Marginalia

The first part introduces Peter Corke’s Robotics, Vision and Control and the questions that connect sensing, geometry and action.

Chapter 1 places mobile robots, robot arms and robotic vision in context, including the ethical responsibilities of building autonomous systems.

Chapter 2 develops coordinate frames, relative pose and the representations used to describe position and orientation in two and three dimensions.

Chapter 3 connects those geometric descriptions with velocity, acceleration, forces and smooth trajectories through time.

Inertial sensing and sensor fusion show how these foundations support a robot’s estimates of its own motion, preparing the ground for mobile robotics.

Author: Peter Corke

Source: Robotics, Vision and Control: Fundamental Algorithms in Python, third edition (2023) · Peter Corke

Series: Robotics, Vision and Control — Part 1 of 5 · Introduction and Foundations

Explore: AI & Computer Science · AI Books

Related episodes: How the Body Shapes the Way We Think: A New View of Intelligence (Pfeifer & Bongard) · Structure and Interpretation of Computer Programs (Harold Abelson & Gerald Jay Sussman) · Lie Groups, Lie Algebras, and Representations (Brian Hall)

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Pamela S. Nadell traces the persistence of antisemitism in America from the arrival of Jews in New Amsterdam in 1654 to contemporary attacks.

The book follows religious hostility, political discrimination and social exclusion through successive periods of American history.

It examines barriers to citizenship, education and employment alongside propaganda, conspiracy thinking and violence.

Nadell also follows Jewish responses to prejudice and the tension between lived discrimination and America’s promise of religious liberty.

Her history asks how antisemitism has endured and adapted within a country often understood as a refuge from persecution.

Author: Pamela S. Nadell

Source: Antisemitism, an American Tradition · Pamela S. Nadell

Series: History & Judaism

Explore: History & Judaism

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Leovino Madriaga Garcia reads Paul Ricoeur’s early philosophy through the relationship between responsibility and hope.

The book follows Freedom and Nature, Fallible Man and The Symbolism of Evil to examine willing, human limitation and the acknowledgment of fault.

Garcia explains how phenomenology and the interpretation of symbols offer different approaches to understanding human action.

He then connects these concerns with Ricoeur’s early essays on civilization, Christian social responsibility, politics and the state.

The central question is how an honest account of human fallibility can sustain responsible action and hope for change.

Author: Leovino Madriaga Garcia

Source: Ricoeur’s Early Ethical Philosophy: Explorations of Responsibility and Hope · Leovino Madriaga Garcia

Series: Philosophy & Critical Theory

Explore: Philosophy & Critical Theory

Related episodes: Memory, History, Forgetting (Paul Ricoeur): Memory and Historical Truth · Time and Narrative (Paul Ricoeur): How Stories Shape Time

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Paul Ricoeur asks how we understand ourselves as persons who speak, act, tell stories and answer for what they do.

Oneself as Another distinguishes sameness from selfhood, showing why personal identity involves more than remaining unchanged.

Its ten studies connect language and agency with narrative identity, promising and relationships with other people.

Ricoeur brings the aim of a good life into conversation with moral obligations, just institutions and practical wisdom.

The book examines how responsibility and our dependence on others shape what it means to be a self.

Author: Paul Ricoeur

Source: Oneself as Another · Paul Ricoeur

Series: Philosophy & Critical Theory

Explore: Philosophy & Critical Theory

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Simon Schama asks why antisemitism persists and adapts across different political and religious settings.

Jew-Hatred: The Latest Edition, published in Jewish Quarterly 265, connects recurring historical myths with contemporary hostility toward Jews.

His essay examines religious prejudice, conspiracy thinking, and the repeated use of Jews as an explanation for wider social anxieties.

Schama also considers the October 7 attacks, the war in Gaza, and arguments about Zionism within the current resurgence of antisemitism.

The discussion centers on historical evidence, collective blame, and the consequences of these arguments for Jewish life and public debate.

