IntelVerse

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

Nicole, 63 ans, est une des rares femmes pêcheuse de crevettes à Dunkerque. Ancienne ouvrière du textile et mère de six enfants, elle trouve dans cette pratique réservée aux hommes une échappatoire, un moment de paix. L'eau soigne son corps abîmé par le travail en usine, les maternités et le travail domestique. Nicole est aussi championne du monde de décorticage de crevettes ! Elle raconte qu'elle a pu gagner 10 fois ce concours grâce au travail en usine, qui lui a fait exercer sa rapidité et sa dextérité. Les médias soudain parlent d'elle. Nicole se voit reconnue hors du cercle domestique. Une récompense ? Une revanche ? Un plaisir ?
Au-delà de l'image folklorique de la pêche à la crevette, cet épisode d'Un podcast à soi / Une vie à soi interroge le rapport au temps, au travail domestique, à la reconnaissance. Et donne à entendre des résistances invisibles.

Pour prolonger l'écoute :
- Un podcast à soi n°16 : Du pain et des roses
- « Quotidien Politique », Geneviève Pruvost, Editions La Découverte
- Domesticités
- Sans queue ni tête, Film en chantier de Julien Brygo
- Sur la planche, un film de Leïla Kilani

Enregistrements : mai 22 - Prise de son, textes et voix : Charlotte Bienaimé - Montage, réalisation, mixage et musique originale : Samuel Hirsch - Sélection des textes, réseaux sociaux et accompagnement éditorial : Sarah Bénichou - Illustrations : Anna Wanda Gogusey - Production : ARTE Radio

Une vie à soi : Nicole | Un podcast à soi (37)

<a href="https://www.economist.com/leaders/2022/06/15/the-fed-and-the-ecb-turn-on-a-dime" rel="noopener noreferrer" target="_blank">America’s central bank </a>raised rates by .75% yesterday—the biggest increase in almost 30 years. Whether that will help tame rising prices without triggering a recession is unclear. The poor performance of Russian tanks in Ukraine has led some to wonder whether <a href="https://www.economist.com/interactive/international/2022/06/15/does-the-tank-have-a-future" rel="noopener noreferrer" target="_blank">the tank itself</a> is obsolete. And the rousing, darkly humorous defiance of <a href="https://www.economist.com/culture/2022/06/08/ukrainian-musicians-have-a-stark-message-for-the-kremlin" rel="noopener noreferrer" target="_blank">Ukrainian war anthems</a>. For full access to print, digital and audio editions of The Economist, subscribe here <a href="http://www.economist.com/intelligenceoffer" rel="noopener noreferrer" target="_blank">www.economist.com/intelligenceoffer</a> &#10;&nbsp; <hr>See <a style='color: grey; ' target='_blank' rel='noopener noreferrer' href='https://acast.com/privacy'>acast.com/privacy</a> for privacy and opt-out information.

Powell to the people: The Fed raises rates

- Tell us something we don't know!
- Stranger Things ROCKS "Master of Puppets"
- An Iowan on Jeopardy? (Waukee!)
- What's next for the Big 12?

Stranger Things ROCKS "Master of Puppets"!

Listen to an excerpt from I'M GLAD MY MOM DIED by Jennette McCurdy, read by the author.

I'M GLAD MY MOM DIED Audiobook Excerpt

In this episode of the O’Reilly Data Show, I spoke with Danny Bickson, co-founder and VP at Dato, and the principal organizer of the Data Science Summit (full disclosure: I’m a member of the conference organizing committee). Among machine learning students and practitioners, recommender systems have become somewhat of a canonical use case and application. One of the early and popular building blocks was GraphLab’s collaborative filtering toolkit, a library originally written and maintained by Bickson. He has continued to keep tabs on the latest developments in recommenders and continues to help organize workshops on related topics throughout the world.

Building and Deploying Large-Scale Machine Learning Applications

BLOOD

In this episode of the Data Show, I spoke with Parvez Ahammad, who leads the data science and machine learning efforts at Instart Logic. He has applied machine learning in a variety of domains, most recently to computational neuroscience and security. Along the way, he has assembled and managed teams of data scientists and has had to grapple with issues like explainability and interpretability, ethics, insufficient amount of labeled data, and adversaries who target machine learning models. As more companies deploy machine learning models into products, it’s important to remember there are many other factors that come into play aside from raw performance metrics.

Building Machine Learning Solutions That Can Withstand Adversarial Attacks

Dr Ben Hardy, Research Associate in Neuroscience, Endocrinology & Finance, says morale is related to performance. Workers with high morale believe they that they work harder, longer and communicate more effectively. Low morale can produce the reverse but not in all circumstances. An individual's professional approach may drive them irrespective of their feelings.

