After many words, the email chain I received netted out to this:
- I can't teach myself data science on my crappy old Windows machine.
- I've decided to get a new Windows machine. Here are the specs.
My response was a mixture of incredulity and bafflement.
It appears that two things happened while I wasn't paying attention.
- Apple ceased to exist.
- The cloud ceased to exist.
I'm aware that many people think the Apple alternative is a
non-starter. They are sure that after 40+ years selling computes,
Apple is doomed, and we'll only have Windows on the desktop.
Seriously.
Some people have farcical explanations for why Apple Cannot be Taken
Seriously.
In this specific instance, there was a large investment in Python and
Java that somehow couldn't be rebuild in Mac OS X. Details were
explicitly not provided. Which is a way of saying there were no
tangible "requirements" for this upgrade. Just specification numbers.
Import note. None of this involved "data" or "science." That was the
baffling part. No objective measurement of anything. No list of
software titles. No projects. No dataset sizes. Nothing.
The anti-cloud argument was even stranger than the anti-Mac argument.
Somehow, a super-large AWS server -- let's say it was a x1.16xlarge --
being used an hour a day (365 day*1 hr/day*$1.82/hr = $664) was deemed
*more* expensive that a 64Gb 6-core home-based machine that would
sit idle 23 hours each day.
The best part of $664/yr being *more* expensive?
Expert Judgement.
No "data". No "science". No measurement. No supporting details.
I wish I'd kept the email describing how someone who knew something
said something about pricing. It was marvelous Highest Paid
Person's Opinion nonsense.
AFAIK, they were using 8,766 hours per year to compare AWS computing
vs. at-home computing. This meant that an m5.4xlarge should be
considered as costing $1,939 each year. Presumably because they'd
never shut it off.
It included terms like "half-way decent performance."
There's a depth of wrongness to this that's hard to characterize
beyond no "data" and no "science".