Author: Simon Schama

Source: Jew-Hatred: The Latest Edition — Jewish Quarterly 265 (October 2026) · Simon Schama

Series: History & Judaism · Jewish Quarterly essay

Explore: History & Judaism

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What assumptions about speaking and listening are built into a machine that claims to understand a voice?

Edward B. Kang investigates how artificial intelligence turns voices into measurable, comparable, and reproducible signals.

The book moves from the histories and framing of voice to machine listening, engineered emotion, and synthetic speech.

Kang connects these technical practices with the economic, social, and cultural forces that shape what a system recognizes.

His concept of the machine voice opens a debate about whose voices count, which standards guide listening, and how technology changes our understanding of human expression.

Source: Machine Voices: A Sonic Study of Artificial Intelligence · Edward B. Kang

Series: Art & Music · AI Books · Book deep dive

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What kind of architecture could support a mind across different tasks and situations?

Paul S. Rosenbloom examines architectures, symbols, intelligence, and theories through decades of research in artificial intelligence and cognitive science.

He maps the choices and trade-offs behind symbolic, neural, and hybrid approaches to intelligent systems.

His account connects work on XAPS, Soar, and Sigma with the search for a Common Model of Cognition.

The book combines conceptual analysis with a research memoir, asking how the fixed organization of a system can make flexible thought possible.

Source: On Minds: Reflections of a Cognitive Architect · Paul S. Rosenbloom

Series: AI Books · Book deep dive

Explore: AI & Computer Science · AI Books

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CLIP asks whether natural-language descriptions can teach a visual model more flexibly than a fixed set of class labels.

Radford and colleagues train image and text encoders on 400 million image-text pairs using a contrastive objective.

Text prompts then describe new categories, allowing the model to attempt classification without task-specific labeled training examples.

The paper evaluates transfer across more than 30 vision datasets and examines robustness, prompting, and the limits of the approach.

This foundational study provides a historical counterpart to the JEPA paper: paired contrastive training offers one route to shared visual and linguistic representations.

Authors: Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever

Source: Learning Transferable Visual Models From Natural Language Supervision · Alec Radford, Jong Wook Kim, Chris Hallacy and colleagues

Series: Weekly AI Papers · Historical classic

Explore: AI & Computer Science · AI Papers

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Can models trained separately on images and language arrive at the same representation of the world?

Randall Balestriero and Yann LeCun derive alignment up to a rotation for an idealized JEPA setting with shared positive pairs and additional assumptions.

They distinguish good views of the same scene from views that preserve the peculiarities of a single observation.

Experiments report stronger cross-modal alignment and substantially greater sample efficiency than next-token prediction in the tested settings.

The results concern cross-modal alignment under specific assumptions and benchmarks, making their scope central to interpreting the broader claims.

Authors: Randall Balestriero and Yann LeCun

Source: Proving and Improving the Platonic Representation Hypothesis with JEPAs · Randall Balestriero and Yann LeCun

Series: Weekly AI Papers · Recent research

Explore: AI & Computer Science · AI Papers

Related episodes: Yann LeCun’s World Models and V-JEPA: Learning from Video · Backpropagation: Learning Representations by Back-Propagating Errors (Rumelhart, Hinton & Williams) · VisionHOPE: Visual Backbones as Self-Modifying Learning Systems

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Sofien Kaabar explains how to build Python models for financial time series, combining machine learning with technical and quantitative analysis.

The book develops the probability, statistics, linear algebra, and data-handling foundations needed for these models.

It progresses from regression and tree-based methods to neural networks, recurrent architectures, and deep reinforcement learning.

Backtesting, time-series cross-validation, regularization, and retraining help examine model performance and the risks of overfitting.

Market drivers, risk management, and behavioral biases place the modeling techniques within the wider practice of financial trading.

Series: AI Books · Book deep dive

Book: Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python by Sofien Kaabar.

Source: O’Reilly Media · January 2024 · ISBN 9781098148393. Author’s code repository.

Explore: AI & Computer Science · AI Books · AI Papers

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