Marginalia

Karen Brodkin examines how American Jews’ changing racial position reshaped Jewish identity, class, and belonging across generations.

She contrasts immigrant experiences of antisemitic exclusion with the postwar opportunities available to many Jews of European descent.

Her account links access to education, professional employment, and suburban housing to public policy and the unequal distribution of opportunity.

Moving between family history and social analysis, she distinguishes institutional racial assignment from the identities people make for themselves.

The discussion follows her arguments about race, class, gender, and the tensions between Jewish distinctiveness and acceptance into white America.

Author: Karen Brodkin

Source: How Jews Became White Folks and What That Says about Race in America · Karen Brodkin

Series: History & Judaism · Book deep dive

Explore: History & Judaism

Related episodes: Antisemitism, an American Tradition (Pamela S. Nadell) · German Jews: A Dual Identity (Paul Mendes-Flohr) · The Necessity of Exile (Shaul Magid): Essays from a Distance

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Ruth R. Wisse traces Jewish political life from the loss of ancient sovereignty through emancipation and the creation of Israel.

She examines how covenant, communal self-government, and accommodation sustained Jewish communities in the Diaspora.

Wisse argues that dependence on rulers’ protection left Jews vulnerable to political movements that profited from targeting them.

She follows the shift from religious hostility to modern political antisemitism and examines how demagogues turned Jewish success into conspiracy narratives.

The discussion closes with her argument that moral responsibility requires collective self-defense, including in the modern state of Israel.

Author: Ruth R. Wisse

Source: Jews and Power · Ruth R. Wisse

Series: History & Judaism · Book deep dive

Explore: History & Judaism

Related episodes: The Necessity of Exile (Shaul Magid): Essays from a Distance · Jew-Hatred: The Latest Edition (Simon Schama) · The Final Solution to the Jewish Question: A Love Story for the Living (Dara Horn)

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Shaul Magid reconsiders exile as a resource for Jewish life rather than a condition that political sovereignty simply ends.

Across nine essays, he examines liberal Zionism, American Jewish identity, communal belonging, and the boundaries of political dissent.

Drawing on Hannah Arendt, Martin Buber, Hasidic thinkers, and Yiddish literature, he develops his idea of counter-Zionism.

He asks how Jewish self-determination can coexist with Palestinian self-determination and critiques claims of exclusive ownership of the land.

The book distinguishes antisemitism from structural oppression and explores an exilic ethic of humility and coexistence, including within Israel.

Author: Shaul Magid

Source: The Necessity of Exile: Essays from a Distance · Shaul Magid

Series: History & Judaism · Book deep dive

Explore: History & Judaism

Related episodes: The Final Solution to the Jewish Question: A Love Story for the Living (Dara Horn) · Jew-Hatred: The Latest Edition (Simon Schama)

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Sandeep Prasada argues that commonsense concepts have a formal structure that guides how we think, speak and reason.

Conceptual Form distinguishes what we know about a category from the perspectives through which we understand its members.

The book develops an instance-of-kind perspective and examines how people reason about kinds, individuals and their properties.

It applies this account to generic statements, systematic polysemy and metaphor, connecting conceptual structure with language.

The later chapters consider how these perspectives are acquired and what they imply for theories of conceptual knowledge.

Author: Sandeep Prasada

Source: Conceptual Form: The Hidden Structure of Commonsense Concepts · Sandeep Prasada

Series: Mind & Psychology · Book deep dive

Explore: Mind & Psychology

Related episodes: How Children Learn the Meanings of Words (Paul Bloom) · Thought and Language (Lev Vygotsky)

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Chelsea Finn, Ian Goodfellow and Sergey Levine investigate how robots can learn the effects of physical interactions from unlabeled video.

Their action-conditioned models predict how pixels move between frames, reusing visual appearance rather than reconstructing every future image from scratch.

The paper introduces a dataset of 59,000 robot-pushing interactions and tests predictions on previously unseen objects.

Its experiments compare alternative motion-prediction architectures and examine their ability to produce plausible futures conditioned on a robot's actions.

This 2016 work provides an early foundation for robotic world models and connects visual prediction with the longer-term goal of planning through learned models.

