Computers that Think and Take Actions for You

Computers that Think and Take Actions for You

Author: Demetrios January 2, 2026 Duration: 45:08

Zengyi Qin is the Founder of the OpenAGI Foundation, working on computer-use models and open, agent-centric AI infrastructure.


Computers that Think and Take Actions for You, Zengy Qin // MLOps Podcast #355


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// Abstract

What if the computer itself can think and take actions for you? You just give it a goal, and it performs every click, type, drag, and gets work done across the desktop and web. In this talk, Zengyi reveals the breakthrough technology that his company OpenAGI is developing: AI that can use computers like humans do. He talks about how his team developed the model, why it outperforms similar models from OpenAI and Google, and its wide use cases across different domains.


// Related Links

Website: https://www.qinzy.tech/


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Connect with Zengyi on LinkedIn: /qinzy/


Timestamps:

[00:00] AI and Human Interaction

[00:30] Zengyi's story

[08:19] Why Expensive Models Lost

[06:30] Bigger Models Are Lazy

[10:24] Training Computer-Use vs LLMs

[13:53] World Models and Sandboxes

[19:42] Dealing with Non-Stationary States

[23:56] Training with Software

[26:44] Sandbox Training Process

[41:33] Infrastructure for Computer Models

[44:36] Wrap up


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
Author: Language: en-us Episodes: 100

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