Think of it as people going out to dinner. The US orders one plate of food per person, when China orders food. Each Chinese is only allowed to have half a plate.
Why? Because they are Chinese, and food ordering is not by headcount but by nationality.
Who in their right mind think this is reasonable?
We need to decrease emission, but it should be across board on a per capita basis.
"You need to be able to increase the costs of getting caught" -- Edward Snowden
Deliberately inserted malware, laying in plain sight in source code, is an existential risk for a company with a reputation like IBM's. Of course, there isn't a 100% guarantee of it being noticed, but a 1% chance of that happening is enough for them to tell the spooks to fuck off.
Special Access Programs only work because God-mode coprocessors like the Intel ME ensure zero risk of blowback for the manufacturer. Force them to have skin in the game and they aren't pushovers anymore.
We say specifically “diagram a technical system you understand well.” It’s going to be challenging to work in technology if the only technical system you understand well is the one you’re currently working on and only the parts that are under NDA.
I have the opposite question from other people in the thread - this seems pretty open-ended.
Just as an example, I do bioinformatics work, and "technical system" for someone I'm interviewing (as I understand your question) might encompass any of:
- a workflow manager: how it works under the hood, common patterns for modularity/reuse or configuration
- a specific pipeline: the stages of cleaning and quantifying raw data, the rationale for various stages and the tools chosen to execute them (including how to benchmark various methods against each other)
- a specific third-party tool: theoretical details of the algorithm, practical considerations for when to apply one over another
- familiarity with common general-purpose packages or APIs (e.g. pandas, numpy, scikit-learn)
- QC: common metrics for QC'ing various experimental data, how to decide if data is "good enough", how to troubleshoot biological vs technical (lab) vs technical (computational) sources of error
- biology: technical details of an experiment, the technologies generating the data, or the underlying biology
- data analysis: how to choose and make relevant figures, any of many data-science/ML topics (e.g. clustering), connecting data to relevant domain questions
- devops: data storage/management on HPC or cloud, HPC job schedulers, any of many cloud topics (e.g. IAC, setting up a database or cloud execution of a pipeline)
I'm more curious about how you guide a candidate towards selecting a system that gives you the most relevant perspective on their thinking and skillset - do you provide any suggestions, or are there typically pretty evident choices based on the role?
For our more junior roles, we leave it more open ended because candidates may not have a similar knowledge bases to the panel. For more senior roles we advise that if they pick technologies that are pertinent to the role and likely to be understood by senior/lead/staff engineers, the process will go better for candidates and panel members.
If I were in your position, one of understanding many complex systems, I would advise you to pick where you felt both strong and the panel was likely to have some entry point into.
So draw the block diagram of something you worked on in school. Or, I don't know, a radio or something, if you're a hardware person.
Someone who answers, "I can't draw anything for you because everything I know about is somebody's private IP," isn't going to get the job. At least, not if I'm doing the interviewing.
You must know something about something else. Right?
Or just interview some place that doesn't give this kind of interview, like most companies. It's pretty trivial to get hired even if you can't talk about technical specifics along the lines of an architecture diagram.
This is why this question is so informative. There are a ton of people in this thread arguing that they can’t describe any technologies they understand because of NDAs.
"Great, that'll do nicely. Vacuum cleaners are complicated and interesting machines. What can you tell me about how a vacuum cleaner is built and how it works? Also, vacuum cleaners are pretty old tech. Is there room for further innovation in that area? If so, what angles would you explore if you worked at a vacuum cleaner company?"
Not sure what's done at Uber but I imagine HA is a requirement.
There are mitigations and a couple of hours of dev downtime is imo not the end of world.
Sure, prod incident could overlap with a devpod incident but sounds like they still have the choice to do local dev.
Why? Because they are Chinese, and food ordering is not by headcount but by nationality.
Who in their right mind think this is reasonable?
We need to decrease emission, but it should be across board on a per capita basis.