Name: Introducing Model-Based Thinking Into AI Systems by O'Reilly Radar in data stuff
Duration: 44 min 37 s
Description: In this episode I spoke with Vikash Mansinghka, research scientist at MIT, where he leads the Probabilistic Computing Project, and co-founder of Empirical Systems. I’ve long wanted to introduce listeners to recent developments in probabilistic programming, and I found the perfect guide in Mansinghka.

data stuff

On this episode of "Speaking of Bitcoin", join hosts Adam B. Levine, Andreas M. Antonopoulos, Stephanie Murphy and Jonathan Mohan for a discussion about loans in the world of crypto.
HODL. It's crypto-land philosophy for not selling your preferred token even when things look their most bleak. But where philosophy intersects with real-world concerns like shelter, food and the niceties of life, tactics have emerged offering both opportunities and risks. From smart contracts to bitcoin collateralized mortgages, the hosts discuss their experiences with loans in the world of crypto.
Credits
Today’s show featured Andreas M. Antonopoulos, Jonathan Mohan, Stephanie Murphy and Adam B. Levine, with editing by Adam B. Levine and music by Gurtybeats.com. Our episode art is a picture provided by The New York Public Library, modified by "Speaking of Bitcoin."
Any questions or comments? Send us an email at adam@speakingofbitcoin.show

SOB #496 The Ups and Downs of Crypto Loans

Listen to an excerpt of Alex Segura's SECRET IDENTITY, read by Aida Reluzco.

It’s 1975 and the comic book industry is struggling, but Carmen Valdez doesn’t care. She’s an assistant at Triumph Comics, which doesn’t have the creative zeal of Marvel nor the buttoned-up efficiency of DC, but it doesn’t matter. Carmen is tantalizingly close to fulfilling her dream of writing a superhero book.

That dream is nearly a reality when one of the Triumph writers enlists her help to create a new character, which they call “The Lethal Lynx,” Triumph's first female hero. But her colleague is acting strangely and asking to keep her involvement a secret. And then he’s found dead, with all of their scripts turned into the publisher without her name. Carmen is desperate to piece together what happened to him, to hang on to her piece of the Lynx, which turns out to be a runaway hit. But that’s complicated by a surprise visitor from her home in Miami, a tenacious cop who is piecing everything together too quickly for Carmen, and the tangled web of secrets and resentments among the passionate eccentrics who write comics for a living.

Alex Segura uses his expertise as a comics creator as well as his unabashed love of noir fiction to create a truly one-of-a-kind novel--hard-edged and bright-eyed, gritty and dangerous, and utterly absorbing.

Buy the audiobook

Secret Identity by Alex Segura, audiobook excerpt

Comment continuer à faire l’amour sans se poser de questions quand on est hétéro, mais aussi fan de Virginie Despentes ? Intellectuellement, on peut tout à fait adhérer aux idées féministes qui démontent les pratiques érotiques standard, à base de pénétration et de domination masculine. Mais en pratique, il n’est pas forcément évident de rebooter son répertoire à phantasmes. Peut-on vraiment dégommer les scénarios sexuels incrustés dans notre psyché ? Qu’en faire ? Comment les assumer sans s’aliéner à ce fichu patriarcat ?

En proie à ces grandes questions et à un vague sentiment de culpabilité, Delphine Saltel rencontre le philosophe Alexandre Lacroix, homme, cis, hétéro, marié, père de 5 enfants, et philosophe. Dans son dernier livre « Apprendre à faire l’amour » paru aux éditions Allary, il essaie d’interroger la sexualité hétéro standard, à sa manière. En puisant dans sa discipline quelques outils sexologiques originaux, Alexandre Lacroix nous incite à passer au rayon X les scripts sexuels dominants dont nous avons hérité. Car pour revisiter nos automatismes et notre imaginaire érotique, il faut déjà prendre conscience des règles et des conventions sociales auxquels on obéit souvent inconsciemment quand on fait l’amour. Analyser le cocktail freudo-porno-sexo qui nous abreuve, et changer nos habitudes pour espérer modifier le scénario. 

