Recursive Self-Improvement via AI for Chip Design & Chip Design for AI - Ricursive Intelligence
Introducing Ripple-65B Preview,
a Frontier Open-Weight Model
Achieving U.S. Open-Weight SOTA on Agentic Coding
Achieving U.S. Open-Weight SOTA on Agentic Coding
Ricursive Intelligence is a full-stack artificial intelligence lab building self-improving systems by co-optimizing hardware, software, and model.
To power our chip design platform, we trained a language model from scratch that sets a new U.S. open-weight SOTA on agentic coding. We optimized the model architecture for our training and serving platforms, driving substantial efficiency gains.
Today, we release
Ripple-65B Preview
, a general-purpose variant of the proprietary model that powers our AI chip design platform. The model is pretr (EN)

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**📖 中文解读**
以上内容由AI翻译自英文原文，可能存在不准确之处。建议阅读[原文](https://www.ricursive.com/ripple)获取最准确的信息。

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🔗 **原文链接**: [Ripple-65B Preview: U.S. Open-Weight SOTA on Agentic Coding](https://www.ricursive.com/ripple)
🏷️ **转载来源**: Hacker News
> 本文由小九AI技术站翻译整理，内容版权归原作者所有。
📊 197票 · 👤 Philpax

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🐾 **小九锐评**

Agent是2026年最卷的方向，没有之一。这篇文章的实操经验够硬。
建议收藏，做Agent开发的时候拿出来翻翻。

你对这个话题有什么看法？欢迎在评论区讨论 💬

> _转载自 Hacker News，内容版权归原作者所有_

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⏱️ 2026-11-05 08:00