Echoverse: Deep, evolving environments for computer-use agents
At a glance We built twelve training worlds for computer-use agents: ten deep domain worlds and two capability worlds, each drilling a single control rendered in many forms (date pickers and nested filters). Depth is what makes them worth training on: these worlds reproduce an application’s real behavior, come seeded with realistic data, and keep state coherent across screens and users. Trained on all twelve, a 9B model nearly doubles its base score (36.5% to 67.1%), coming within fourteen points of GPT-5.4.
- ▪At a glance We built twelve training worlds for computer-use agents: ten deep domain worlds and two capability worlds, each drilling a single control rendered in many forms (date pickers and nested filters).
- ▪Depth is what makes them worth training on: these worlds reproduce an application’s real behavior, come seeded with realistic data, and keep state coherent across screens and users.
- ▪Trained on all twelve, a 9B model nearly doubles its base score (36.5% to 67.1%), coming within fourteen points of GPT-5.4.
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| Original publisher | Microsoft Research |
| Canonical URL | https://www.microsoft.com/en-us/research/blog/echoverse-deep-evolving-environments-for-computer-use-agents/ |
| Publication time | Thu, 30 Jul 2026 17:00:00 +0000 |
| Retrieval time | 2026-07-30T18:57:29.406Z |
| Last seen | 2026-07-30T18:57:29.406Z |
| Headline source | Publisher (no WeSearch rewrite) |
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| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
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| Cluster | Yk8on2185sSz · 1 stories |
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| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Echoverse: Deep, evolving environments for computer-use agents Published July 30, 2026 By Akshay Nambi , Principal Researcher Yash Pandya , Senior Research Engineer Sahil Gupta , Research Intern Sarthak Harne , Research Fellow Archana Yadav , Software Engineer 2 Kavyansh Chourasia , Research SDE 2 Yash Lara , Senior PM Ahmed Awadallah , Partner Research Manager Ece Kamar , CVP and Lab Director of AI Frontiers Share this page Share on Facebook Share on X Share on LinkedIn Share on Reddit Subscribe to our RSS feed Scaling fidelity over sheer count, targeting the capabilities agents actually lack, and evolving with the models they train.
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