The Verge - Artificial Intelligences 02月20日
Rabbit shows off the AI agent it should have launched with
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Rabbit公司发布了一篇博客文章和视频,展示了一个“通用Android代理”,它以类似于Rabbit一年前声称其R1设备的方式缓慢地控制平板电脑上的应用程序。该代理基于Rabbit去年推出的“通用Web代理”LAM Playground构建。工程师们没有使用Rabbit R1,而是将请求输入到笔记本电脑上的提示框中,然后将其转换为Android平板电脑上的操作。演示包括查找YouTube视频、在鸡尾酒应用程序中查找威士忌鸡尾酒配方、收集配料,然后将它们添加到Google Keep购物清单中。甚至还让它下载了益智游戏2048并弄清楚如何玩,尽管速度很慢。

🤖Rabbit展示了一个在Android平板电脑上运行的“通用Android代理”,它能够执行诸如查找视频、搜索菜谱、以及下载并学习玩游戏等任务,但速度较慢。

📝该代理通过笔记本电脑上的提示框接收指令,然后将这些指令转化为平板电脑上的操作,这与Rabbit R1设备最初承诺的功能类似,但R1本身并未参与演示。

🧩Rabbit的AI代理仍在开发中,尽管自R1发布以来已经进行了一些更新,例如训练AI代理完成特定任务或提示其重新制作自己的界面,但距离其创始人最初的设想仍有差距。

The Humane AI Pin has collapsed, but Rabbit is still kicking. The company published a blog post and video today showing off a “generalist Android agent,” slowly controlling apps on a tablet in much the same way that Rabbit claimed its R1 device would over a year ago. (It couldn’t, and can’t.) The work builds on LAM Playground, a “generalist web agent” Rabbit launched last year.

The engineers don’t use the Rabbit R1 at all for the demonstration. Instead, they type their requests into a prompt box on a laptop, which translates them to actions on an Android tablet. They task it with things like finding a YouTube video or locating a whiskey cocktail recipe in a cocktail app, gathering the ingredients, and then adding them to a Google Keep grocery list. At one point, they ask it to download the puzzle game 2048 and figure out how to play it, which it does, albeit slowly.

The model generally does the things they ask, sometimes well and sometimes with quirks like sending a poem over WhatsApp one message at a time instead of in a single block. One of the engineers wonders if they should have asked it to use line breaks in their prompt, but they don’t go back to try again.

Rabbit’s AI agent is clearly still a work in progress, as it has been since the R1 launched with almost none of the capabilities that founder and CEO Jesse Lyu presented in January 2024. Rabbit has steadily rolled out updates, like the ability to train its AI agents to complete specific tasks or prompt it to remake its own interface. The examples it presented today are “only the core action loop an Android agent completes,” according to Rabbit’s blog post. The company promises to share more about its “upcoming cross-platform multi-agent system” in coming weeks.

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