Published 3 articles so far, but working on AI architecture and management. While most people are focused on prompt engineering and making stuff with AI; I'm more interested in how it actually works, how to size workloads, how to maximize performance, the security and safety aspects. Here is my most recent article where I played with benchmarking tools to get a baseline and understand how configurations impact token generation
Professor Madhavapeddy, am I understanding your comment correctly? "without having to seek permission slips signed in triplicate", the motivation to create Docker was because of IT bureaucracy?
I've been trying to use tools like these for data aggregation, analysis, and finding trends. One major issue I experience with almost every product is I will tell it to "sort by column x" and it either doesn't do it, or will state that it did it when in fact it did not do the sorting. Check out this query: https://www.phind.com/search/cm7444is700011y6rtzk6l5th
How did you select the hardware?
Did you do a bake off/poc with different vendors?
With the intention of being in different countries, are you going to leverage the same hardware at every DC?
What level of support SLA did you go with for your hardware vendors and the colo facilities?
And my favorite, how are your finances changing (plus pros cons) by going capex vs opex?