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* Fooled By Randomness (NN Taleb): Taleb is a complicated personality, but this book gave me a heuristic for thinking about long-tails and uncertain events that
by wenc 5y ago
* Fooled By Randomness (NN Taleb): Taleb is a complicated personality, but this book gave me a heuristic for thinking about long-tails and uncertain events that I could never have derived myself from a probability textbook.
* Designing Data Intensive Applications (M Kleppmann): Provided a first-principles approach for thinking about the design of modern large-scale data infrastructure. It's not just about assembling different technologies -- there are principles behind how data moves and transforms that transcend current technology, and DDIA is an articulation of those principles. After reading this, I began to notice general patterns in data infrastructure, which helped me quickly grasp how new technologies worked. (most are variations on the same principles)
* Introduction to Statistical Learning (James et al) and Applied Predictive Modeling (Kuhn et al). These two books gave me a grand sweep of predictive modeling methods pre-deep learning, methods which continue to be useful and applicable to a wider variety of problem contexts than AI/Deep Learning. (neural networks aren't appropriate for huge classes of problems)
* High Output Management (A Grove): oft-recommended book by former Intel CEO Andy Grove on how middle management in large corporations actually works, from promotions to meetings (as a unit of work). This was my guide to interpreting my experiences when I joined a large corporation and boy was it accurate. It gave me a language and a framework for thinking about what was happening around me. I heard this was 1 of 2 books Tobi Luetke read to understand management when he went from being a technical person to CEO of Shopify. (the other book being Cialdini's Influence). Hard Things about Hard Things (B Horowitz) is a different take that is also worth a read to understand the hidden--but intentional--managerial design of a modern tech company. These some of the very few books written by practitioners--rather than management gurus--that I've found to track pretty closely with my own real life experiences.
- TheFreim 5y agoFooled By Randomness was a really great book, I second your suggestion.
- llaolleh 5y agoHigh Output Management was an interesting read. Grove took timeless computer architecture techniques and mapped it onto management.
- deleted 5y ago[deleted]
- reactspa 5y ago>gave me a heuristic for thinking about long-tails and uncertain events If it's possible to summarize and share the heuristic in this forum format, I request you to please do. Am always learning from Taleb's books and ideas.
- wenc 5y agoI'm hard pressed to summarize the book because it introduces so many ideas. Perhaps I can point you to summaries other folks have written, like [1]. That said, I can rattle off some heuristics from Taleb that I've applied in real life: 1) Look out for fat tails and rare events in real life. Don't obsess over trying to predict them (you cannot -- rare events are such that they are inherently difficult to predict. They're rare!); instead protect yourself against their downsides by designing the appropriate defenses for when they do happen (e.g. having some form of insurance, setting up legal clauses that limit liability, etc.) For instance, contracts can be set up to limit liability from very rare events that have damages that scale infinitely. This can be done by adding a clause that says if said rare event happens, one will only pay damages up to $x, which contains the downside. (Insurance companies do this a lot) 2) When to take risks? In situations where there are low downsides if you're wrong and high upside if you're right. When to not take risks? When the opposite is true. 3) Don't mistake individual risk for systems risk. The startup community valorizes risk-taking (after all, nothing ventured nothing gained). However never fall into the trap into thinking that risk-taking makes everyone stronger. When individuals fail, they don't always get stronger (many are destroyed) -- instead their failures make the system/ecosystem stronger. It's like airplane crashes, which are themselves unrecoverable failures. But each airplane crash actually improves airline safety for everyone through learnings obtained from post-mortems and blackboxes, which lead to new FAA guidelines. 4) Don't obsess over probabilities alone -- pay attention to payoffs (or better yet, focus on "expectation", which is the sum/integral of probabilities times payoffs). (everybody learns this in statistics class but no one has thought about how to apply this). You want to maximize expectation, not probability. [1] https://tylerdevries.com/book-summaries/fooled-by-randomness/ https://tylerdevries.com/book-summaries/fooled-by-randomness...
- reactspa 5y ago
- LarryEt 5y agoWonderful. I am such a Taleb fan boy but have been putting off Designing Data Intensive Applications. I am starting on it this afternoon from this post. I just started on Daniel Kahneman's Noise. It will be disappointing if it isn't one of these type of books.
- cweill 5y agoI'm also a huge Taleb fan. However for a first book, I'd recommend his Antifragile book instead since it was written 10 years later in his career and further explores the ideas addressed in Fooled by Randomness with the benefit of more hindsight and discussion with peers in the field. For anyone interested, I discuss the key takeaways from Antifragile, specifically for software engineers in https://youtu.be/jP6UQPSAk58 https://youtu.be/jP6UQPSAk58.