Merci à Xavier de la Porte.

Bibliographie :
- « Apprendre à faire l’amour », Alexandre Lacroix, Allary éditions
- « Trois essais sur la théorie sexuelle », Sigmund Freud, 1906
- « Human sexual response », William Masters et Virginia Johnson, 1966
- « Le rapport Hite », Shere Hite, Robert Laffont, 1977
- « Connemara », Nicolas Mathieu, Actes Sud, 2022
- « Réinventer l’amour », Mona Chollet, La Découverte, 2021

Vivons heureux avant la fin du monde
Comment s’habiller, échanger, voyager, s’aimer dans les années 20 ? Pour se bricoler une morale minimale en des temps de crises sociale, écologique et sanitaire, Delphine Saltel (Que sont-ils devenus ?, Y'a deux écoles) explore chaque mois nos incohérences et les solutions possibles. Mêlant questionnement personnel, tribulations domestiques, reportages et entretiens avec des chercheurs et des activistes, ce nouveau podcast veut alerter, éveiller et rassurer sur un autre monde possible.

Enregistrements : avril 2022 - Texte, voix, entretiens, réalisation : Delphine Saltel - Mise en ondes & mix : Charlie Marcelet - Illustration : Mathilde Rives - Production : ARTE Radio

Doit-on apprendre à faire l’amour ?

Pendant des décennies, les personnes analphabètes de ma famille se sont enregistrées sur des cassettes afin de communiquer avec leurs proches en France. Ma mère et moi venons de retrouver une K7 audio datant de 2004, glissée dans une enveloppe qui n’a jamais été ouverte. Elle l’écoute pour la première fois, dix-sept ans plus tard. Nous étions persuadées qu’elle contenait un message de ma grand-mère. Mais la cassette renferme en réalité un message de la première femme de mon grand-père, yaye Elisa ou "maman Elisa", aujourd’hui décédée. Ma mère semble bien plus émue que s’il s’agissait de la voix de sa “vraie” maman. Cette découverte surprenante me pousse à échanger avec elle sur la polygamie, mais aussi sur l'importance de l'oralité et de la transmission dans notre famille partagée entre France et Sénégal. Ma mère, comme beaucoup d'immigrés, a mené une double vie entre deux continents. L’écoute de cette cassette réactive une mémoire de l’immigration : une arrivée en France douloureuse et l’amour des siens laissés au pays. (Emilie) 

Ce documentaire a été soutenu par l'appel à projets 2021 du ministère de la Culture. 

Emilie Mendy est auteure de podcasts et journaliste. En 2021, elle coécrit avec Annabelle Martella la fiction "Game Lover" produite par ARTE Radio, et classée parmi les 10 podcasts les plus marquants de l’année par Les Inrocks. Elle aide les auteurs débutants à lancer leur podcast sur sa plateforme Emilie Podcast. Depuis 2020, elle tient également la chronique mode “Dress code : street” sur Mouv’. Ses sujets de prédilection concernent les contre-cultures et les populations marginalisées.

Enregistrements : 2021-22 - Texte, voix, prise de son, montage : Emilie Mendy - Réalisation et musique originale : Samuel Hirsch - Illustration : Maïc Baxane - Production : ARTE Radio - Remerciements : Clarisse Mendy, Elisa Mendy, Jeanette Gomis

La K7 de yaye Elisa

Rana Eid est sound designer et réalisatrice. Depuis près 40 ans, elle enregistre les ambiances de Beyrouth, sa ville natale. Elle enregistre donc les sons de la guerre civile (1975-1990), la reconstruction, la guerre de 2006, la révolution civile de 2019, l’explosion du port le 4 août 2020 et enfin l’effondrement actuel du Liban. Aujourd'hui, elle commente ses propres archives sonores qui racontent son pays meurtri et une ville qui retient son souffle. Marine Vlahovic (Carnets de correspondante) a rencontré Rana Eid une première fois en 2014 avant de la retrouver quelques années plus tard. Un manifeste sensible sur l’importance du son dans nos mémoires. 

