My Review of "The Tree" by Percival Everett

The Trees by Percival Everett
My rating: 5 of 5 stars

This was a fun read, it's part murder mystery part historical lesson about lynching in America, this book conveys a powerful message with a satirical tone (the joke's on the racists) that only Percival Everett can pull off.

I picked up this book on whim when I was at the bookstore, the first few pages caught my interest, and I finished it in one day. I laughed out loud, got angry, and made me a little more conscious. I'm 2 for 2 with this writer (I read James and really liked it too)


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My review of "Empire of AI" by Karen Hao

Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI by Karen Hao
My rating: 5 of 5 stars

This is a highly opinionated book that answers the following question:

- Why did Sam Altman get fired from OpenAI and then come back (long answer and not that exciting unless you're into corporate drama)
- How does OpenAI and big tech companies affect me, and how they affect the world?
- Should the power of AI and all that it entails be concentrated in the hands of very few people?

I gained a lot of insights into the way Silicon Valley tech dudes think about AI. I didn't know that there were two camps when it comes to thinking about General Artificial Intelligence (Doomers and Boomers) this was all very interesting to me. Fascinating. The chapters about power consumption and and what's going on in Chile and Uruguay are upsetting.

This book is well researched, one thing I'd say is not really focused on one thing per se, there's stuff about Altman's personal life, stuff about OpenAI and it's drama and stuff about the tech industry in general, these are all somewhat tied together, but besides all that, this is a must-read for everyone with a job that requires technical knowledge.

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My Review of "Why Machines Learn: The Elegant Math Behind Modern AI" on GoodReads

Why Machines Learn: The Elegant Math Behind Modern AI by Anil Ananthaswamy
My rating: 5 of 5 stars

This book gives an overview of the math that powers Deep Learning algorithms, I was goin to say high level, but that's not quite right. It goes into great depths, describing the concepts in lay terms. This book will give you an intuition for thinking about large language models (LLMs) like ChatGPT and such.
I love that the author gives clear explanations to complex topics. I really enjoyed getting the history and the people behind each discovery, the book goes in chronological order.
I have been studying and following AI since it was called "Pattern Recognition" in grad school, I took courses on "Machine Learning" at the University of Washington about 10 years ago, right around the time Deep Nets were stating to gain traction. I was starting to think I was not going to get anything new from this book but the last chapter of the book covers what's been happening since 2020 and it made me change my mind about this field. I don't want to "spoil" it, but I didn't know about that fact that Neural Networks are going past the theoretical bias/variance "Goldilocks" limit. Reading about that made me take another look at the tech. Like I said, I've been skeptical about NN and the "hype" of AI, but reading about this made me want to know more.

Excellent Read


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