[{"data":1,"prerenderedAt":217},["ShallowReactive",2],{"/projects":3,"content-navigation-8C37fagqQL":32},[4,15,24],{"_path":5,"title":6,"description":7,"heading":8,"abstract":9,"year":10,"tags":11},"/projects/md-reheader","md-reheader: Restoring heading hierarchy in PDF-extracted markdown","Fine-tuned Qwen3-0.6B model that restores correct heading levels (H1-H6) in markdown documents produced by PDF extraction tools, achieving 80.6% per-heading accuracy. Published on PyPI and HuggingFace.","md-reheader","Fine-tuned a 0.6B parameter LLM to restore flattened heading hierarchies in markdown extracted from PDFs. 80.6% per-heading accuracy, runs on CPU, published as a PyPI package and HuggingFace model.","2026",[12,13,14],"On Github","PyPI","HuggingFace",{"_path":16,"title":17,"description":18,"heading":19,"abstract":20,"year":10,"tags":21},"/projects/slidev-mcp","Slidev MCP: AI-powered presentation generation with shareable links","Open-source MCP server that lets any AI assistant create, update, and host Slidev presentations with permanent shareable URLs, 24 themes, and zero-login sharing.","Slidev MCP","Built an MCP server that turns any AI assistant into a presentation tool. Ask it to create slides, pick a theme, and get a shareable link that works in any browser. 24 themes, iterative editing, 30-day hosted URLs.",[12,22,23],"MCP","Slidev",{"_path":25,"title":26,"description":27,"heading":28,"abstract":29,"year":10,"tags":30},"/projects/vue-mcp","Vue Docs MCP: Live Vue ecosystem documentation for AI assistants","Open-source MCP server giving AI assistants grounded, up-to-date access to Vue.js, Nuxt, Vite, Pinia, VueUse, and more — hybrid search over official docs with 4.8/5 answer quality.","Vue Docs MCP","Built an MCP server that gives AI assistants direct access to live Vue ecosystem documentation. Hybrid retrieval over 8 frameworks, structure-aware chunking, deterministic query pipeline, free hosted at mcp.vue-mcp.org.",[12,22,31],"RAG",[33,47,63,79,86,171],{"title":34,"_path":35,"children":36,"icon":46},"About","/about",[37,40,43],{"title":38,"_path":39},"Joel Barmettler - AI Engineer, Researcher, and Entrepreneur","/about/about-me",{"title":41,"_path":42},"What Drives Me - Research Focus and Philosophy on AI Systems","/about/what-drives-me",{"title":44,"_path":45},"Technical Skills and Expertise - AI, ML, Infrastructure, and Web Development","/about/skills","📁",{"title":48,"_path":49,"children":50,"icon":46},"Career","/career",[51,54,57,60],{"title":52,"_path":53},"Building the AI Business Area at bbv Software Services","/career/bbv",{"title":55,"_path":56},"PolygonSoftware: Building a tech company during university","/career/polygon-software",{"title":58,"_path":59},"Machine learning for semiconductor quality control at BESI","/career/besi",{"title":61,"_path":62},"Data engineering for cryptocurrency analytics at CoinPaper","/career/coinpaper",{"title":64,"_path":65,"children":66,"icon":46},"Research","/research",[67,70,73,76],{"title":68,"_path":69},"The Invisible Coalition Partner: How LLMs Vote When Democracy Gets Concrete","/research/invisible-coalition-partner",{"title":71,"_path":72},"ConceptFormer: Graph-native grounding of LLMs via latent concept injection","/research/masters-thesis",{"title":74,"_path":75},"Airspace auction simulator for urban drone traffic","/research/masters-project",{"title":77,"_path":78},"Physical sky rendering engine for appleseed","/research/bachelors-thesis",{"title":80,"_path":81,"children":82,"icon":46},"Projects","/projects",[83,84,85],{"title":6,"_path":5},{"title":17,"_path":16},{"title":26,"_path":25},{"title":87,"_path":88,"children":89,"icon":46},"Podcast","/podcast",[90,93,96,99,102,105,108,111,114,117,120,123,126,129,132,135,138,141,144,147,150,153,156,159,162,165,168],{"title":91,"_path":92},"Measuring political bias in language models: systematic analysis using Swiss Smart Vote data","/podcast/political-bias-in-language-models",{"title":94,"_path":95},"DeepSeek R1: pure reinforcement learning for reasoning and why distillation changes everything","/podcast/deepseek-r1-reasoning",{"title":97,"_path":98},"DeepSeek V3: how mixture-of-experts and multi-token prediction enable $5.5M training runs","/podcast/deepseek-v3-architecture",{"title":100,"_path":101},"SRF Arena part 3: international regulation, student perspectives, and why the debate structure failed","/podcast/srf-arena-final-analysis",{"title":103,"_path":104},"SRF Arena part 2: the EU AI Act, nationalization demands, and Switzerland's supercomputer strategy","/podcast/srf-arena-regulation-debate",{"title":106,"_path":107},"Deconstructing the SRF Arena AI debate: deepfakes, Swiss GPT, and the job displacement