Ce documentaire est lauréat de l'appel à projets 2021 du ministère de la Culture.

Le souffle de Beyrouth

Athlétique et intrépide, Giovanna Amati n’a qu’une idée en tête: devenir pilote automobile. Pour l’heure, la jeune femme de 19 ans vit enchainée dans un caisson obscur et insonorisé de 4m². Daniel Nieto est son geôlier attitré. Une nuit, il entre dans la cage à visage découvert...

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(4/7): Dans la cage

Wall Street Journal's Josh Zumbrun details how airlines get rid of certain passengers on a flight and how passengers can fight against this issue.

The Science Behind Who Airlines Bump From a Flight—and How to Exploit It

<ul> 
<li>Apple is just three weeks away from showing off the iPhone 14.</li> 
<li>Apple workers launch petition over company's reported return-to-office plan.</li> 
<li>Apple's new iPad multitasking system doesn't cut it</li> 
<li>Apple releases iOS, iPadOS and macOS security fixes for two zero-days under active attack.</li> 
<li>Tim Cook, Jony Ive, and Laurene Powell Jobs to speak at Code 2022 conference next month.</li> 
<li>iOS VPNs have leaked traffic for years, researcher claims.</li> 
<li>M2 MacBook Air runs Windows 11 faster than pricier Dell laptop.</li> 
<li>Former Apple engineer accused of stealing automotive trade secrets pleads guilty.</li> 
<li>John Foster: In memoriam.</li> 
<li>10 million watched 'House of Dragon,' HBO says.</li> 
<li>Apple fails in bid for Big Ten Conference streaming package.</li> 
<li>Apple brings Self-Service Repair to the Mac.</li> 
<li>Jason found a funny bug in macOS beta.</li></ul> 
Picks of the Week<ul> 
<li>Alex's Pick: Stellar X2</li> 
<li>Andy's Pick: Anker Nano II 65W GaN Charger</li> 
<li>Jason's Pick: One Thing &amp; Shortery</li></ul> 
Hosts: <a href="https://twit.tv/people/leo-laporte">Leo Laporte</a>, <a href="https://twit.tv/people/alex-lindsay">Alex Lindsay</a>, <a href="https://twit.tv/people/andy-ihnatko">Andy Ihnatko</a>, and <a href="https://twit.tv/people/jason-snell">Jason Snell</a> 
Download or subscribe to this show at <a href="https://twit.tv/shows/macbreak-weekly">https://twit.tv/shows/macbreak-weekly</a>. 
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MacBreak Weekly 832: A Fine Patina

In this episode I spoke with Vikash Mansinghka, research scientist at MIT, where he leads the Probabilistic Computing Project, and co-founder of Empirical Systems. I’ve long wanted to introduce listeners to recent developments in probabilistic programming, and I found the perfect guide in Mansinghka.

Introducing Model-Based Thinking Into AI Systems

In this episode of the Data Show, I spoke with Aurélien Géron, a serial entrepreneur, data scientist, and author of a popular, new book entitled "Hands-on Machine Learning with Scikit-Learn and TensorFlow." Géron’s book is aimed at software engineers who want to learn machine learning and start deploying machine learning models in real-world products.

Becoming a Machine Learning Engineer

In this episode of the Data Show, I spoke with Jeremy Stanley, VP of data science at Instacart, a popular grocery delivery service that is expanding rapidly. As Stanley describes it, Instacart operates a four-sided marketplace comprised of retail stores, products within the stores, shoppers assigned to the stores, and customers who order from Instacart. The objective is to get fresh groceries from popular retailers delivered to customers in a timely fashion. Instacart’s goals land them in the center of the many opportunities and challenges involved in building high-impact data products.

Data Science and Deep Learning in Retail

In this episode of the Data Show, I speak with Naveen Rao, VP and GM of the Artificial Intelligence Products Group at Intel. In an earlier episode, we learned that scaling current deep learning models requires innovations in both software and hardware. Through his startup Nervana (since acquired by Intel), Rao has been at the forefront of building a next generation platform for deep learning and AI.

