Osmosis-Structure-0.6B is a small model trained with reinforcement learning to do one thing well: extract structured data, typically JSON, from unformatted text. That’s it!
Osmosis | Forward Deployed Reinforcement Learning Platform
Osmosis is a forward-deployed reinforcement learning platform that helps companies train task-specific AI models that outperform foundation models at a fraction of the cost. Build, deploy, and continuously improve intelligent systems with hands-on integration and real-time feedback.
The control layer for AI
The industry spent two years teaching LLMs to speak JSON. That work mattered: free-form text was unusable in production. Today, every serious inference provider uses some implementation (often open-source) of structured output. Structured output has become essential infrastructure that the team at .txt is proud to have spearheaded. Even as the ecosystem evolves, and open-source alternatives emerged, our engine remains the state of the art.
The control layer for AI
The industry spent two years teaching LLMs to speak JSON. That work mattered: free-form text was unusable in production. Today, every serious inference provider uses some implementation (often open-source) of structured output. Structured output has become essential infrastructure that the team at .txt is proud to have spearheaded. Even as the ecosystem evolves, and open-source alternatives emerged, our engine remains the state of the art.
Structured Outputs with Will Kurt and Cameron Pfiffer - Weaviate Podcast #119!
Everything I Learned Training Frontier Small Models — Maxime Labonne, Liquid AI
Everything I Learned Training Frontier Small Models — Maxime Labonne, Liquid AI
ZML - Model to Metal
ZML is a production inference stack, purpose-built to decouple AI workloads from proprietary hardware.
Daniel Han on Twitter / X
OpenAI's OSS model possible breakdown:1. 120B MoE 5B active + 20B text only2. Trained with Float4 maybe Blackwell chips3. SwiGLU clip (-7,7) like ReLU64. 128K context via YaRN from 4K5. Sliding window 128 + attention sinks6. Llama/Mixtral arch + biasesDetails:1. 120B MoE… https://t.co/bMFp3Z6Gs5 pic.twitter.com/1NFO4utPqr— Daniel Han (@danielhanchen) August 1, 2025
Liquid <> .txt Collaboration | Liquid AI
Faster and more accurate function calling on the edge with .txt’s structured outputs and Liquid Foundation Models
Models Don't "Get Reward" — LessWrong
Models don't "get" reward. Reward is the mechanism by which we select parameters, it is not something "given" to the model. Reinforcement learning sh…
Liquid AI — Device-native foundation models.
Liquid AI is an efficiency-first foundation model company. We build highly capable, compute-optimized models that bring intelligence to any device and medium of choice.
containers/ramalama
RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in production, all through the familiar language of containers.
Models
Amp uses the best model for each task: leading generalist foundation models for complex reasoning and planning, and smaller specialized models for fast, accurate responses in specific domains.
DevReal: Simple Knowledge Graphs with Outlines, neo4j, and Modal, Cameron Pfiffer
