The problem I typically find very hard to figure out in the whole SUSE company who is the go-to guy for a certain skill/knowledge/experience. I'd like to have some place where one, who does not know people around him, can just browse and search for people by some tag or label. Sometimes you have a problem in a specific area but you don't know who to ask to, or even if you do, you don't know there were many other people with the same knowledge/experience you could have ask before.
The idea Getting inspired by GitHub/GitLab issues and labels, we could have a website with all SUSE employees and a list of assigned tags as a property to look up for people with a certain knowledge/experience.
The solution - a web page with all the SUSE employees - a list of tags and the possibility to create new tags - a single page per each employee - a list of assigned tags for a single profile - a toolbox in the single profile page where to add an existing tag, or create a new one and assign it to the profile. Let the people freely assign tags to people profiles (if I know you know something, I will add the tag to you and you can be visible and reachable by that tech area) - a global search-by-tag box to add the possibility to look for people by the list of existing tags, or by a partial match with the inserted text.
Use case example Let's say we have { tags : [java, javascript, cloud, python, perl, suse manager, network, obs, jenkins, licenses, ruby, ....] } and I look for "java", then the search result should include all people with both the java and the javascript tag.
It frequently happen that we have the same problem in different products, but we solve it in different ways because we don't know the each other problem exists or it has been already solved. This feature could be very useful, especially for asking for help or ideas.
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Hack Week 17
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SUSE AI Meets the Game Board by moio
Use tabletopgames.ai’s open source TAG and PyTAG frameworks to apply Statistical Forward Planning and Deep Reinforcement Learning to two board games of our own design. On an all-green, all-open source, all-AWS stack!
Results: Infrastructure Achievements
We successfully built and automated a containerized stack to support our AI experiments. This included:
- a Fully-Automated, One-Command, GPU-accelerated Kubernetes setup: we created an OpenTofu based script, tofu-tag, to deploy SUSE's RKE2 Kubernetes running on CUDA-enabled nodes in AWS, powered by openSUSE with GPU drivers and gpu-operator
- Containerization of the TAG and PyTAG frameworks: TAG (Tabletop AI Games) and PyTAG were patched for seamless deployment in containerized environments. We automated the container image creation process with GitHub Actions. Our forks (PRs upstream upcoming):
./deploy.sh and voilà - Kubernetes running PyTAG (k9s, above) with GPU acceleration (nvtop, below)
Results: Game Design Insights
Our project focused on modeling and analyzing two card games of our own design within the TAG framework:
- Game Modeling: We implemented models for Dario's "Bamboo" and Silvio's "Totoro" and "R3" games, enabling AI agents to play thousands of games ...in minutes!
- AI-driven optimization: By analyzing statistical data on moves, strategies, and outcomes, we iteratively tweaked the game mechanics and rules to achieve better balance and player engagement.
- Advanced analytics: Leveraging AI agents with Monte Carlo Tree Search (MCTS) and random action selection, we compared performance metrics to identify optimal strategies and uncover opportunities for game refinement .
- more about Bamboo on Dario's site
- more about R3 on Silvio's site (italian, translation coming)
- more about Totoro on Silvio's site
A family picture of our card games in progress. From the top: Bamboo, Totoro, R3
Results: Learning, Collaboration, and Innovation
Beyond technical accomplishments, the project showcased innovative approaches to coding, learning, and teamwork:
- "Trio programming" with AI assistance: Our "trio programming" approach—two developers and GitHub Copilot—was a standout success, especially in handling slightly-repetitive but not-quite-exactly-copypaste tasks. Java as a language tends to be verbose and we found it to be fitting particularly well.
- AI tools for reporting and documentation: We extensively used AI chatbots to streamline writing and reporting. (Including writing this report! ...but this note was added manually during edit!)
- GPU compute expertise: Overcoming challenges with CUDA drivers and cloud infrastructure deepened our understanding of GPU-accelerated workloads in the open-source ecosystem.
- Game design as a learning platform: By blending AI techniques with creative game design, we learned not only about AI strategies but also about making games fun, engaging, and balanced.
Last but not least we had a lot of fun! ...and this was definitely not a chatbot generated line!
The Context: AI + Board Games
WebUI for your data by avicenzi
A single place to view every bit of data you have.
Problem
You have too much data and you are a data hoarder.
- Family photos and videos.
- Lots of eBooks, TV Shows, Movies, and else.
- Boxes full of papers (taxes, invoices, IDs, certificates, exams, and else).
- Bank account statements (multiple currencies, countries, and people).
Maybe you have some data on S3, some on your NAS, and some on your local PC.
- How do you get it all together?
- How do you link a bank transaction to a product invoice?
- How to tag any object type and create a collection out of it (mix videos, photos, PDFs, transactions)?
- How to store this? file/folder structure does not work, everything is linked together
Project Description
The idea is a place where you can throw all your data, photos, videos, documents, binaries, and else.
Create photo albums, document collections, add tags across multiple file-formats, link content, and else.
The UI should be easy to use, where the data is not important for now (could be all S3 or local drive).
Similar proposals
The closest I found so far is https://perkeep.org/, but this is not what I'm looking for.
Goal for this Hackweek
Create a web UI, in Svelte ideally, perhaps React.
It should be able to show photos and videos at least.
Resources
None so far, this is just an idea.
Use local/private LLM for semantic knowledge search by digitaltomm
Description
Use a local LLM, based on SUSE AI (ollama, openwebui) to power geeko search (public instance: https://geeko.port0.org/).
Goals
Build a SUSE internal instance of https://geeko.port0.org/ that can operate on internal resources, crawling confluence.suse.com, gitlab.suse.de, etc.
Resources
Repo: https://github.com/digitaltom/semantic-knowledge-search
Public instance: https://geeko.port0.org/
Results
Internal instance:
I have an internal test instance running which has indexed a couple of internal wiki pages from the SCC team. It's using the ollama (llama3.1:8b) backend of suse-ai.openplatform.suse.com to create embedding vectors for indexed resources and to create a chat response. The semantic search for documents is done with a vector search inside of sqlite, using sqlite-vec.