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Osmosis

Company blog · osmosis.ai/blogaiprogramming

Osmosis is the company blog at osmosis.ai, writing about ai and programming. Since 2025, 3 different Hacker News readers have linked it 9 times, most often “Training over a thousand LoRA adapters at once”. No feed was found, so read it on the site itself.

No feed foundVisit the blog
9mentions?
3HN people?
2025–2026first – last linked?
Links on Hacker News per year · peak 6 in 2025

Too few sampled comments (1) to say how often HN recommends it.?

Why HN links it

The linked material is a product announcement for an open source small language model, osmosis-mcp-4b, that connects any MCP client to any MCP server. No comment discusses the writing.

Summarised by Claude from a sample of 1 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

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.

Most-linked posts?

  1. Training over a thousand LoRA adapters at once
    2 people · 2 mentions · first linked 2026-06-02

What Hacker News says?

  1. Hey HN! We’re Kasey and Andy from Osmosis ( https://osmosis.ai/ ). We’ve been playing with MCP recently and wanted to share a lightweight open source model that can connect any MCP client* to any MCP server! Check it out here: https://huggingface.co/osmosis-ai/osmosis-mcp-4b Right now, the only models that consistently work well for MCP are large and closed-source (e.g. 3.7 Sonnet, Gemini 2.5). Other models struggle…

    Comment linking /

    on “Open Source SLM Trained for MCP”
  2. Submitted Training over a thousand LoRA adapters at once as a story · 8 points

    HN discussion
  3. Submitted Open Source SLM Trained for MCP as a story · 8 points

    HN discussion
  4. Submitted LoRA's Limitations: Head-to-Head with Full RL as a story · 7 points

    HN discussion
  5. Submitted Show HN: LLM structured outputs hurt performance, we built a model to fix it as a story · 5 points

    HN discussion
  6. Submitted Unlocking LoRA Moe RL for Qwen3.5 as a story · 3 points

    HN discussion
  7. Submitted Code merging SLM exceeding performance of large models as a story · 3 points

    HN discussion
  8. Submitted Exploring Foundation Models' Tool-Use Efficacy as a story · 2 points

    HN discussion
  9. Submitted Training Thousands of LoRA Adapters at Once as a story · 1 points

    HN discussion

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