What used to be feature engineering a decade or more ago now seems to have shifted to developing distributed representations. LLMs use word tokens (for words or the entities in images). But there are many more. The 3D Fields (or whatever they have evolved to) developed by Fei-Fei Li's group represent visual information in a way better suited for geometrical tasks. Wav2Vec, the convolutional features for YOLO and friends, and these sentence representations are other examples. I would love to read a review of this circle of ideas.
I also prefer to number just the important equations. One of the advantages of numbering all equations is that the reader can binary search an equation by number. I try to mitigate that loss by providing page numbers or section numbers.
Providing “contrast” is something I appreciate as a reader. It is much easier to provide in person, on a whiteboard. Maybe we need papers to have references to YouTube derivations :)
One of my pet theories is that flimsy homes reflect an economics signaling problem: it is hard to prove to a buyer the value of quality. Whereas size is easier. As a suburban home owner, I would have preferred the quality-square footage point to lean a bit more towards quality.
I also like Contact, which I think of as Sagan’s struggle with reconciling religion and science for himself. Also, I nlike what the article mentions, I recall the book being based on the script.
I got through graduate school and over a decade of research with my inexpensive but very smooth Uni-ball cylinders (or classic roller) micro, 0.5mm pens. They were light, with a minimal and elegant design, inexpensive, and wrote great. Then, about a decade ago, something happened to them. I now go between a Jetstream (a ballpoint) and the Uni-ball Eye (which feels identical to the Vision to me).
I would have included symbolic algebra systems to the list. Many famous calculations in physics and mathematics may not have been attempted without them. Macsyma and Reduce paved the way for Mathematica and Maple. There are still many symbolic algebra algorithms waiting to be implemented. The love and care many open source symbolic systems are receiving is a reflection of their need and importance to science and technology.
Amazing things can happen when cellular automata have symmetries. Conserve number and momentum and you're a few steps from the HPP gas [0]. Make the momentum flow a bit more isotropic, and you are on your way to the FHP gas [1]. The history I remember is that Hasslacher and Wolfram had overlapped at the IAS early 1980s. On the summer of 1985 Hasslacher visited Frisch in Nice. It was there that they guessed that the hexagonal lattice might brake the strange conservation laws of HPP. After that it was a few days until they had a set of rules for the lattice gas fluid in 2d. From France Hasslacher called Shimomura at Los Alamos and asked him if could implement them. In a few days Shimomura has a crowd staring at his screen watching a simulation of a fluid flow past an obstacle shedding vortices in real simulation time. We can do that today with our smartphones, but at the time it must have been a first.
Some URL shorteners provide a copy of their mappings to the Internet Archive as a promise that if they stop functioning for any reason the archive will continue to provide the mapping (and make the mapping file available).