Don't worry be happy!

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

In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer and legal engineer at Immuta, a company building data management tools tuned for data science. Burt and cybersecurity pioneer Daniel Geer recently released a must-read white paper (“Flat Light”) that provides a great framework for how to think about information security in the age of big data and AI. They list important changes to the information landscape and offer suggestions on how to alleviate some of the new risks introduced by the rise of machine learning and AI.

We discussed their new white paper, cybersecurity (Burt was previously a special advisor at the FBI), and an exciting new Strata Data tutorial that Burt will be co-teaching in March.

How Machine Learning Impacts Information Security

Three generals are voting on whether to attack or retreat from their siege of a castle. One of the generals is corrupt and two of them are not. What happens when the corrupted general sends different answers to the other two generals?

A Byzantine fault is "a condition of a computer system, particularly distributed computing systems, where components may fail and there is imperfect information on whether a component has failed. The term takes its name from an allegory, the "Byzantine Generals' Problem", developed to describe this condition, where actors must agree on a concerted strategy to avoid catastrophic system failure, but some of the actors are unreliable."

The Byzantine Generals' Problem and associated issues in maintaining reliable distributed computing networks is illuminating for both AI alignment and modern networks we interact with like Youtube, Facebook, or Google. By exploring this space, we are shown the limits of reliable distributed computing, the safety concerns and threats in this space, and the tradeoffs we will have to make for varying degrees of efficiency or safety.

The Byzantine Generals' Problem, Poisoning, and Distributed Machine Learning with El Mahdi El Mahmdi is the ninth podcast in the AI Alignment Podcast series, hosted by Lucas Perry. El Mahdi pioneered Byzantine resilient machine learning devising a series of provably safe algorithms he recently presented at NeurIPS and ICML. Interested in theoretical biology, his work also includes the analysis of error propagation and networks applied to both neural and biomolecular networks. This particular episode was recorded at the Beneficial AGI 2019 conference in Puerto Rico. We hope that you will join in the conversations by following us or subscribing to our podcasts on Youtube, SoundCloud, iTunes, Google Play, Stitcher, or your preferred podcast site/application. You can find all the AI Alignment Podcasts here.

If you're interested in exploring the interdisciplinary nature of AI alignment, we suggest you take a look here at a preliminary landscape which begins to map this space.

Topics discussed in this episode include:

The Byzantine Generals' Problem
What this has to do with artificial intelligence and machine learning
Everyday situations where this is important
How systems and models are to update in the context of asynchrony
Why it's hard to do Byzantine resilient distributed ML.
Why this is important for long-term AI alignment
An overview of Adversarial Machine Learning and where Byzantine-resilient Machine Learning stands on the map is available in this (9min) video . A specific focus on Byzantine Fault Tolerant Machine Learning is available here (~7min)

In particular, El Mahdi argues in the first interview (and in the podcast) that technical AI safety is not only relevant for long term concerns, but is crucial in current pressing issues such as social media poisoning of public debates and misinformation propagation, both of which fall into Poisoning-resilience. Another example he likes to use is social media addiction, that could be seen as a case of (non) Safely Interruptible learning. This value misalignment is already an issue with the primitive forms of AIs that optimize our world today as they maximize our watch-time all over the internet.

The latter (Safe Interruptibility) is another technical AI safety question El Mahdi works on, in the context of Reinforcement Learning. This line of research was initially dismissed as "science fiction", in this interview (5min), El Mahdi explains why it is a realistic question that arises naturally in reinforcement learning

El Mahdi's work on Byzantine-resilient Machine Learning and other relevant topics is available on
his Google scholar profile.

The Byzantine Generals' Problem, Poisoning, and Distributed Machine Learning with El Mahdi El Mhamdi

Guess Who

Founder of EPIC Knowledge Society and SPACE Creative Culture Labs. I am a Futurist and Data Scientist with Professional Mastery and Pragmatic Insights on Digital Transformation and Innovation Management with extensive credentials on Digital Enterprise Architectures, Crypto Economics, Customer Experience Design, Social Entrepreneurship Incubation, Business Model Innovation, Innovation Ecosystems, Innovation Analytics, Innovation Consulting, Social Business Networks, Academic Research Networks, Industrial Research Alliances, New Service Incubation, New Product Incubation, New Platform Innovation, High performing Teams, Cross Competency Innovation etc.

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.

Building and Deploying Large-Scale Machine Learning Applications

O'Reilly Radar

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