Meet Ace, The Realtime Computer Autopilot by General Agents

Ace - The AI Realtime Computer Autopilot by General Agents

✔️ Research suggests Ace, developed by General Agents, is a computer autopilot automating desktop tasks using mouse and keyboard.

✔️ It seems likely that Ace is trained on over a million tasks, aiming to liberate humanity from digital labor.

✔️ The evidence leans toward Ace being in early stages, with a research preview available, and it may improve with more resources.

✔️ There is some uncertainty about whether "AI Agent Swarm" refers to multiple agents, but it likely describes Ace's collaborative functionality.

Overview
Ace is an innovative AI tool designed to perform tasks on your desktop, such as mouse clicks and keystrokes, potentially revolutionizing how we interact with computers.

Developed by General Agents, a research lab focused on autonomous intelligence, Ace aims to automate digital tasks to free humans from repetitive work.

Capabilities and Performance
Ace is trained on a vast dataset, reportedly over a million tasks, performed by software specialists and domain experts.
It outperforms other models in computer use tasks, with specific click accuracy rates for different models, and is noted for its speed, with action prediction latency in the hundreds of milliseconds.

Current Status and Future Currently
Ace is in its early stages and may make mistakes, but General Agents is launching an early version in research preview.

As training resources increase, it is expected to become more intelligent and capable, aligning with the company's mission to empower individuals through AI.

Survey Note: Comprehensive Analysis of Ace, the AI Agent Swarm
Ace, developed by General Agents, represents a significant advancement in the field of autonomous intelligence, specifically targeting the automation of desktop tasks.

This report provides a detailed examination of Ace, its capabilities, development, and the broader context of its creation, including the company's mission and the concept of "AI Agent Swarm."

Introduction to Ace
Ace is described as a computer autopilot capable of performing tasks on your desktop using mouse and keyboard inputs. This functionality positions it as a tool for automating digital labor, aligning with General Agents' mission to liberate humanity from repetitive computer tasks. The company's website, General Agents | Introducing Ace, highlights Ace's ability to outperform other models on a suite of computer use tasks, which are open-sourced for transparency at GitHub Repository.

Capabilities and Performance
Ace's primary function is to execute mouse clicks and keystrokes based on screen prompts, trained on an extensive dataset of over a million tasks. This training is conducted by a team of software specialists and domain experts, emphasizing a behavioral training paradigm that focuses on the process generating work outputs, as noted on General Agents | About. Performance metrics include exceptional speed, with action prediction latency in the range of hundreds of milliseconds, and specific click accuracy rates for models such as ace-control-medium and ace-control-small, detailed in the dataset analysis.

Model Click Accuracy (95% CI) Latency (ms, 95% CI)
ace-control-medium 77.56% (+3.41%/-3.59%) 533 (+8/-7)
ace-control-small 72.89% (+3.59%/-3.77%) 324 (+7/-7)

The dataset, showdown-clicks, comprises 5,679 left clicks from macOS desktop tasks, released in March 2025, with a subset showdown-clicks-dev of 557 clicks, ensuring no personally identifiable information (PII) and collected late 2024. Episodes range from tens of seconds to minutes, with screenshots at resolutions from WXGA (1280×800) to WSXGA+ (1680×1050), evaluated for instruction-following and low-level control capabilities.

Development and Training
Ace's development leverages a behavioral training approach, distinct from traditional language and vision models trained on text and images. Instead, it uses screen recordings, mouse, and keyboard logs to learn task performance, making it more natural for domain experts to contribute data without learning new tools. This method is corroborated by the use of step-by-step reasoning in training frontier language models, as mentioned on General Agents | About.

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