Weird, I have always aligned as the gp showed. I’m reasonably sure tidyverse documentation does the same (which is probably where we both picked it up from).
Not for an enterprise buying (or renting) furniture in bulk it isn’t. The chair will also easily last a decade and be turned over to the next employee if this one leaves… unlike computer hardware which is unlikely to be reused and will historically need to be replaced every 24-36 months even if your dev sticks around anyway.
> computer hardware which is unlikely to be reused and will historically need to be replaced every 24-36 months
That seems unreasonably short. My work computer is 10 years old (which is admittedly the other extreme, and far past the lifecycle policy, but it does what I need it to do and I just never really think about replacing it).
> My work computer is 10 years old... but it does what I need it to do and I just never really think about replacing it
It depends what you're working on. My work laptop is 5 years old, and it takes ~4 minutes to do a clean compile of a codebase I work on regularly. The laptop I had before that (which would now be around 10 years old) would take ~40 minutes to compile to the same codebase. It would be completely untenable for me to do the job I do with that laptop (and indeed I only started working in the area I do once I got this one).
That’s more or less my point from a different angle: unlimited spend isn’t reasonable and the justification “but $other_thing is way more expensive!” Is often incorrect.
Computer Engineering is its own discipline, typically lumped with Electrical Engineering, which is more about system architecture and design and only touches on programming at a low level such as device firmware.
What I think you're really lamenting is the devolution of CS education to vocational programming.
“Software Engineering” tends to be about project management: schedules and organisation, estimation, defect rates and so on. For vocational training on existing IT systems (including some coding), which I assume is more what the course focused on, then “Management Information Systems” or “Information Technology” would be the more traditional names IIUC.
None of that really helps LCDs primary downsides of poor contrast ratio and relatively high energy consumption. Backlit displays will always inherently score worse on these metrics vs self emissive displays.
peak brightness is not contrast. If anything higher peaks mean worse contrast, even for systems with local dimming zones due to bleed between zones / gradients in display content which do not align with backlight zones.
LCDs as a transmissive display technology work by emitting a bunch of photons and then selectively filtering some out to achieve the desired color / pixel brightness. Any filtered photon is wasted energy, this is inherent to the display technology and is not limited to dark content, just exacerbated by it.
Given that, all things equal there is no way for LCD to equal the efficiency of a self emissive display, at best it's a question of when will the luminous efficiency of OLED exceed that of white/blue backlight LEDs... and honestly we're likely already at or past that point.
Well, according to ABET Engineering is: “The profession in which a knowledge of the mathematical and natural sciences gained by study, experience, and practice is applied with judgment to develop ways to utilize, economically, the materials and forces of nature for the benefit of mankind”.
By that definition, developing and training an LLM model could be argued to be a form of engineering… but exercising that model definitely isn’t. An analogy to mechanical engineering would be the difference between designing a CNC machine vs programming the machine to carve out a widget.
Complete aside but I believe you meant/it is spelled "too nouveau" (assuming you meant more recently founded schools are too "new money" and lack sufficient prestige due to their young age).
“Working” assumes this new scale is actually based on reality and that an A or B is realistically obtainable without compromises (ie here image quality) that no one wants to make.
Specialization I presume, so one produces the metadata that can be consumed by another.
Also, the thing from the above post that stood out to me would be to act as a reminder for the reader. Not so much the location and emotion, but the character data. I've often found myself wondering who the character is that's appeared in a scene, forgetting that they previously appeared earlier.
Excel does that type coercion if you import from CSV. If you export pandas data to XLSX it adds proper type information and then it imports properly into Excel and you avoid those problems.
Until you have a large amount of data & need either random access or to work on multiple full columns at once. Duplicated keys names mean it's very easy for data in jsonlines format to be orders of magnitude larger than the same data as CSV, which is incredibly annoying if your processing for it isn't amenable to streaming.