I wanted to get his thoughts on what the future infrastructure for machine learning would look like. At least for now, we’re seeing a variety of approaches, and many companies are using heterogeneous processors (even specialized ones) and proprietary interconnects for deep learning. Nvidia and Intel Nervana are set to release processors that excel at both training and inference, but as Rao pointed out, at large-scale there are many considerations—including utilization, power consumption, and convenience—that come into play.

Building a Next-Generation Platform for Deep Learning

In this episode of the Data Show, I spoke with Ken Stanley, founding member of Uber AI Labs and associate professor at the University of Central Florida. Stanley is an AI researcher and a leading pioneer in the field of neuroevolution—a method for evolving and learning neural networks through evolutionary algorithms. In a recent survey article, Stanley went through the history of neuroevolution and listed recent developments, including its applications to reinforcement learning problems.

Effective Mechanisms for Searching the Space of Machine Learning Algorithms

When I first discovered and started using Apache Spark, a majority of the use cases I used it for involved unstructured text. The absence of libraries meant rolling my own NLP utilities, and, in many cases, implementing a machine learning library (this was pre deep learning, and MLlib was much smaller). I’d always wondered why no one bothered to create an NLP library for Spark when many people were using Spark to process large amounts of text. The recent, early success of BigDL confirms that users like the option of having native libraries.

In this episode of the Data Show, I spoke with David Talby of Pacific.AI, a consulting company that specializes in data science, analytics, and big data. A couple of years ago I mentioned the need for an NLP library within Spark to Talby; he not only agreed, he rounded up collaborators to build such a library. They eventually carved out time to build the newly released Spark NLP library. Judging by the reception received by BigDL and the number of Spark users faced with large-scale text processing tasks, I suspect Spark NLP will be a standard tool among Spark users.

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Registration is now open 
Talby and I also discussed his work helping companies build, deploy, and monitor machine learning models. Tools and best practices for model development and deployment are just beginning to emerge—I summarized some of them in a recent post, and, in this episode, I discussed these topics with a leading practitioner.

Building a Natural Language Processing Library for Apache Spark

Le sommier qui grince. Les cris et gémissements de la porte à-côté. Le plafond qui menace de s'écrouler. Pourquoi la vie sexuelle de nos voisins est-elle aussi envahissante ? Comment une activité privée finit-elle par devenir publique ? Ils prennent du Viagra ou des amphétamines ? Et surtout : est-ce que par hasard... on n'aimerait pas entendre - et écouter - nos voisins ?

A retrouver aussi sur la chaîne Youtube ARTE Radio
Enregistrements : avril 18 - Mise en ondes & mix : Arnaud Forest - Texte & voix : Maïa Mazaurette - Illustration : Sjoerd van Leeuwen

Sex and sounds (n°26) : Les voisins bruyants

While shooting the cultish webserie “New York Minute”, Samuel Hirsch recorded some urban sounds and voices for this short Afro-American ballad.  
Recorded on March 2010 - Directed by Samuel Hirsch - Produced by http://arteradio.com
Balade sonore à New York, avec sons urbain et voix afro-américaines. Enregistrée et montée par Samuel Hirsch pendant le tournage de "New York Minute", la web série culte produite par ARTE Radio.  

Download : http://bit.ly/1gFFt92


NY state of mind

O'Reilly Media spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. We have a pretty good record at having anticipated some of the big technology developments in recent history. For instance, we launched the first commercial Web site, GNN, in 1993; we organized the meeting at which the term “open source” was first adopted; we were early investors in Blogger, which helped launch the blogging revolution; and more recently, our Web 2.0 conference launched a world-wide meme. We call this predictive sense the “O’Reilly Radar.” And while we’re certainly not always right, we are, at least, good at making interesting guesses.

Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.

Introducing Model-Based Thinking Into AI Systems

O'Reilly Radar

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