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Max Shron and Jake Porway talk with Jon Bruner about frameworks for making reasoned arguments with data. Max's recent book, <a href="http://shop.oreilly.com/product/0636920029182.do"><i>Thinking with Data</i></a>, outlines the crucial process of developing good questions and creating a plan to answer them. Jake's nonprofit, <a href="http://www.datakind.org/">DataKind</a>, connects data scientists with worthy causes where they can apply their skills.

For more on this episode, visit the <a href="http://radar.oreilly.com/2014/03/podcast-thinking-with-data.html">O'Reilly Radar blog</a>.

<i>This episode is brought to you by <a href="http://solidcon.com/">Solid</a>, O'Reilly's new conference about the intersection between software and the physical world--including hardware, manufacturing, design, and the code that makes sense of it all. For more information on Solid, and to reserve tickets, visit http://solidcon.com.</i>

Thinking with data

China has been a tough market to crack for U.S. internet companies. One of the key reasons is China has its own crop of hugely successful and highly innovative companies. Andreessen Horowitz’s Chris Dixon, Connie Chan and Benedict Evans highlight the key players in China, and what non-Chinese companies can learn from them. Where Chinese companies and money are headed next.

a16z Podcast: China and Tech

In this episode, I talk with Liza Kindred, founder of Third Wave Fashion and author of the new free report “Fashioning Data: How fashion industry leaders innovate with data and what you can learn from what they know.” Kindred addresses the evolving role data and analytics are playing in the fashion industry, and the emerging connections between technology and fashion companies. 

In the second segment, I chat with Max Firtman, founder of ITMaster, about the state of the HTML5 space and the future of mobile. He stresses that the change the Internet of Things will bring to the space will be significant and companies need to prepare: "All we know for sure right now is that everything is going to change."

For more, visit O'Reilly Radar: http://oreil.ly/101zhb5

What happens when fashion meets data?

On today’s show and thanks to one of our loyal listeners, I was able to finally meet up with Elizabeth Rossiello. Elizabeth is an American living and working in Kenya. She has worked as a microfinance analyst and investment associate since 2009. She is an expert in East African financial product development and she is the CEO and Co-Founder of BitPesa. BitPesa is the next logical step after mpesa and if you have no idea what I’m talking about, then stay tuned because this is a great interview.


CREDITS:

Links for the charities:
Tunapanda Institute
Contact: Jay Larson Jay@tunapanda.org

R.O.C.K
Contact Jason Lee  JLee1782@gmail.com

Heshima Kenya
Contact Tracey Hagman tracey@heshima.org

To get in touch with BitPesa:  info@bitpesa.co

Ode To Satoshi

Ode to Satoshi lyrics & melody by John Barrett
Copyright 2014 RJM Publishing - BMI Nashville. 

Lead Vocal, Harmony Vocals, Harmonica, Snare Drum: John Barrett
Harmony vocals: John Barrett, Connie Sinclair and Lij Shaw
Guitar: Jonathan Brown
Mandolin: Ben Miller
Bass Guitar: Michael Rinne

Initial tracks recorded by Mark Thornton of Sidekick Sound Studios, Madison, TN.  All other tracks Recorded, Mixed and Mastered at The Toy Box Studio, Nashville, Tennessee
Engineer: Lij Shaw. Assistant to engineer: Don “The Don” Bates
Produced by John Barrett & Elijah “Lij” Shaw
 
Special thanks to Alex Munoz Guijarro for his excellent pedal steel playing on many of our shows.

Interviews for this episode were edited and produced by John Barrett at The Tree House Studio - East Nashville, Tennessee.

Theme song “Gravy” by the band, Eleanor Roosevelt with Lij on fiddle.

Special thanks to Alex Munõz Guijarro for his excellent pedal steel playing on many of our shows.

Interviews for this episode were recorded and edited by John Barrett at The Tree House Studio - East Nashville, Tennessee. All shows are produced by John Barrett with the moral support of his trusty sidekick Maxwell Rascalnikov CoyoTe Rex, aka Max.

Theme song “Gravy” by the band, Eleanor Roosevelt with Elijah “Lij” Shaw on fiddle.

And a big thank you for moral support from my good friends at The Tennessee Bitcoin Alliance:
TennesseeBitcoin.org
 
Questions or Comments?

Bitcoins and Gravy Hotline: (615) 208-5198
Listeners . . . listen up! Call this number and say something funny, sing a song, read a poem or just rant! Or if you’d rather you can ask me a question, leave a comment, make a suggestion or record a complaint! If I like what you say I’ll put it on the next show!

