卧槽,居然真有比Codex内置computer use更快的操作电脑的方式
我尝试用Codex+Jev打造了一个加强版computer use,我称之为「Jev Use」。比内置的更快更丝滑,token消耗却差不多
下面是我用「添加Mac日历事件」做了一个对比视频,同样的内容,明显可以看到Jev版本整体过程几乎无任何停顿😆
Written in Chinese. Sac built a computer-use loop on Codex with Jev as the judgment layer and calls it Jev Use: faster and smoother than Codex's built-in computer use for about the same tokens, shown side by side on adding a calendar event on a Mac, where the Jev run barely pauses.
卧槽,居然真有比Codex内置computer use更快的操作电脑的方式
我尝试用Codex+Jev打造了一个加强版computer use,我称之为「Jev Use」。比内置的更快更丝滑,token消耗却差不多
下面是我用「添加Mac日历事件」做了一个对比视频,同样的内容,明显可以看到Jev版本整体过程几乎无任何停顿😆
Andre Landgraf's showcase of the yes/no gate, several worked examples at the link.
Ok, jev is really cool. So many great use cases where a fast and accurate yes/no gate can deliver meaningful performance gains.
Played around and built some showcase examples here →
Vipul Sharma's Minecraft agents ask Jev whether to fight or run, from what the agent can see, the mob count, its weapon and its health; one broke off mid-fight as the odds turned.
I hooked up Jev by @typesafeai to a few agents on my Minecraft world. Look at how Jev decides when they should fight and when they should run away.
Jev rates the odds from what the agent can see, mob count, weapon, how hurt it is, and runs away when they are bad. One broke off mid-fight as its odds turned.
Mahmoud's simulation of fifteen autonomous drones through an asteroid field, Jev deciding for each in under 300 ms, all fifteen arriving.
Jev can control a swarm of 15 autonomous drones in real time!
I built a simulation to test it navigating an asteroid field:
• Decision latency: < 300ms
• Survival rate: 100% (all 15 reached the destination)
Built with @typesafeai by @CompleteSkeptic