If you are interested in more maths and 3D Geometry, the bible of the field is "Multiple view geometry in computer vision" by Hartley and Zisserman. Szielski's book is very hands on, but is it more of a formulas + litterature review book than a clean derivation book.
A lot of 3D Geometry algorithms are based on clean derivations and estimations, thus depending on your math fluency, you will find great enjoyment in that book too. The proofs flow really well.
I think the PR vs actual results of Lambda is a big problem when a lot of complains on higher education are about the gap between the dream vision of what a degree does for you, vs reality. But fine. The complains about ISA are mostly unfair
> I have never lied
That's probably one of the things you should never say ever. People will find moments you were either not telling what turned out to be the truth, or were not accurate, and will paint you as totally dishonest.
This assumes talent is geographically homogeneous. IMHO, Talent in top cities in the US is better than the one in the rest of the countries, and so it goes for other countries.
For top US firms, it may well be that there is a better pool for top talent, but not THAT much better. I believe it would be possible to do inferences from # of non-US citizen in FAANGs.
On Urbanism:
Her podcast Order without Design [0] where she interviews the Bertaud couple
Fields note on Miami [1] (with beautiful pictures)
Metamuse interview on cities [2]
and a lot more on her blog
On tech :
She was the PM for Github sponsors (and I believe other open-source friendly projects), great interview of her by the changelog [4]
The Pioneer series (of which this interview is an episod), favorites are Louis Pouzing and roundtable about Hamming [5]
[0] https://podcasts.apple.com/us/podcast/order-without-design-h...
[1] https://devonzuegel.com/post/field-notes-miami
[2] https://museapp.com/podcast/33-cities/
[3] https://changelog.com/podcast/370
[4] https://www.notion.so/blog/topic/pioneers