Allen Downey’s books are very good. For example: Modeling and Simulation in Python

https://allendowney.github.io/ModSimPy/

“Proper” writing technique has the pen being right angled to the line, which puts the wrist below the line and avoids smudging. It’s pretty uncomfortable at first, but can be learned.

Surely the earth 50-100m down is warm due to radioactive decay deeper in the crust, rather than from “absorbing sunlight over millenia”!

A valid point, not sure why you were downvoted

Geothermal, Nuclear and Tidal* are sources which don't rely on the Sun. Fossil fuels are solar energy that's been stored for millions of years, Solar and Wind rely on the sun.

* OK the sun has a small affect on Tidal but the moon has more of an effect - and there's about 10^30J of energy in it's orbital energy, enough to power human civilization for billions of years

That's nothing compared to the sun of course, which puts out about that amount of energy every hour.

At those levels the temperature is the same as the groundwater.

Which in turn is originally heated by the sun.

Further down (maybe 1000m under ideal conditions) the heat comes from the core.

I may add that in Sweden this kind of heat pumps are abundant. I have one with a 150m drill hole.

Also some from the initial heat of formation of the Earth.

But yeah - this is coming from inside, not outside.

It would be really useful to see a real example of a use-case. Is there one available?

Looks great! Do you anticipate any pushback from cloud providers, who might one day decide to restrict access to stop people getting a better price elsewhere?

We don't anticipate this will happen for a few reasons. When the usage of SkyPilot (or a SkyPilot-like "intercloud broker" system) is small, it probably doesn't warrant the dominant clouds' attention.

When the usage gets bigger, I'm not sure how providers can restrict access anyway (curious if there are precedents). There are quite a few large multicloud platforms like Snowflake or Databricks heavily utilizing AWS/GCP/Azure already. (Granted, these platforms are not meta-cloud, in the sense of moving their customer workloads transparently across clouds.)

Ultimately we see such a system to grow the pie for the whole cloud market. The incumbents' relative shares may drop, but their absolute volume will grow.

One of the insights here is using the “tangent point energy” as part of the repulsion loss function. If anyone’s used, or knows of, a python implementation of this TPE function then please lmk!