{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"AI News Today | Julian Goldie Podcast","title":"Ornith-1.0 is INSANE (FREE + Local + Open Source)!","html":"","width":"100%","height":180,"duration":546,"description":"Ornif 1.0: Free Self-Learning Local Coding Model (Runs on Ollama + Works with Hermes Agents)\nThe video tests Ornif 1.0, a new free self-learning local open coding model from Deep Reinforce, showing benchmark comparisons where it outperforms models like Gemma 4 31B and even compares well against larger flagship options. The model can be downloaded via Ollama with a simple command and is integrated into the creator’s agent operating system, including Hermes profiles for agentic workflows. Ornif’s key idea is “self-scaffolding”: it writes its own plans/instructions, generates multiple solution rollouts, gets graded, and improves both planning and coding through reinforcement learning. The creator highlights a gallery of apps, games, tools, and visual outputs made with Ornif, plus local and frontier leaderboards, and demonstrates local offline systems like a Hermes engine, agent Kanban orchestration, and local chat, emphasizing local AI benefits like being free, private, fast, and improving.\n00:00 Meet Ornif 1.0\n00:34 Setup With Ollama\n00:45 What Ornif Is\n01:04 Real Build Examples\n01:51 Benchmark Reality Check\n02:11 Self Improving Framework\n03:02 Reinforcement Learning Loop\n03:52 Self Scaffolding Explained\n05:31 Local Leaderboards Demos\n06:21 Agent OS Integrations\n07:32 Model Comparisons Use Cases\n08:05 Join The Community\n09:05 Final Thanks","thumbnail_url":"https://img.transistorcdn.com/Tp0JSUlyiAe2ran44b13cjk4ImQYS1QEMKCAa9Q7go0/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9lNTYz/NGQxMTU2ZTM1MzU5/MDNiYjcwZjJmYTY5/ODJmOS5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}