Oct 30, 202650 min
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...
About this Podcast:
Explore big questions through the books and papers behind them. Dratsi Pod brings you long, accessible deep dives that follow arguments chapter by chapter and concept by concept, explain difficult ideas, and show how they connect. Browse all episodes by subject, author, and book or paper , or choose a series: 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. AI Books : long deep dives into books and book chapters. AI Papers : paper deep dives, including our weekly recent-paper and historical-classic pair. The AI Papers series pairs recent research with historically significant papers, connecting today's questions to the foundations of the field. Human-curated and AI-produced with NotebookLM, these conversations are grounded in the source books and papers. Start with a subject you love, follow a connected series, or discover something new. Follow Dratsi Pod to keep exploring. felipecasadei.ai
Pitch Analysis
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Contact path
Verified email
Booking probability
34%
Guest openness
Selective
80/100
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What is Dratsi Pod about?
Explore big questions through the books and papers behind them. Dratsi Pod brings you long, accessible deep dives that follow arguments chapter by chapter and concept by concept, explain difficult ideas, and show how they connect. Browse all episodes by subject, author, and book or paper, or choose a series: Philosophy & Critical Theory: Ricoeur, Adorno, truth, interpretation, and ethics.
What has Dratsi Pod covered recently?
Recent episodes include "Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python (Sofien Kaabar)" (30 October 2026, 50 minutes), "How the Body Shapes the Way We Think: A New View of Intelligence (Pfeifer & Bongard)" (21 October 2026, 57 minutes), and "Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation" (21 October 2026, 47 minutes).
How often does Dratsi Pod publish?
Dratsi Pod publishes roughly daily, with episodes averaging 50 minutes.
How hard is it to get booked on Dratsi Pod?
Booking probability for Dratsi Pod is 34%, and the host is rated Selective on guests. Dratsi Pod requires a Pod Score of 80 or higher. Dratsi Pod's contact route on record: verified email.
Who should pitch Dratsi Pod?
The strongest fits for Dratsi Pod are Educational Support Services. Dratsi Pod has an arts audience.
About the host
Dratsi Pod is an arts podcast.
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Recent episodes
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.
Oct 21, 202657 minGot 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...
Oct 21, 202647 minGot 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...
Oct 21, 202653 minGot 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...
Oct 17, 20261h 8mGot 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...
View More
Oct 7, 202658 minS4Series: 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...
Oct 7, 202656 minRumelhart, 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...
Oct 7, 202637 minVisionHOPE 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...
Episode #57
First Course in Causal Inference (Peng Ding)
Oct 4, 202655 minS1A 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...
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