Sandy

Nothing I can write here would do this novel justice. Go read it yourself; it'll be worth it. I promise.

Terse. Maybe too terse, but a lot of my issues would have been resolved had I realized there was an appendix of notation at the back of the book. Serves as a pretty solid introduction to category theory, but provides absolutely no indication as to why one might want to know category theory. The treatment is primarily for organizing ones thoughts about abstract structures rather than actually working with them. The book very briefly mentions representability, with no discussion of the Yoneda lemma (which I understand to be one of the more useful parts of category theory).

I read this as part of MIRI's recommended reading list.

A lot of this book is about how to identify if you are pessimistic, or if your children are depressed (despite the fact the author says it's impossible for children to be depressed). It's a lot of filler with not much actionable or theoretical content.

This book has an ironically low signal to noise ratio. It's far too long for its insight density and is unbelievably Ameri-centric. If you know any math, or have read LessWrong you'll get much out of this book.

Disclaimer: I only read 30% of this book, but found I was completely incapable of keeping going. It's a light and fluffy pop-sci approach to the history of language, which panders easy realizations (of course language is evolving – it doesn't take three chapters to grab this concept) and straw-mans just-so theories in an attempt to sound more convincing (I really, really hope they are straw-men). In the third of the book I read, I did not find a single takeaway. If you're looking for an interesting book on language, look elsewhere.

Short and sweet. It's a beautifully inspirational account of what a love of math and physics feels like, on the inside. Highly recommended to anyone who doesn't feel warm and fuzzy about math or physics.

I'm very conflicted about this book. in the abstract, it's a fascinating study of human cognitive evolution as a continuous function – though of its accuracy I'm not entirely convinced. In hindsight, it appears to explain a huge number of phenomena from my past relationships which at the time I considered almost inherently mystifying – however, the strength of a theory is not how well it fits the past, but how well it predicts the future.

Unfortunately, Kegan seems almost enamored with Freud, and attempts to fit as many of his own models to agree with Freud's. Kegan's lack of skepticism in this regard strikes me as ominous; I can only wonder how much skepticism he has applied to his own models. While this not an explicit reason to disbelieve Kegan's theory of cognitive development, it is certainly sets off loud alarms. Most of the book's arguments come anecdotally, with a startlingly small sample size – the majority of the book focuses on only three individuals, though Kegan says the theory itself is derived from “interviews with over 40 patients”. Perhaps most damningly, the book relies far too heavily on large, incomprehensible tables spanning multiple pages with no visible signs of organization.

Though he does not formalize it as such, Kegan's theory seems to implicitly model human cognitive as a continuous oscillatory function, mapping from time to an axis of ego-differentiation/integration. Kegan states that these are opposite sides of the same coin, and strongly suggests that the ideal balance is the equilibrium between the two. The book offers some actionable advice on how to inspire transition between the cognitive stages, and how to notice the transition when it occurs. Furthermore, it suggests the reason that we are sometimes completely unable to see others' arguments is that they are aimed at a level we are not able to comprehend, let alone appreciate.

The final section of the book consists of advice for psychologists; it is entirely skippable for those of use who are not professional psychologists, and, though I am not an expert in the field, I would suspect it is indeed skipple for everyone entirely.

In conclusion: if you're interested in this book, read the Wikipedia page instead. You'll save yourself a lot of time and headache.

If you're familiar with x-risk, there isn't a lot for you in this book, except perhaps a better understanding of just how risky x-risk can be. For the uninitiated, however, I would wholeheartedly recommend this book to you – it briefly chronicles what likely may be humanity's most important (and last, one way or another) achievement, and how terrible it will be if we get it wrong.

Here are the particular passages I underlined while reading through Superintelligence:
http://sandymaguire.me/books/nick-bostrom-superintelligence.html

One of the more comprehensible textbooks I've ever read. I haven't experienced other introductory quantum books, but this is not a bad place to start.

There is no math in this book. Why is there no math in this book!?

I found this book to be a little duplicitous, in that I absolutely adored the first 60% and uncontrollably hated the second half. The first half focuses on the very strong and well-argued thesis that humans live by metaphor, and indeed that metaphor is our only means of understanding abstract, non-directly-experiential concepts. It's repetitive at times, but not distractingly so.

