| Web | https://dracoblue.net |
| Github | https://github.com/DracoBlue |
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I pushed the first version of clawlet, which is like a 1200 linea of code version trying to cover my use case and giving me understanding how openclaw (amazing piece of AI work!) works.
Die Maus erklärt wie KI / Large Language Models funktionieren. Faszinierend detailliert, schaut mal rein!
Vielen Dank, an @berlinfediday, dass wir auf dem #fediday aus der täglichen Praxis unserer BSI-Präsenz im Fediverse berichten durften! Danke auch an die Teilnehmenden für die guten Fragen und die engagierte Diskussion.
👉 Ein paar unserer Erkenntnisse bis hierher:
(1/3)
"Ey, wie geil wäre das, wenn sich eine KI um alles kümmert, was total nervt." 😂
https://jingles.erstmal.com/jingle/kuenstliche-intelligenz.html
🚀 TopicWatchdog – Week 3: Stable Topics with BERTopic
KMeans worked, but cluster IDs kept jumping across retrains. This week I added a Python BERTopic stage with a BigQuery registry → stable topic IDs!
🟢 UMAP + HDBSCAN
🟢 Stable IDs via registry
🟢 Auto-labels with Gemini
🟢 Looker Studio dashboards
📊 3,802 topics → 2,472 mapped, top clusters: migration, economy, climate, politics.
👉 Blog: https://dracoblue.net/dev/topicwatchdog-stable-topics-with-bertopic/
#TopicWatchdog #BERTopic #BigQuery
#Clustering
#MachineLearning
#FediScience
In Week 1 (extraction) and Week 2 (embeddings + KMeans in BigQuery ML) we laid the groundwork. This week I built a Python BERTopic stage whose IDs stay stable across runs by mapping BERTopic’s internal clusters to stable topic IDs in BigQuery. I use Go...
TopicWatchdog (Week 2)
Move beyond string matching: cluster political topics from German shorts with embeddings + KMeans in BigQuery ML.
642 videos → 620 topics → 20 clusters (AfD positions, debates, labor market, climate/economy, corruption …).
Blogpost with SQL & charts:
🔗 https://dracoblue.net/dev/topicwatchdog-embeddings-and-kmeans-clustering-of-topics-claims/
#TopicWatchdog #BigQuery #Embeddings #Clustering #MachineLearning #FediScience
This post documents Week 2 of the TopicWatchdog project.Last week we successfully extracted topics and claims from German political short videos and persisted them in BigQuery.However, topics often appeared under slightly different names — making aggre...
Kickoff: TopicWatchdog (Week 1)
I’m building a reproducible pipeline that collects German political shorts, transcribes them, extracts topics & claims with timestamps, and stores everything in BigQuery for transparent analysis.
First finding: topic names are unstable → next up: embeddings + clustering in BigQuery ML.
Full write-up:
#TopicWatchdog #BigQuery #MachineLearning #LLM #OpenData #FediScience
BSI