Getting into artificial intelligence again

At work, I was learning Rust, but now I want to start the journey yet again of learning machine learning and artificial intelligence. How will I do that?

My boss has recommended two books:

• The Alignment Problem by Brian Christian (who also co-authored “Algorithms to Live By”). This book is great because it provides a philosophical overview of the problems present with artificial intelligence and machine learning models — hence the title of the book, “The Alignment Problem”. Some examples include using the algorithm in the judicial system in which the data that is used to train, which has an implicit bias, is mimicked too by that algorithm's decision.

• Deep Learning in Python by François Chollet is another book that dives into the weeds of deep learning, a subset of machine learning and artificial intelligence (AI). The book provides a history of AI (I wish there was something similar for web development). Chollet has a nice paragraph in the book. I’ll paraphrase it: don’t worry about the hype in AI. AI has gone through many “winters” followed by much excitement — appealing to a long-term approach to studying AI.

Over a year ago, I wrote an article about AI and optometry, but the landscape has changed vastly since then.

What am I consuming?

• “Black and White” (2002) directed by Craig Lahiff is about the story of Max Stuart and the injustices faced by Aboriginals in the late 50s in Australia. Based on a true story as well.

• “October Sky” directed by Joe Johnston, follows the life of Homer H. Hickman Jr. Living in a small coal mining town, he decides to build a rocket in his backyard after being inspired by the Soviet’s successful launch of Sputnik 1. It goes to show where you are from doesn’t matter. You can still achieve greatness.

Thanks for reading, I hope you have a good week ahead.

Stay focused,

Shivan