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当你缔造AI时,记取,它比钻石贵!

我试图在我的商讨机构缔造一个袖珍的东谈主工智能商讨测试台,以下是每次BOM和操作用度:

1)500个最新GPU芯片组:约1500万好意思元

2)邻近开荒和所需系统:约600万好意思元

3)5年软件相沿和许可证:3百万好意思元

4)5年电力用度:400万好意思元

5)2名全职履行室职工,为期5年:100万好意思元

这种袖珍东谈主工智能商讨测试台的预算总老本:2900万好意思元

用这样2900万好意思元,我不错招募苟简30名伯克利加州分校或斯坦福大学或剑桥大学或麻省理工学院教育。 偶然我不错招60名清华大学或北京大学的正教育。

是以,哪个更紧迫? 教育 vs AI?

若是你相沿AI,你基本上等于相沿英伟达和中国邻近材料供应商(在台湾和中国大陆)。

若是你相沿教育,你基本上等于相沿咱们后代的学生。

等于这样浅易!

When you build AI, remember, it is more expensive than diamond!

I tried to build a small AI research testbed at my research organization, here is the cost per BOM and operation:

1) 500 newest GPU chipsets: about US$15M

2) Peripheral devices and required systems: about US$6M

3) Software supports and licenses for 5 years: US$3M

4) Electricity power cost for 5 years: US$4M

5) 2 full-time lab staffs for 5 years: US$1M

Total cost of budget for such Small AI research testbed: US$29M

With such US$29M, I can recruit about 30 Full Professors of UC Berkeley or Stanford University or University of Cambridge or MIT Professor. Or I can recruit 60 full professors of Tsinghua University or Peking University.

So, which one is more important? Professor vs. AI?

If you support AI, you are basically supporting Nvidia and Chinese peripheral material vendors (in Taiwan and Mainland China).

If you support professors, you are basically supporting our future generations of students.

That is so simple!九游会j9·游戏「中国」官方网站