I try to develop primitives for data structures and/or algorithms - starting with e.g a doubly linked list node / binary tree node… moving on to e.g. breadth first search implementation, etc.
Being older, for me this has the benefit of refreshing some compsci fundamentals while exploring the new language.
A 100 nits huge screen at a distance that covers 20% of my field of vision would be the same as a 100 nits tiny screen close to my eye that covers 20% of my field of vision.
Or to put it another way, things don't look dimmer just because they're further away. It's less total light because it covers less of my field of vision.
Fair point, I imagined nits was something like Lumen.
But I think it certainly matters, since nits indicate the amount of light (candles per square meter) hitting a board 1m from the source, if the board/eye is only 10mm away, the intensity in that spot is much higher.
That said, the area changes much more than the distance I think, so overal brightness is probably still not equivalent to 100 nits (at 1m).
> since nits indicate the amount of light (candles per square meter) hitting a board 1m from the source,
I think I can see how you've got here but that's not correct. It's about the light emitted per square meter of the source, not a measure of the light hitting a board some distance away.
Moving a screen closer doesn't make it more intense, because as you move closer it covers more of your vision. Total light increased, but not more intense.
I don't think the brightness changes with the distance. Take any screen (or any object). When you very the distance the color of it doesn't increase or decrease in intensity.
The new M1 Mac’s really are impressive. I suspect I might be similarly impressed by the latest AMD chips with 8 cores, but quite a lot of my everyday workloads are seeing 5x-10x performance increases over my previous 2015 MacBook.
I have the M1 Pro with (8 + 2) cores. But seeing as the cores are identical I suspect with the base models with (4 + 4) cores you'd see very similar performance except you'd be looking at 5x rather than 10x on multicore workloads.
Have the cheapest M1. It flies and the battery life is stellar. The only downside I would say is it's only 8GB of RAM. If you're doing anything with electron development, it's a no-go. You'll need a minimum of 16GB.
It's an incredible machine though. The perf and battery life remind me of the upgrade I got when switching from a HDD to a SSD for the first time. It changes how I use the device.
I have a largish white board (thanks home office) on which I summarize a (sub)section of a book / online course in my own handwriting / symbols / diagrams after reading / watching it first and doing the summarizing on a second run (after which I take a photo and save it to a doc on the topic).
This method has helped me commit quite a lot of conceptual information into long term memory - but - it is time consuming.
If I ever need to refresh my memory on a topic, I pull up the photo and redraw it - sometimes adding or changing things a bit - then take photo again. Rinse and repeat.
Thats not quite accurate- it is true that high amp current is deadly in many scenarios, but it takes both amps and volts to kill. High amp, high voltage current is a killer for sure, but high current at sufficiently tiny voltages is not necessarily deadly. Similarly, high voltage at low currents is usually not deadly (but can be very painful).
High voltage from a Tesla coil not only has low average current, but is subject to the skin effect. So while it can still cause a painful shock to your superficial sensory nerves, not much of that energy ends up in contact with the motor nerves.
TL,DR: you probably don't want to be shocked by a big Tesla coil, even though it won't kill you.
You are assuming edible plants to have been readily available at high enough concentrations at the hunter gatherer stage of human evolution.
It is energetically more expensive to roam a large area to gather x calories than finding and killing an animal (herbivore) that did that for you - never mind the ability of the herbivore to release calories contained in leaves and grass (something humans cannot do)
Then in winter this ratio increases even more.
I don’t know if you’ve ever been to the African savannah, but early human evolution here was definitely not driven by the abundance of edible vegetation.
Interesting to see the relatively small percentage of PUT requests.
A (generously opinionated) observation of the technical debt / re-invented wheels in the wild?
For example a gateway / proxy can much more efficiently route a PUT payload to the required upstream (with “INSERT” permission and tuning) than deciding by analysing the payload, or even worse, not having to because the entire stack just uses POST as some franken analogue to “UPSERT”
Goes a bit deeper. Can you replace a source of data with another in a few lines (besides the new implementation) and not break a whole chain of dependencies and associates unit tests? (apart from "does someone knows what's going on") - i.e. code at scale.