argument","/podcast/srf-arena-ai-debate-analysis",{"title":109,"_path":110},"O3-mini: how a smaller model outperforms its predecessor at a fraction of the cost","/podcast/openai-o3-mini",{"title":112,"_path":113},"OpenAI o3: trading compute time for reasoning capability","/podcast/openai-o3",{"title":115,"_path":116},"ChatGPT o1: reasoning breakthroughs and emergent deception","/podcast/chatgpt-o1-manipulation",{"title":118,"_path":119},"When AI kills: autonomous weapons, drone swarms, and predictive policing","/podcast/when-ai-kills",{"title":121,"_path":122},"Google's AI pivot: 25% AI-generated code and 90% cost reduction","/podcast/google-ai-revolution",{"title":124,"_path":125},"Why AI projects fail: a practitioner's guide to implementation","/podcast/ai-project-implementation",{"title":127,"_path":128},"Deep learning explained: from embedding spaces to few-shot learning","/podcast/deep-learning-explained",{"title":130,"_path":131},"Vision AI: why language models need to see, and how Llama 3.2 gets there","/podcast/vision-ai",{"title":133,"_path":134},"BitNets and the road to AGI: on-device inference and Sam Altman's 1000-day prediction","/podcast/bitnets-and-agi",{"title":136,"_path":137},"OpenAI o1 benchmarks and AGI implications: IQ 120, coding breakthroughs, and what they mean","/podcast/openai-o1-technical-analysis",{"title":139,"_path":140},"OpenAI o1 and the mechanics of self-reflection: how 70,000 hidden tokens change inference","/podcast/openai-o1-self-reflection",{"title":142,"_path":143},"AI utopia 2035: when automation funds a renaissance in human agency (part 2 of 2)","/podcast/ai-utopia-2035",{"title":145,"_path":146},"AI dystopia 2035: when AI becomes the lifeblood of the economy (part 1 of 2)","/podcast/ai-dystopia-2035",{"title":148,"_path":149},"AI hype vs. reality: a technical assessment of where things actually stand","/podcast/ai-hype-vs-reality",{"title":151,"_path":152},"Open-source AI: the infrastructure behind the hype","/podcast/open-source-ai",{"title":154,"_path":155},"Is AI intelligent? Why the question matters less than you think","/podcast/is-ai-intelligent",{"title":157,"_path":158},"AI in education: why bans backfire and what actually needs to change","/podcast/ai-in-education",{"title":160,"_path":161},"Bias in AI systems: how 15 people shape the values of a billion-user product","/podcast/bias-in-ai-systems",{"title":163,"_path":164},"AI and the labor market: autonomous agents and the transformation of knowledge work","/podcast/ai-and-the-labor-market",{"title":166,"_path":167},"AI terminology explained: a technical guide beyond the hype","/podcast/ai-terminology-explained",{"title":169,"_path":170},"AI and democratic manipulation: from Cambridge Analytica to language models","/podcast/ai-and-democracy",{"title":172,"_path":173,"children":174,"icon":46},"Appearances","/appearances",[175,178,181,184,187,190,193,196,199,202,205,208,211,214],{"title":176,"_path":177},"AI trends 2025 and predictions for 2026: model convergence, integration, and sovereignty","/appearances/webinar-2025-rewind-2026-outlook",{"title":179,"_path":180},"Swiss AI Impact Forum 2025: live demos of the Swiss AI Hub","/appearances/swiss-ai-impact-forum-2025",{"title":182,"_path":183},"AI trends 2024 and predictions for 2025: a technical analysis","/appearances/webinar-2024-rewind-2025-outlook",{"title":185,"_path":186},"AI as a development partner: tools, techniques, and team integration","/appearances/webinar-ai-development-partner",{"title":188,"_path":189},"Swiss AI Impact Forum: Panel on the future of AI in Switzerland","/appearances/swiss-ai-impact-forum-2024",{"title":191,"_path":192},"AI in knowledge management: keynote at the SWICO event in Zurich","/appearances/swico",{"title":194,"_path":195},"Swiss AI Conference: hands-on workshop on AI agents in the enterprise","/appearances/swiss-ai-conference",{"title":197,"_path":198},"AI trends 2023: milestones and developments in artificial intelligence","/appearances/webinar-2023-rewind",{"title":200,"_path":201},"KI Revolution: AI first how a digital native thinks about generative AI","/appearances/bbv-ki-revolution",{"title":203,"_path":204},"AI agents: the future of enterprise automation","/appearances/netzwoche",{"title":206,"_path":207},"ChatGPT demystified: technical deep dive into large language models","/appearances/webinar-chatgpt-demystified",{"title":209,"_path":210},"Swarm intelligence and AI: the future of enterprise automation","/appearances/webinar-swarm-intelligence",{"title":212,"_path":213},"Polygon Software our journey to an innovative UZH tech startup","/appearances/readme-polygon",{"title":215,"_path":216},"UZH startup label for Polygon Software","/appearances/uzh-startup-label",1775406465317]