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MachineFi Labs · 博客

关于情境化世界模型的思考

MachineFi Labs 关于情境化世界模型、Trio-Spark v1.0,以及如何为具体环境构建智能的研究与产品更新。

Trio-Spark accuracy table against Jev 1.14, Clef, Clef-Flash and Laya
Product update

Trio-Spark v1.4: one model for text and vision, same API

Trio-Spark now runs one model for text, image and sampled-video decisions. Thirteen benchmarks against Jev 1.14, Clef, Clef-Flash and Laya.

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Trio-Spark v1.3 accuracy table against v1.2, v1.0, Jev, Clef, Clef-Flash and Laya
Product update

Trio-Spark v1.3: Better decisions on every task we measured

New text weights for the same one-pass decision API. Thirteen benchmarks against v1.2, v1.0 and four other fast decision models.

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Trio-Spark v1.1 and v1.2 matched text regression counts
Product update

Trio-Spark v1.2: Sharper decisions. Same fast API.

A stronger text release for the same decision API. Matched results, separate offline comparisons, and two to eight choices your application controls.

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MachineFi Labs
Product update

Trio-Spark v1.1: See the scene. Choose the next move.

Bring text, one image, or a short sampled window to the same decision API—and choose from the actions your application allows.

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Trio-Spark v1.0 benchmark highlights
Now live

Introducing Trio-Spark v1.0: A one-pass decision API for GUI agents

A structured state and 2–8 allowed actions in; one selected action and the full probability distribution out.

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进展更新

Trio:面向物理运营的世界模型

MachineFi Labs 关于 Trio 的进展更新——我们构建了什么、现在有什么在运行,以及如何让你的摄像头用上它。

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MachineFi LabsSituated World Models. Built to Move.
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