If you want to learn a lot about startups and feel like meeting with a lot you could distribute it in multiple $20k-$30k bets in up and coming startups you believe in. If you aim at landing cash in 20-30 startups with that cash many of them will go to $0, some will be a break even or moderate success, and 1 or 2 might be a likely winner of the entire strategy. Angel investing isn't for everyone and also there are many better ways to see a "more guaranteed" return on investment but little as interesting as getting a front row seat to the future. If you are purely after risk adjusted returns then just make sure you are allocating to beat inflation, mitigate hyper inflation and into something you know or want to know a lot about. Many great investors out there to learn from but if you want the "starter" guide Angel by Jason Calacanis is a pretty decent book to read.
Great writing. This should replace the syllabus for very many Comp Sci / Soft Eng "Intro to Compilers/Interpreters" courses as many do not come close to this level of detail.
I'm considering it for the course I teach! Although one thing that draws me is it doesn't have too much extraneous detail off the main narrative thread.
I currently use parts of the textbook Programming Language Pragmatics [1], one of the semi-standard texts used by a lot of universities (plus some of my own course notes). That book isn't really readable straight through though. It's 992 pages long, and some of the chapters get bogged down in a ton of coverage of the landscape of design and implementation choices. As a reference book that has some pros: you can look up something like looping constructs, and get a very detailed tour of how languages from Algol-68 through Modula-2 and C# have taken different design and implementation strategies. But that's not the same as reading something as your first introduction to a subject.
> I currently use parts of the textbook Programming Language Pragmatics
That was the first PL book I read. I really liked it, but you're right that it's like a survey of the entire landscape. For a first book, I personally like getting a single guided tour so that I feel like I'm going somewhere and not just looking at everything from a distance.
That is if every company that is in the chain follows those strict data protection laws.
It wouldn't be the first time that bad actors exploited legally protected browsing.
Disagree, I was the not in the "in crowd" with my boss at a previous location and yet I was the person (as suggested) in regards to everything backend related.
I share this feeling. Going to python for the first time as someone that has developed software for 16+ years was incredibly more difficult and time consuming than I would have hoped. I still don't understand how it has become the default go to language for teaching new coders when it has quite unintuitive syntax / packages and setup steps.
Get into a startup where a lot of these practices/ideas aren't yet fully ingrained/adhered to and grow with your team. This will also let you learn more skills than "just coding" as you will have to wear multiple hats.
Once you are confident you can move on to bigger engineering shops. Or just stay and have a great time building new things in startup world. :)
For what it's worth, that's also what I do. But is it optimal? :)
The source code is leading the blog posts [1], so I think I already have an answer to that question for games on 2x2 and 3x3 boards using Markov Decision Processes, but the approach doesn't scale to the 4x4 board.
