The O'Reilly Data Show explores the opportunities and techniques driving big data and data science. Through interviews and analysis, we highlight the people putting data to work.

The O'Reilly Data Show Podcast

This brand-new unabridged audio book of The Fellowship of the Ring, the first part of J. R. R. Tolkien’s epic adventure, The Lord of the Rings, is read by the BAFTA award-winning actor, director and author, Andy Serkis. 

 In a sleepy village in the Shire, a young hobbit is entrusted with an immense task. He must make a perilous journey across Middle-earth to the Cracks of Doom, there to destroy the Ruling Ring of Power – the only thing that prevents the Dark Lord Sauron’s evil dominion.

Thus begins J. R. R. Tolkien’s classic tale of adventure, which continues in The Two Towers and The Return of the King.

The Fellowship of the Ring, By J. R. R. Tolkien, Read by Andy Serkis

Host Meg Wolitzer presents three works about women who defy the status quo and might therefore be perceived as “dangerous.”  In Margaret Atwood’s “Unpopular Gals,” fairy-tale archetypes reclaim their power. The reader is Ann Harada.  A boisterous and brilliant student threatens to upend the order of her high school in Shanteka Sigers’ “A Way with Bea,” performed by Pascale Armand.  And a Victorian-era wife fights for her sanity in Charlotte Perkins Gilman’s classic “The Yellow Wallpaper,” performed by Carrie Coon.  The show also includes commentary by the Egyptian-American journalist and activist Mona Eltahawy.

Dangerous Women

Daniel Nieto est activement recherché. Les enquêteurs ont identifié le Marseillais en cavale. Dans un geste désespéré, il donne un dernier rendez-vous à Giovanna Amati le 24 mai 1978...

Enlèvement à l’italienne
Rome. Fin des années 1970. Daniel Nieto, un braqueur marseillais, est en cavale dans l’Italie des années de plomb où le rapt est une véritable industrie. Il devient kidnappeur et enlève la fille d’un riche industriel du cinéma. Une relation contre-nature se noue entre l’otage et son geôlier. Elle sera fatale à ce dernier.

Une série documentaire de Marine Vlahovic
Enregistrements: Août 2020 à mai 2022 - Entretiens: Marine Vlahovic - Montage : Marine Vlahovic et Sara Monimart - Réalisation : Marine Vlahovic et Samuel Hirsch - Musique originale & mixage: Samuel Hirsch - Illustration : Zaven Najjar - Production : Arte Radio

Enlèvement à l'italienne (7/7): Nous nous sommes tant aimés

Obedear (Outro) [Prod. By ROME]

The diary of a girl in the 1980s who-- forbidden to go out on dates-- resorts to finding love via the phone. To learn more about Mortified visit getmortified.com.  The Mortified Podcast is a proud member of Radiotopia from PRX. 

02 Sakena: Mr. Telephone Man

Wenn es euch gefällt bitte abonnieren. ;-)

Please subscribe if you like it. ;-)

Thank you for listening!

Neodym - New

Firewatch stand auf unserer Liste der meisterwarteten Spiele 2016. Jetzt ist die Zeit der Abrechnung gekommen: Ist das Indie-Abentuer wirklich unsere Vorfreude wert gewesen, oder verdammen wir es wie eifersüchtige Ex-Freundinen?

Runde #46: Firewatch (Some people just want to watch the world burn)

BLOOD

In this episode of the Data Show, I spoke with Haoyuan Li, CEO and founder of Alluxio, a startup commercializing the open source project with the same name (full disclosure: I’m an advisor to Alluxio). Our discussion focuses on the state of Alluxio (the open source project that has roots in UC Berkeley’s AMPLab), specifically emerging use cases here and in China. Given the large-scale use in China, I also wanted to get Li’s take on the state of data and AI technologies in Beijing and other parts of China.

In the Age of AI, Fundamental Value Resides in Data

Scientist.

In this episode of the Data Show, I spoke with Roger Chen, co-founder and CEO of Computable Labs, a startup focused on building tools for the creation of data networks and data exchanges. Chen has also served as co-chair of O'Reilly's Artificial Intelligence Conference since its inception in 2016. This conversation took place the day after Chen and his collaborators released an interesting new white paper, "Fair value and decentralized governance of data." Current-generation AI and machine learning technologies rely on large amounts of data, and to the extent they can use their large user bases to create “data silos,” large companies in large countries (like the U.S. and China) enjoy a competitive advantage. With that said, we are awash in articles about the dangers posed by these data silos. Privacy and security, disinformation, bias, and a lack of transparency and control are just some of the issues that have plagued the perceived owners of “data monopolies.”

Acquiring and Sharing High-Quality Data

In this episode of the Data Show, I speak with Cassie Kozyrkov, technical director and chief decision scientist at Google Cloud. She describes "decision intelligence" as an interdisciplinary field concerned with all aspects of decision-making, and which combines data science with the behavioral sciences. Most recently she has been focused on developing best practices that can help practitioners make safe, effective use of AI and data. Kozyrkov uses her platform to help data scientists develop skills that will enable them to connect data and AI with their organizations' core businesses.

We had a great conversation spanning many topics, including:

How data science can be more useful

The importance of the human side of data

The leadership talent shortage in data science

Is data science a bubble?

Make Data Science More Useful

In this episode of the Data Show, I speak with Alex Ratner, project lead for Stanford’s Snorkel open source project; Ratner also recently garnered a faculty position at the University of Washington and is currently working on a company supporting and extending the Snorkel project. Snorkel is a framework for building and managing training data. Based on our survey from earlier this year, labeled data remains a key bottleneck for organizations building machine learning applications and services.

Ratner was a guest on the podcast a little over two years ago when Snorkel was a relatively new project. Since then, Snorkel has added more features, expanded into computer vision use cases, and now boasts many users, including Google, Intel, IBM, and other organizations. Along with his thesis advisor professor Chris Ré of Stanford, Ratner and his collaborators have long championed the importance of building tools aimed squarely at helping teams build and manage training data. With today’s release of Snorkel version 0.9, we are a step closer to having a framework that enables the programmatic creation of training data sets.

Labeling, Transforming, and Structuring Training Data Sets for Machine Learning

In this episode of the Data Show, I speak with Kesha Williams, technical instructor at A Cloud Guru, a training company focused on cloud computing. As a full stack web developer, Williams became intrigued by machine learning and started teaching herself the ML tools on Amazon Web Services. Fast forward to today, Williams has built some well-regarded Alexa skills, mastered ML services on AWS, and has now firmly added machine learning to her developer toolkit.

Becoming a Machine Learning Practitioner

In this episode of the Data Show, I speak with Michael Mahoney, a member of RISELab, the International Computer Science Institute, and the Department of Statistics at UC Berkeley. A physicist by training, Mahoney has been at the forefront of many important problems in large-scale data analysis. On the theoretical side, his works spans algorithmic and statistical methods for matrices, graphs, regression, optimization, and related problems. On the applications side, he has contributed to systems used for internet and social media analysis, social network analysis, as well as for a host of applications in the physical and life sciences. Most recently, he has been working on deep neural networks, specifically developing theoretical methods and practical diagnostic tools that should be helpful to practitioners who use deep learning.

Understanding Deep Neural Networks

Un soffio carico di pensieri
percorre il mio senso privato del dolore.

Iroshi Ito - Digital Sound
S. Zafarana 2012

foto di Kuno Ichi

Shunch'

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In the Age of AI, Fundamental Value Resides in Data

O'Reilly Radar

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