Weekly Summary(20240609)

技术

Shader 可能是 C 端落地性能问题的解决方案

有感于子焱的分享，这个方向我们可以深入挖掘一下。

包括 WebGPU，这还可以作为前端入行 AI 的一个切入点。

Data Storytelling

这个居然也可以卖钱，图表+Data Storytelling：

Columns: your AI data storyteller

Chrome 本地调试线上资源

Chrome-将浏览器执行脚本代理到本地

想法

慢一点

慢一点，慢生活，慢就是快，关键是方向和目标得正确，不然即使着急忙慌，也是误入歧途，最后回头一看，纯属浪费时光。

最近在家里的慢生活，这个周末和上周的几天，没有去想工作的事情，感觉非常放松。

周末就放开玩，别想着工作和学习，不然玩得不开心，也没学进去。

心流

我现在很不专注，做事没那种心流的状态，太浮躁马虎了，这样做不好，也做不精。

回顾下去年 5 月份学习 AI 的时候，是真的在学习的，那种感觉很好。当时更多是兴趣驱动吧，就像学 UE 一样，兴趣永远是最好的老师。

好闻摘抄

If you can’t measure it, you can’t improve it.

When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind.

– William Thomson(Lord Kelvin)

There is often a significant gap between technically feasible demos and successful productization. We approach deployment of ideas to products with three guidelines:

  1. Prioritize by technical feasibility and impact: Work on ideas wherein both technical feasibility has already been established and high (measureable) impact on engineers’ workflows is expected.
  2. Learn quickly, to improve UX and model quality: Focus on iterating quickly and extracting lessons learned, while safeguarding developer productivity and happiness. User experience is just as important as model quality.
  3. Measure effectiveness: As our goal is to increase productivity and satisfaction metrics, we need to extensively monitor these metrics.

– AI in software engineering at Google: Progress and the path ahead