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For readers exploring computing, mathematics, model interpretation, minds, and AI safety through researchers’ recommendations. These five editorial starting choices are not a technical curriculum or a reading order endorsed by the recommenders.
Editorial starting points from From The Greats. Level, prerequisites, learning goals and reading order are our guidance, not statements attributed to the recommenders. Inspect their actual recommendation evidence below.
Editorial guidance
Explore how programs express ideas through a recommendation from Peter Norvig.
Level: Computing foundations
Prerequisites: Editorial suggestion: some programming experience and comfort with symbolic expressions.
Learning goal: Develop a deeper understanding of abstraction and the structure of computer programs.
Caveats: A classic computing text rather than a modern machine-learning or LLM implementation guide. Norvig’s recommendation does not endorse this editorial sequence.
Recommended by Peter Norvig — recommendation evidence.
Open the bookEditorial guidance
Refresh mathematical foundations through Pieter Abbeel’s recommendation.
Level: Mathematical prerequisites
Prerequisites: Editorial suggestion: some prior algebra and calculus; use additional explanations and exercises when needed.
Learning goal: Connect linear algebra, calculus, probability, and optimization to machine-learning methods.
Caveats: The recommendation is an undated author-hosted endorsement of the 2020 work. It does not establish endorsement of every later online PDF revision.
Recommended by Pieter Abbeel — recommendation evidence.
Open the bookEditorial guidance
Explore how models and predictions can be explained through Sebastian Raschka’s review.
Level: Model interpretation
Prerequisites: Editorial suggestion: familiarity with supervised learning and common predictive models.
Learning goal: Compare approaches to interpreting models and their predictions.
Caveats: Raschka’s review dates to August 2020 and concerns the print and online versions available then. The online book continues to change; the review does not endorse every later revision.
Recommended by Sebastian Raschka — recommendation evidence.
Open the bookEditorial guidance
Explore formal systems, minds, and computation through a recommendation from Demis Hassabis.
Level: Conceptual exploration
Prerequisites: Editorial suggestion: curiosity about logic and computation; no model-training setup is needed.
Learning goal: Explore connections between formal systems, self-reference, and ideas about intelligence.
Caveats: A cross-disciplinary conceptual book rather than a machine-learning textbook. Its place here is an editorial starting choice, not evidence of a technical learning sequence.
Recommended by Demis Hassabis — recommendation evidence.
Open the bookEditorial guidance
Explore arguments about beneficial AI through Yoshua Bengio’s recommendation.
Level: AI safety context
Prerequisites: Editorial suggestion: no programming prerequisite; familiarity with basic AI ideas may help.
Learning goal: Examine Stuart Russell’s arguments about AI objectives, human preferences, and safety.
Caveats: Bengio’s recommendation is an undated publisher-hosted endorsement. This is conceptual AI safety reading, not a coding tutorial or a complete account of current AI research.
Recommended by Yoshua Bengio — recommendation evidence.
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From The Greats