The second half, however, is where everything falls apart. The authors ironically fail to notice their mind-projection of human-understanding-as-metaphor to the external world, and spend the remainder of the book arguing that because humans experience the universe through metaphor that there can be no absolute truth in the universe. It's nice that Lakoff and Johnson are arguing against the contemporary philosophical stance on this, and, while they get some things right, they're significantly further off-course than the Bayesians on the same subject matter.

Perhaps more heinously, the authors spend a good deal of the second half of the book arguing with straw-man objectivists in an attempt to drive home their conclusions, at one point quoting philosophers as far back as Plato to argue their claims (despite the fact that one of their central arguments is that western philosophy is impossibly flawed as it stands). It's a terribly disappointing end to an otherwise fantastic book.

If I had the ability, I'd rate this 3.5 stars, but alas, I do not.

I read about 20% of this book before putting it down. It's too light and fluffy for my liking, and (in the part I read, at least) focuses significantly more on things we know now to be incorrect (eg. phrenology) than on anything else.

Had some fascinating insights into social mobility (there's not a lot of it, and that is maybe a good thing), but the best part of the book to me was that it was a case study in good experiment design.

I wouldn't recommend it, but if you are going to anyway, you can skim it – the conclusions keep being the same.

I got this on the suggestion of Malcolm Ocean (http://malcolmocean.com/), and it is probably the most inspiring thing I have ever read. Marshall first describes the loneliness of greatness in such haunting terms that I was brought to tears, but stays determined that this is indeed a worthwhile cause. The rest of the book is fantastically good advice about how to do just that.

Yes, as other reviews have said, the editing is sloppy, and often times there is is extensive amounts of the same information entirely copied and pasted, but the information contained in this book more than makes up for it. Give it a try, and push through. You won't regret it.

I think I preferred Skiena's Algorithm Design Manual as a refresher on algorithms/interview prep, but this book is also very good (and easier to find!). Let's see if it gets me the job!

I stopped reading around 40%. Being a math major, it wasn't providing enough insight-density to warrant further reading. Others with less math experience would likely get a lot out of it, however.

I'm very critical of philosophy in general, but Dennett seems to be one of the few philosophers doing it (mostly) right. The book consists of a vast collection of small thinking tools for sousing out comprehension from complex concepts – most of them are silly, but it's likely beneficial to skim through the first half of the book to see if any of them work for you.

What I found most fascinating, however, were the last few chapters. One was on “what is it like to be a philosopher” (apparently very circle-jerky; no big surprises there), and the other on “use the [thinking] tools; try harder” which is a good call to action for finding a use for critical thinking in ways which turn out to actually be useful.

I'd recommend this book to people with philosophical inklings but who distrust the field, and then I'd tell them to head over to lesswrong.com and see if any of it sticks. The rest of you – those on-board with Dennett and those with no interest in philosophy – stay away and go read Kahneman; it'll be a better use of your time.

This book had the interesting property of making me think bigger thoughts without making me think about any big thoughts in particular. There is notably no central theme, and large, seemingly inconsequential mathematical tangents, but it was a useful study in watching the author constantly generalize over concepts.

I can't say I enjoyed it, and I can't say I'd recommend it to anyone, but it definitely improved my understanding of computation. There are probably better and faster ways of doing that, but this is what I had to work with.

Super actionable book on how to better structure your university life. Lots of filler so you can read it in an hour or two, but definitely has enough useful concepts to be worth your time/money.

Fantastic introduction to game theory. I would highly recommend this book to everyone I've ever met.

Despite it's dismissal of using tactics over strategy, this book is essentially a book of tactics and mindsets. There is very little actionable advice (although the advice that is there IS good), especially for people who haven't actually written 5 books yet.

The end of the book makes a nod to talking about the actual mechanics behind which the authors were able to publish 1.5 million words in a year, and then falls completely short saying “oh actually we don't want this book to be any longer”. That's why I bought the book, you bastards.

Haskell reinvigorated my love for programming, lifting it up a meta-level and forcing me to reevaluate the way I look at the world.

Inspired me to start programming for fun again!

Helped identify /lots/ of potential failure modes for my one-day startup.

Unfortunately, not Godel Escher Bach 2.