Dratsi Pod

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 a...

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...

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...

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 co...

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 ec...

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...

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 transf...

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 cro...

Got something to say to this podcast? Send a voicemail, and you might hear yourself on the next episode! Series: AI Books · Book deep dive Book: Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python by Sofien Kaabar. Sofien Kaabar explains how to build Python models for financial time series, combining machine learning with technical and quantitative analysis...

Got something to say to this podcast? Send a voicemail, and you might hear yourself on the next episode! Series: AI Books · Book deep dive Rolf Pfeifer and Josh Bongard argue that intelligence emerges through interactions among the brain, the body, and the environment. Robot experiments show how physical form and sensory-motor coordination can contribute to behavior that otherwise appears to requi...

Got something to say to this podcast? Send a voicemail, and you might hear yourself on the next episode! Series: Weekly AI Papers · Recent research Any Time, Any Space tackles the problem of keeping generated video shots consistent across changes of place, viewpoint, and time. The framework turns a screenplay into shot requests with explicit scene, camera, and event-time references. Scene memory s...

Got something to say to this podcast? Send a voicemail, and you might hear yourself on the next episode! Series: Mathematics & Science Book: An Advanced Course in Probability and Stochastic Processes by Dirk P. Kroese and Zdravko I. Botev. Kroese and Botev build a rigorous account of probability from measurable spaces, integration, and random variables. They compare different forms of converge...

Got something to say to this podcast? Send a voicemail, and you might hear yourself on the next episode! Series: AI Books · Book deep dive Book: Human-in-the-Loop Machine Learning: Active Learning and Annotation for Human-Centered AI by Robert (Munro) Monarch. Robert Monarch explains how human judgment and machine learning can work together to build better models. Active learning uses uncertainty...

Series: History & Judaism Book: The Final Solution to the Jewish Question: A Love Story for the Living by Dara Horn. Dara Horn examines why antisemitism persists and why familiar responses often fail to confront it. She combines historical research, reporting, and personal experience to trace recurring myths about Jews. The book questions prevailing approaches to Holocaust education and examin...

Rumelhart, Hinton, and Williams explain how backpropagation trains hidden units to learn useful internal representations. A forward pass computes the network's outputs; a backward pass uses the chain rule to calculate how each weight contributes to the error. The weights are adjusted to reduce squared output error, with momentum helping the learning process converge. Experiments on mirror symmetry...

VisionHOPE explores how a vision model can change both its memory and its learning rules while processing an image. Its design connects five memories: content, keys, values, learning rate, and retention. The paper develops controls that keep these coupled updates stable under the conditions established by its analysis. Four directional scans adapt the method to the two-dimensional structure of ima...

A First Course in Causal Inference — Peng Ding Peng Ding introduces causal inference from a statistical perspective. The book explains the foundations needed to reason about causal effects rather than associations alone. Examples and applications draw on biostatistics and econometrics. Mathematical arguments are accompanied by exercises, data, and practical R code. The course assumes basic probabi...

Graph Theory (Diestel)

Syntactic Theory

Lie Groups

Jews of Lithuania

Cambridge History of Judaism 2 - The Hellenistic Age 1/2

Cambridge History of Judaism 2 - The Hellenistic Age 2/2

Cambridge History of Judaism 3 - The Early Roman Period 3/4

Cambridge History of Judaism 3 - The Early Roman Period 1/4