Marginalia

Felipe C.
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Marginalia brings books and research into conversations about how we think, speak, remember, and live together. Explore philosophy, artificial intelligence, linguistics, psychology, history, art, and science through the ideas and questions in the source texts. Listen to learn, question what you hear, and take the debate further. Browse seven subject collections, including separate AI Books and AI Papers series. AI Papers connects recent research with historically significant work. Philosophy & Critical Theory: Ricoeur, Adorno, truth, interpretation, and ethics.AI & Computer Science: Learning, world models, and the ideas behind intelligent machines.Language & Linguistics: How language works, develops, and evolves.Mind & Psychology: Consciousness, cognition, development, and human behavior.History & Judaism: Jewish history, memory, and how we understand the past.Art & Music: Aesthetics, creativity, and ways of listening.Mathematics & Science: Mathematical ideas, scientific reasoning, and how we establish knowledge.Human-curated, with conversations produced using NotebookLM. Explore the episodes and their source references at the podcast library. felipecasadei.ai

  1. 3d ago

    Conceptual Form (Sandeep Prasada): The Hidden Structure of Commonsense Concepts

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

    Conceptual Form (Sandeep Prasada): The Hidden Structure of Commonsense Concepts

  2. 3d ago

    Unsupervised Learning for Physical Interaction through Video Prediction (Chelsea Finn, Ian Goodfellow & Sergey Levine)

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

    Unsupervised Learning for Physical Interaction through Video Prediction (Chelsea Finn, Ian Goodfellow & Sergey Levine)

  3. 3d ago

    La-JEPA: Compact Robot Policies with Latent World Modeling (Mateo Clémente et al.)

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

    La-JEPA: Compact Robot Policies with Latent World Modeling (Mateo Clémente et al.)

  4. 5d ago

    Robotics, Vision and Control (Peter Corke) — Part 5 of 5: Vision-Based Control

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

    Robotics, Vision and Control (Peter Corke) — Part 5 of 5: Vision-Based Control

  5. 5d ago

    Robotics, Vision and Control (Peter Corke) — Part 4 of 5: Computer Vision

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

    Robotics, Vision and Control (Peter Corke) — Part 4 of 5: Computer Vision

  6. 5d ago

    Robotics, Vision and Control (Peter Corke) — Part 3 of 5: Robot Manipulators

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

    Robotics, Vision and Control (Peter Corke) — Part 3 of 5: Robot Manipulators

  7. 5d ago

    Robotics, Vision and Control (Peter Corke) — Part 2 of 5: Mobile Robotics

    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!

    Robotics, Vision and Control (Peter Corke) — Part 2 of 5: Mobile Robotics

  8. 5d ago

    Robotics, Vision and Control (Peter Corke) — Part 1 of 5: Introduction and Foundations

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

    Robotics, Vision and Control (Peter Corke) — Part 1 of 5: Introduction and Foundations
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About

Marginalia brings books and research into conversations about how we think, speak, remember, and live together. Explore philosophy, artificial intelligence, linguistics, psychology, history, art, and science through the ideas and questions in the source texts. Listen to learn, question what you hear, and take the debate further. Browse seven subject collections, including separate AI Books and AI Papers series. AI Papers connects recent research with historically significant work. Philosophy & Critical Theory: Ricoeur, Adorno, truth, interpretation, and ethics.AI & Computer Science: Learning, world models, and the ideas behind intelligent machines.Language & Linguistics: How language works, develops, and evolves.Mind & Psychology: Consciousness, cognition, development, and human behavior.History & Judaism: Jewish history, memory, and how we understand the past.Art & Music: Aesthetics, creativity, and ways of listening.Mathematics & Science: Mathematical ideas, scientific reasoning, and how we establish knowledge.Human-curated, with conversations produced using NotebookLM. Explore the episodes and their source references at the podcast library. felipecasadei.ai

Information

  • Creator
    Felipe C.
  • Years Active
    2025 - 2026
  • Episodes
    101
  • Rating
    Explicit
  • Copyright
    © FC2026
  • Show Website
    Marginalia

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