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CASE FILE / Model & agent routing

Jev by @typesafeai turns your  Mac into an AI agent

Jev by @typesafeai turns your  Mac into an AI agent... what this means for You ? - Jev, a new model from a ChatGPT co-inventor, can operate computer tools in real time. - It is 200x faster for Computer use and 400x cheaper in addition to the optimizations. - Yappy from @MitosisLabs is an AI that lives on your mac and do several things in parallel. Filling out Job applications, doing your Taxes and other documents, filling out forms, and so on... - With Jev, all these things happen at the blink of your eye! Below is a video demonstrating this IRL. Here are the benchmarks (Yappy + Jev V/S our competitor): - End-to-end time: 1m 54s vs 13m 14s - LLM Calls: 22 vs 104 - Input tokens consumed: 0.39M vs 11.24M - Estimated cost of the run: ~$0.24 vs ~$4.24 Link to download in comments.

By Prakshal Jain @prakshaljain_
● ● ●CASE FILEGUIDE
Prakshal Jain · @prakshaljain_

Original post

Jev by @typesafeai turns your  Mac into an AI agent... what this means for You ? - Jev, a new model from a ChatGPT co-inventor, can operate computer tools in real time. - It is 200x faster for Computer use and 400x cheaper in addition to the optimizations. - Yappy from @MitosisLabs is an AI that lives on your mac and do several things in parallel. Filling out Job applications, doing your Taxes and other documents, filling out forms, and so on... - With Jev, all these things happen at the blink of your eye! Below is a video demonstrating this IRL. Here are the benchmarks (Yappy + Jev V/S our competitor): - End-to-end time: 1m 54s vs 13m 14s - LLM Calls: 22 vs 104 - Input tokens consumed: 0.39M vs 11.24M - Estimated cost of the run: ~$0.24 vs ~$4.24 Link to download in comments.
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Chinese translation

Jev by @typesafeai将您的DeliverMac变成了人工智能代理. 这对你意味着什么? - Jev是ChatGPT共同发明者的一款新型号,可以实时操作计算机工具。 - 除了优化外,计算机使用速度更快200倍,便宜400倍。 - @MitosisLabs的Yappy是一款人工智能,它运行在您的Mac上,并并行执行多项任务。填写工作申请表、填写税务和其他文件、填写表格等等. - 对于Jev,所有这些事情都在眨眼间发生! 以下是演示该IRL的视频。 以下是基准(Yappy + Jev V/S 我们的竞争对手): - 端到端时间:1 m 54 s vs 13 m 14 s - LLM Calls:22 vs 104 - 消耗的输入令牌:0.39 M vs 11.24 M - 运行的估计成本:约0.24美元vs约4.24美元 在评论中下载链接。

What this case shows

  • Let JEV choose the model or tool first
  • Auto-route on high confidence, escalate otherwise
  • This is the most common production pattern