ccosm

Highly recommend Stats 110 from Blitzstein. Lectures and textbook are all online https://stat110.hsites.harvard.edu/

>Basically every advanced/"next generation" thing the article touts has fallen flat on its face when applied to real problems

Even Arnold's work? FEEC seemed quite promising last time I was reading about it, but never seemed to get much traction in the wider FEM world.

"I have largely avoided the second law of thermodynamics, which says that entropy always increases. While fascinating, this is so problematic that a good explanation would require another book!"

For those interested I am currently reading "Entropy Demystified" by Arieh Ben-Naim which tackles this side of things from much the same direction.

No Navier-Stokes? Elasticity?

The book for this course is a fantastic practical introduction to Bayesian statistical modeling. If you've ever been curious about probabilistic programming give it a shot.

Also if you're rusty in probability and worried about prerequisites, Harvard's Stat110 can serve as a very good foundation (book and lectures are free online).

Is there a reason why every price increase is referred to as "inflation" these days? I thought inflation had more to do with debasement of a currency than price fluctuations due to supply and demand, with the key functional distinction being that the former can be hard to reverse while the latter can self-correct given time (e.g. the lumber price increase we saw this summer).

Barring some exponential increase in the usability of FPGA tools, I think the mainstreaming of these technologies will forever remain just around the corner.

More coarse-grained architectures like GPUs or reduced-scope architectures with a less intense cognitive load like the programmable IOs found in Raspberry Pi Picos or some Texas Instruments MCUs seem like a much more feasible solution for the vast majority of potential FPGA use-cases a tinkerer would run into.