Podcast
Intellectually Curious
Hosted by Mike Breault · EN
Intellectually Curious is a podcast by Mike Breault featuring over 1,800 AI-powered explorations across science, mathematics, philosophy, and personal growth. Each short-form episode is generated, refined, and published with the help of large language models—turning curiosity into an ongoing audio encyclopedia. Designed for anyone who loves learning, it offers quick dives into everything from combinatorics and cryptography to systems thinking and psychology.
Inspiration for this podcast:
"Muad'Dib learned rapidly because his first training was in how to learn. And the first lesson of all was the basic trust that he could learn. It's shocking to find how many people do not believe they can learn, and how many more believe learning to be difficult. Muad'Dib knew that every experience carries its lesson."
― Frank Herbert, Dune
Note: These podcasts were made with NotebookLM. AI can make mistakes. Please double-check any critical information.
71episodes
Episodes
Newest firstAll episodes
Non-Euclidean Vision: The Curved Geometry Behind Color Perception
Yesterday00:05:37Tap to summarizeWe trace Schrödinger’s 3D color cone, the Bezold–Brücke effect, and the shift from cones to rods as light fades. Learn how Los Alamos researchers use curved, non-Euclidean geometry to map the shortest perceived paths for color, and how this changes the way displays, VR, and cognitive psychology understand human vision.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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Making Claude a Chemist
2d ago00:04:54Tap to summarizeAnthropic is enhancing Claude's chemistry proficiency by training it to interpret complex analytical data like NMR spectra. Recent tests demonstrate that the Opus 4.7 model performs as well as, or better than, specialized industry software when predicting how molecules react to magnetic fields. Beyond simple prediction, the AI successfully performs structure elucidation, a difficult task where it identifies unknown molecules based solely on experimental readings. This capability allows researchers to translate between various chemical representations, such as hand-drawn sketches and technical data, more efficiently than traditional tools. By automating these time-consuming analytical processes, the goal is to provide a versatile assistant that supports scientists in navigating massive chemical registries and complex synthetic workflows. While current evaluations are small in scale, they indicate that general-purpose AI is becoming a formidable tool for modern laboratory research.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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Multigres: A Scalable Operating System for Postgres
3d ago00:06:29Tap to summarizeMultigres is an open-source project designed to provide Vitess-grade scalability and high availability for Postgres databases. Recently released in its v0.1 alpha stage, it functions as a comprehensive management system that handles connection pooling, automatic failovers, and backup orchestration. The platform utilizes a specialized Kubernetes operator to simplify cluster deployment and uses a unique consensus protocol to ensure data integrity during hardware failures. Its sophisticated architecture includes a two-service pooling solution that transparently routes traffic while maintaining connection state without requiring manual mode selection.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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The Giant Space Umbrella
4d ago00:05:25Tap to summarizeCould a hybrid system—30–40 meter ground-based telescopes paired with a distant 99-meter starshade—finally enable direct imaging of Earth-like worlds? We dissect a wild proposal: a sunflower-shaped starshade occluding starlight in space, diffraction control that yields a deep shadow, and the real-time adaptive optics and AI that keep ground‑based optics razor‑sharp through Earth's atmosphere. If targets out to seven parsecs can yield an hour-long spectrum, we might detect oxygen and water on a nearby Earth twin—redefining how we search for life beyond our solar system.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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How Claude Reached 95% Analytics Accuracy
5d ago00:06:19Tap to summarizeWe dissect how Anthropic tackled data ambiguity, staleness, and retrieval chaos to automate the majority of business analytics with Claude. Anthropic's technical guide describes the development of an agentic analytics stack designed to automate business data insights using Claude. The strategy centers on overcoming three primary obstacles: conceptual ambiguity, data staleness, and retrieval failures. To ensure high accuracy, the framework prioritizes robust data foundations, a strictly enforced semantic layer, and specialized procedural skills that guide the AI's reasoning. The methodology also incorporates adversarial reviews and continuous offline evaluations to maintain the integrity of automated reports. Ultimately, this system allows data teams to shift their focus from repetitive queries to high-level strategic modeling.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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Microsoft AI: Launching the MAI Model Family
