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Predictive test selection for SUSE Manageran idea by jordimassaguerpla I once had a bad dream. |
Face recognition on nextcloud with TPUa project by jordimassaguerpla Project Description |
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Learn about AI, ML, neural networks and see what's possible with SUSE Linuxa project by rsimai Everybody is talking about (and with) ChatGPT. I tried it and was impressed by how well the language model behaves and finally how real and humanly it appears, despite the obvious nonsense that it outputs. I was wondering how machine learning practically works and how to build a neural network. |
Package MONAI Machine Learning Models for Medical Applicationsan invention by jordimassaguerpla Project Description |
Implement Generative AI for SUSE Asset management (using Amazon Bedrock)a project by mpiala |
AI frontend to Bugzillaan idea by paolodepa Project Description |
Play with stable diffusion AI model to generate custom avatarsan invention by STorresi Project Description |
TinyTutor - an AI chat-bot powered children's tutora project by dmulder |
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COOTWbota project by ngetahun |
Create language model based on Uyuni documentationan idea by nadvornik |
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Save pytorch models in OCI registriesa project by jguilhermevanz Description |
AI for product managementan invention by a_jaeger Description |
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Make more sense of openQA test results using AIan invention by livdywan DescriptionAI has the potential to help with something many of us spend a lot of time doing which is making sense of openQA logs when a job fails. |
Research how LLMs could help to Linux developers and/or usersa project by anicka DescriptionLarge language models like ChatGPT have demonstrated remarkable capabilities across a variety of applications. However, their potential for enhancing the Linux development and user ecosystem remains largely unexplored. This project seeks to bridge that gap by researching practical applications of LLMs to improve workflows in areas such as backporting, packaging, log analysis, system migration, and more. By identifying patterns that LLMs can leverage, we aim to uncover new efficiencies and automation strategies that can benefit developers, maintainers, and end users alike. |
Learn how to integrate Elixir and Phoenix Liveview with LLMsa project by ninopaparo Description |
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Run local LLMs with Ollama and explore possible integrations with Uyunia project by PSuarezHernandez DescriptionUsing Ollama you can easily run different LLM models in your local computer. This project is about exploring Ollama, testing different LLMs and try to fine tune them. Also, explore potential ways of integration with Uyuni. |
Use local/private LLM for semantic knowledge searchan invention by digitaltomm Description |
Use AI tools to convert legacy perl scripts to bashan idea by nadvornik Description |
Gen-AI chatbots and test-automation of generated responsesa project by mdati Description |
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SUSE Observability MCP servera project by drutigliano Description |
Update M2Cryptoa project by mcepl There are couple of projects I work on, which need my attention and putting them to shape: |
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Uyuni Health-check Grafana AI Troubleshootera project by ygutierrez Description |
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MCP Server for SCCan invention by digitaltomm Description |
AI-Powered Unit Test Automation for Agamaa project by joseivanlopez The Agama project is a multi-language Linux installer that leverages the distinct strengths of several key technologies: |
Multi-agent AI assistant for Linux troubleshootingan invention by doreilly DescriptionExplore multi-agent architecture as a way to avoid MCP context rot. |
SUSE Edge Image Builder MCPan invention by eminguez Description |
"what is it" file and directory analysis via MCP and local LLM, for console and KDEa project by rsimai DescriptionUsers sometimes wonder what files or directories they find on their local PC are good for. If they can't determine from the filename or metadata, there should an easy way to quickly analyze the content and at least guess the meaning. An LLM could help with that, through the use of a filesystem MCP and to-text-converters for typical file types. Ideally this is integrated into the desktop environment but works as well from a console. All data is processed locally or "on premise", no artifacts remain or leave the system. |
Background Coding Agenta project by mmanno Description |
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Extended private brain - RAG my own scripts and data into offline LLM AIan invention by tjyrinki_suse Description |
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Try AI training with ROCm and LoRAa project by bmwiedemann Description |
MCP Trace Suitea project by r1chard-lyu DescriptionThis project plans to create an MCP Trace Suite, a system that consolidates commonly used Linux debugging tools such as bpftrace, perf, and ftrace. |
Try out Neovim Plugins supporting AI Providersa project by enavarro_suse Description |
Explore LLM evaluation metricsa project by thbertoldi Description |
Kubernetes-Based ML Lifecycle Automationa project by lmiranda DescriptionThis project aims to build a complete end-to-end Machine Learning pipeline running entirely on Kubernetes, using Go, and containerized ML components. |
Enable more features in mcp-server-uyunia project by j_renner Description |
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Liz - Prompt autocompletea project by ftorchia DescriptionLiz is the Rancher AI assistant for cluster operations. |
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Backporting patches using LLMa project by jankara Description |



