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True computer use is fully general. FDM-1 uses arrow keys on a computer to steer a car in San Francisco with less than 1 hour of fine-tuning data. The action policy is critical: tuning FDM-1 to drive gets much higher accuracy than tuning just the video encoder on the... show more

Standard Intelligence

10,412 subscribers

72,372 просмотров • 6 месяцев назад •via X (Twitter)

Наука и технологии

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Комментарии: 14

Фото профиля Standard Intelligence

Standard Intelligence6 месяцев назад

FDM-1 completes complex tasks and navigates interfaces well enough to use CAD applications. Forking VMs allow us to snapshot when a successful operation completes (extrusion, selection, etc.), letting us apply test-time compute to computer use.

Фото профиля Standard Intelligence

Standard Intelligence6 месяцев назад

Inspired by VPT (Baker et al), we train an inverse dynamics model (IDM) to predict frame-by-frame computer actions. The IDM leverages 40k hours of contractor data to label 11 million hours of screen recordings—550,000x larger than the largest open-source computer use dataset.

Фото профиля Standard Intelligence

Standard Intelligence6 месяцев назад

We’ve made two main advances: the ability to train on our 11M+ hour computer action dataset and understand long-context video. Our video encoder can fit nearly two hours of 30FPS, high-resolution video into a 1M token context window, ~50x more efficient than existing SOTA.

Фото профиля Standard Intelligence

Standard Intelligence6 месяцев назад

Computer use models shouldn't learn from screenshots. We built a new foundation model that learns from video like humans do. FDM-1 can construct a gear in Blender, find software bugs, and even drive a real car through San Francisco using arrow keys.

Фото профиля Standard Intelligence

Standard Intelligence6 месяцев назад

Here’s the blog post, where you can learn more about how we trained this model:

Фото профиля agniv

agniv6 месяцев назад

HOLY DUCK

Фото профиля _____

_____6 месяцев назад

amazing work! any idea why the baseline for the self driving task starts out worse than random guessing though?

Фото профиля Yuze

Yuze6 месяцев назад

fascinating work on the context compression part! Wondering if the model would be able to know what is a good quality action at system 2 level. eg. when to raise/fall on playing card games 😀

Фото профиля Yuval Grossman

Yuval Grossman6 месяцев назад

Can you explain what do you mean here by “tuning the video encoder”?

Фото профиля Samu

Samu6 месяцев назад

nice

Фото профиля madhavan

madhavan6 месяцев назад

holy fire

Фото профиля Gary Basin

Gary Basin6 месяцев назад

> less than 1 hour of fine-tuning data

Фото профиля FallenOne

FallenOne6 месяцев назад

that's so cool

Фото профиля Haris Poljo

Haris Poljo6 месяцев назад

@comma_ai

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