6d ago00:06:25Tap to summarizeMicrosoft AI has introduced seven new MAI models designed to handle diverse tasks such as complex reasoning, coding, and high-fidelity media generation. These specialized tools, including MAI-Thinking-1 and MAI-Code-1-Flash, emphasize efficiency and are built using proprietary infrastructure and clean data. A major highlight is the introduction of Frontier Tuning, which allows organizations to refine these models using their own private data for superior performance. The initiative also features a significant partnership with the Mayo Clinic to develop a custom AI model dedicated to advanced clinical reasoning and diagnostics. Ultimately, Microsoft aims to achieve Humanist Superintelligence, focusing on creating powerful systems that remain transparent and directed by human goals.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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Splink: Fast and Scalable Probabilistic Data Linkage Guide
1w ago00:05:46Tap to summarizeSplink is an open-source Python library designed for high-speed, probabilistic record linkage and data deduplication across various SQL backends like DuckDB, Spark, and Athena. Developed by the Ministry of Justice, it utilizes the Fellegi-Sunter model to identify and cluster matching records in large datasets without requiring unique identifiers or extensive training data. The provided documentation highlights Splink’s ability to scale to hundreds of millions of records while offering interactive visualizations for model diagnostics. Case studies from the UK government illustrate how the tool is productionized using modular pipelines and automated workflows to ensure consistency and auditability. These sources emphasize a design philosophy rooted in idempotency and observability, allowing organizations to manage complex entity resolution tasks reliably. Ultimately, the software serves as a versatile framework for data scientists to resolve identities and link disparate information systems efficiently.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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NVIDIA Cosmos 3: Foundations for Physical AI Reasoning and Action
1w ago00:05:53Tap to summarizeDive into NVIDIA’s Cosmos 3, an open, omni‑modal foundation model that treats physical action as a native modality. Rather than merely predicting video frames, Cosmos 3 reasons about physics and outputs precise trajectories and torques, enabling physics‑accurate simulations for real‑world scenarios. We unpack its mixture of transformers, edge‑to‑cloud compute tiers, and the Cosmos Coalition, and explore how robotics, autonomous driving, and smart infrastructure use it to pre‑test innovations and generate safe, edge‑case scenarios without risk.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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The Einstein Telescope: An Underground Xylophone for Gravitational Waves
1w ago00:06:25Tap to summarizeWe dive into the planned third‑generation gravitational‑wave detector—the Einstein Telescope. Buried deep underground to tame seismic noise, ET uses a ‘xylophone’ design: a cryogenic low‑frequency arm cooled to ~10–20 K and a room‑temperature high‑frequency arm powered by a massive 3 MW laser. We explore why depth matters, where ET might be built, and how this upgrade could boost sensitivity tenfold, turning a few detections per week into potentially millions per year and letting us hear back to redshift ~100—the era of the first stars. We’ll also investigate the data deluge, the rise of autonomous AI agents running the full analysis pipeline, and how they might spot new physics before humans. A journey from cosmic dawn to automated discovery. Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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Jupiter’s Grand Tack: Shaping the Early Solar System
1w ago00:05:18Tap to summarizeThe Grand tack hypothesis describes a period in the early Solar System when Jupiter and Saturn underwent significant orbital migration, moving toward the Sun before reversing direction. This theoretical movement, comparable to a sailboat tacking, likely dictated the final architecture of the inner planets by clearing away excess material. The model provides a solution for the Mars problem by explaining why the Red Planet remained so small compared to Earth. It also clarifies the structure of the asteroid belt, which contains a diverse mix of rocky and icy bodies scattered by the gas giants' passage. While the theory addresses the absence of super-Earths, critics point to potential issues regarding gas accretion and the specific gravitational resonances required for such a migration. Scientists continue to evaluate alternative models, such as pebble accretion or early instabilities, to explain these cosmic mysteries.Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.Sponsored by Embersilk LLC
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