Data operations are increasingly happening near the GPU side to boost efficiency—especially for compute-heavy workflows. Talking about Arrow file processing and zero-copy queries on DataFrames, which are becoming crucial for modern data pipelines. I think another option worth considering is chdb, which supports these features and fits well with this shift. (author of chdb here)
I think Human Layer is a great idea. Recently, my baby turned one year old, which made me reflect on many issues. We train AI with a lot of data but overlook the impact that decades of seemingly useless data from human growth experiences have on our brain development. As a result, humans still have an incomparable advantage over LLMs in terms of the so-called "big picture." For example, a recent experience I had was when I asked Claude 3.5-sonnet to write a bash script; it inadvertently modified the PATH variable, costing me a lot of time to fix it. Such attention to detail in work is difficult to avoid through vector db recall or manual context completion. But I believe that a true bash expert would not make such mistakes.