Author: Chelsea Finn, Ian Goodfellow and Sergey Levine

Source: Unsupervised Learning for Physical Interaction through Video Prediction · Chelsea Finn, Ian Goodfellow and Sergey Levine

Series: Weekly AI Papers · Historical classic

Explore: AI & Computer Science · AI Papers

Related episodes: Backpropagation: Learning Representations by Back-Propagating Errors (Rumelhart, Hinton & Williams) · Robotics, Vision and Control (Peter Corke) — Part 3 of 5: Robot Manipulators

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Mateo Clémente and colleagues introduce La-JEPA, a compact robot policy trained in the feature space of a pretrained V-JEPA 2.1 video encoder.

The model learns to predict future visual features alongside actions during training, then generates actions alone when controlling the robot.

The authors evaluate it on LIBERO-Plus, RoboTwin 2.0 and four real-robot tasks, reporting strong results with smaller policies than several generation-based alternatives.

Their design study compares JEPA features with video-VAE latents and examines which forms of predictive supervision improve control.

The paper also identifies corrupted instructions in the released LIBERO-Plus evaluator and re-evaluates baselines under a corrected protocol.

Author: Mateo Clémente, George Z. Xue, Amin Abyaneh, Liheng Ma, Rui Heng Yang, Tongtong Cao, Zhanguang Zhang and Yingxue Zhang

Source: La-JEPA: Compact Robot Policies with Latent World Modeling · Mateo Clémente, George Z. Xue, Amin Abyaneh, Liheng Ma, Rui Heng Yang, Tongtong Cao, Zhanguang Zhang and Yingxue Zhang

Series: Weekly AI Papers · Recent research

Explore: AI & Computer Science · AI Papers

Related episodes: Yann LeCun & Randall Balestriero: The Platonic Representation Hypothesis with JEPAs · Robotics, Vision and Control (Peter Corke) — Part 5 of 5: Vision-Based Control

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The final part connects the series’ robotics and vision foundations through vision-based control.

Position-based visual servoing uses estimated spatial quantities, while image-based visual servoing acts on errors measured in image features.

The interaction matrix links motion to changes in the image, making the choice of features, depth estimates and camera model consequential.

Advanced methods include partitioned, polar-coordinate and spherical-camera approaches to visual servoing.

Applications to robot arms, mobile robots and aerial robots close the perception-to-action loop and expose the assumptions and performance limits of the methods.

Author: Peter Corke

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

Series: Robotics, Vision and Control — Part 5 of 5 · Vision-Based Control

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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Part 4 follows the book’s five computer-vision chapters, from the physical properties of light to information recovered from multiple images.

Light, color and image-processing operations explain how measurements become usable digital representations.

Region, line and point features provide ways to describe structures and establish correspondences in images.

Camera models and calibration relate image measurements to the geometry of the world.

Multiple-view geometry and stereo methods show how relationships between images reveal depth, structure and motion, preparing the transition to visual feedback control.

Author: Peter Corke

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

Series: Robotics, Vision and Control — Part 4 of 5 · Computer Vision

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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Part 3 turns from moving a robot’s base to controlling the motion of a robot arm.

Forward and inverse kinematics connect joint configurations with the position and orientation of the end effector.

The manipulator Jacobian relates joint velocity to task-space motion and reveals the significance of singularities and manipulability.

Dynamics adds mass, inertia and the forces or torques required to produce a desired movement.

Corke’s control methods connect these models with the practical problem of making an arm follow a commanded motion.

Author: Peter Corke

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

Series: Robotics, Vision and Control — Part 3 of 5 · Robot Manipulators

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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Part 2 follows Corke’s treatment of mobile robots, navigation, localization and mapping.

Vehicle models explain how wheeled and aerial robots can move, and which motions their physical constraints permit.

Reactive behavior and map-based path planning offer different ways to reach a destination while handling obstacles.

Odometry and probabilistic localization address the uncertainty in a robot’s estimate of where it is.

Mapping and SLAM bring motion, measurements and environmental structure together, showing why navigation depends on both geometry and reliable estimation.

Author: Peter Corke

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

Series: Robotics, Vision and Control — Part 2 of 5 · Mobile Robotics

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)

Got something to say to this podcast? Send a voicemail, and you might hear yourself on the next episode!