Hauptprogramm quasi in nichts...

What Networks tell us about Trades, Power, and the World? (sps25)

Networks are all around us, shaping phenomena like epidemics, communication, and transportation. In this talk, we will explore how real-world problems can be analyzed and solved using graph-based methods and simple algorithms. Drawing from examples such as trade networks, corporate structures, and historical data, I will demonstrate how network analysis reveals insights that would otherwise remain hidden. Using NetworKit (and NetworkX), we will analyze real-world datasets to answer questions like: What does the core-periphery model reveal about trade networks? Could we have predicted that Moscow will become Russia's capital? How do corporate hierarchies differ...

AI Coding Agents and how to code them (sps25)

I Agents are the next big thing everyone has been talking about. They are expected to revolutionize various industries by automating routine tasks, mission critical business workflows, enhancing productivity, and enabling humans to focus on creative and strategic work. Of course, you can apply them to your everyday coding tasks as well. In this talk we’ll go over what those agents can bring to the table of coding world, and why they can deliver the promise of coding smarter that the current generation of coding assistants can’t. We will then dive right into a...

Docling: Get your documents ready for generative AI (sps25)

Docling is an open-source Python package that simplifies document processing by parsing diverse formats — including advanced PDF understanding — and integrating seamlessly with the generative AI ecosystem. It supports a wide range of input types such as PDFs, DOCX, XLSX, HTML, and images, offering rich parsing capabilities including reading order, table structure, code, and formulas. Docling provides a unified and expressive DoclingDocument format, enabling easy export to Markdown, HTML, and lossless JSON. It offers plug-and-play integrations with popular frameworks like LangChain, LlamaIndex, Crew AI, and Haystack, along with strong local execution support for...

Agentic Cyber Defense with External Threat Intelligence (sps25)

This talk will detail how to integrate external threat intelligence data into an autonomous agentic AI system for proactive cybersecurity. Using real world datasets—including open-source threat feeds, security logs, or OSINT—you will learn how to build a data ingestion pipeline, train models with Python, and deploy agents that autonomously detect and mitigate cyber threats. This case study will provide practical insights into data preprocessing, feature engineering, and the challenges of adversarial conditions. about this event: https://talks.python-summit.ch/sps25/talk/QNWFTD/
Video:import-56457-eng-Agentic_Cyber_Defense_with_External_Threat_Intelligence_hd.mp4

Causal ML for Smarter Advertising Campaigns with Python (sps25)

Traditionally, marketing campaign analysis relies on simple metrics like the number of purchases made after a contact, or conversions following a promotion. While these numbers tell us what happened, they don’t reveal why it happened or if the campaign truly made a difference. Such analysis can’t distinguish between customers who would have acted anyway and those who were genuinely influenced by the campaign. The key question is: did the campaign actually cause the desired effect? In this practical and beginner-friendly session, we’ll explore how Causal Machine Learning provides the missing piece in campaign evaluation...

Machine learning for Swiss democracy (sps25)

Demokratis.ch is a non-profit project working to modernise the consultation procedure—a key democratic process that allows Swiss citizens to provide feedback on proposed laws and amendments. Today, the process is slow and cumbersome for everyone involved: it requires studying lengthy PDFs, writing formal letters, and even synthesising legal arguments by copy-pasting into Excel. There’s a huge opportunity to streamline this process and make this democratic tool more accessible and inclusive. In this talk, I’ll share how we’re tackling this challenge with machine learning: building data processing pipelines, extracting features from endless PDFs, embedding and...

Gompertz Linear Units (GoLU) (sps25)

Activation functions are fundamental elements of deep learning architectures as they significantly influence training dynamics. ReLU, while widely used, is prone to the dying neuron problem, which has been mitigated by variants such as LeakyReLU, PReLU, and ELU that better handle negative neuron outputs. Recently, self-gated activations like GELU and Swish have emerged as state-of-the-art alternatives, leveraging their smoothness to ensure stable gradient flow and prevent neuron inactivity. In this work, we introduce the Gompertz Linear Unit (GoLU), a novel self-gated activation function defined as `GoLU(x) = x Gompertz(x)`, where `Gompertz(x) = exp(−exp(−x))`. The...

Anonymization of sensitive information in financial documents (sps25)

Data is the fossil fuel of the machine learning world, essential for developing high quality models but in limited supply. Yet institutions handling sensitive documents — such as financial, medical, or legal records often cannot fully leverage their own data due to stringent privacy, compliance, and security requirements, making training high quality models difficult. A promising solution is to replace the personally identifiable information (PII) with realistic synthetic stand-ins, whilst leaving the rest of the document in tact. In this talk, we will discuss the use of open source tools and models that can...