October books included a comprehensive overview of machine learning, a novel about an epic 1980s racer, and a dystopian American future after a second civil war.
The Alignment Problem — I loved Brian Christian’s survey of Machine Learning. He blends computer science with philosophical and political considerations in a way that, frankly, made me jealous. Also a bit of a thrill for me that some of the people he interviewed are people I knew when I was in grad school at University of Alberta — the professors, of course, but also my former office mate. A strong, five-star recommendation for anyone who wants to understand machine learning and how it can shape our world.
Malibu Rising — This was a book club selection. There are sort of two stories going on here: one is this epic rager of a 1980s Malibu party, and the other was the story of a family across two generations. I really enjoyed the family story and didn’t much care for the party story. On the whole, I didn’t like this book as much as Jenkins Reid’s earlier novel Daisy Jones and the Six.
American War — In this book, Omar El Akkad has a richly-imagined dystopian near-future, where America is ravaged both by climate change and a still-simmering second American civil war. It’s an amazing premise, and El Akkad makes it so believable, but for me, the story didn’t quite live up to the premise. We end up following one character over a period of years, which ends up giving us a narrow perspective on the world he’s created. That’s the same choice you see in, say, The Handmaid’s Tale, or Never Let Me Go, but for some reason this book left me with the feeling that something was missing. There were things I wanted to see and understand, and it was unsatisfying to have so many of those questions unanswered.