Email me to say Howdy!: howdy@bitcoinsandgravy.com

Visit theWebsite: BitcoinsAndGravy.com

Bitcoins and Gravy Tipping Addresses:

Bitcoin: 1ByqQXLTm9JZGSwnfqCCakaifBt3grQkXS
Litecoin: LgqYgxLTBPgr8C1JGLLJVLK4ZN1fveprAp

And if you don’t feel like contacting me, just kick back, relax and enjoy the show. 
I hope you enjoy listening to my guests as much as I enjoy talking with them!


Bitcoins and Gravy Episode #46 BitPesa for Remittances and Spending!

O’Reilly’s big data guru Ben Lorica sits down with prominent data scientist DJ Patil to talk about his new ebook (written with Hilary Mason) and other topics in data science and big data.

A Brief Look At Data Science's Past And Future

John Wohlstetter, a senior fellow at the Discovery Institute and London Center for Policy Research where he specializes in national security, foreign policy and in particular nuclear proliferation, and author most recently of "Sleepwalking With the Bomb," sits down with Ben Weingarten of TheBlaze Books to discuss the most terrifying threats to America's homeland: nuclear weapons and an EMP. During the interview, John and Ben discuss why the nuclear threat is greater today than during the Cold War, the knock-on effects of a nuclear Iran, everything you need to know about EMPs, the strength of America's missile defense system, how the concept of mirror imaging is damaging national security, and much much more. 

Everything You Need to Know About the Nuclear and EMP Threats to the American Homeland

What exactly is an EMP, how much damage could it cause, and how might an attack happen?

Capital In The Twenty-First Century by Thomas Piketty on Audible:
http://www.audible.com/pd?asin=B00K33KA7M&source_code=AUDORWS0210159CL5

Get this audiobook for free when you try Audible:
http://www.audible.com/offers/30free?asin=B00K33KA7M&source_code=AUDORWS0210159CL5

Summary:

What are the grand dynamics that drive the accumulation and distribution of capital? Questions about the long-term evolution of inequality, the concentration of wealth, and the prospects for economic growth lie at the heart of political economy. But satisfactory answers have been hard to find for lack of adequate data and clear guiding theories. In Capital in the Twenty-First Century, Thomas Piketty analyzes a unique collection of data from 20 countries, ranging as far back as the 18th century, to uncover key economic and social patterns. His findings will transform debate and set the agenda for the next generation of thought about wealth and inequality.

Piketty shows that modern economic growth and the diffusion of knowledge have allowed us to avoid inequalities on the apocalyptic scale predicted by Karl Marx. But we have not modified the deep structures of capital and inequality as much as we thought in the optimistic decades following World War II. The main driver of inequality - the tendency of returns on capital to exceed the rate of economic growth - today threatens to generate extreme inequalities that stir discontent and undermine democratic values. But economic trends are not acts of God. Political action has curbed dangerous inequalities in the past, Piketty says, and may do so again.

A work of extraordinary ambition, originality, and rigor, Capital in the Twenty-First Century reorients our understanding of economic history and confronts us with sobering lessons for today.

Buy on Audible

Capital In The Twenty-First Century by Thomas Piketty, Narrated by L. J. Ganser

There are a couple of seemingly contradictory memes rolling around the deep learning field. One is that you need a truly epic amount of data to do interesting work. The other is that in many subject areas there is a ton of data but it's not just laying around for data scientists to snarf up.

On this week's Structure Show podcast, Enlitic Founder and CEO Jeremy Howard and Senior Data Scientist Ahna Girshick address those topics and more.

Girshick, who is our first guest who's worked with Philip Glass and Björk on creating music visualizations, said while there may be scads of MRIs, CAT scans, x-rays created -- they're typically used for their primary purpose -- to diagnose your bum knee, and are then squirreled away in some PACS system never to see the light of day again.

All of that data is useful for machine learning algorithms, or would be, if it were accessible, she said.

Girshick and  Howard agreed that while deep learning -- the process of a computer teaching itself how to solve a problem -- gets better with more data, there's no reason to hold off working with it for data become available.

"While more data can be better I think this is stopping people from trying to use big data inappropriately," Howard said. He cited a recent Kaggle competition on facial key point recognition that's  using 7,000 images and "the top algorithms are nearly perfectly accurate."

The reason companies like Baidu and Google say you need mountains of data is because they have mountains of data available, he said.  "I don't think people should be put off trying to use deep learing just because they don't have a lot of data."

Enlitic is using deep learning to provide medical diagnoses faster and help provide better medical and outcomes for millions of underserved people.

It's a fascinating discussion so please check it out -- Girshick will speak more on what Enlitic is doing at Structure Data next month.

And, if you want to hear what's going on with Pivotal's big data portfolio, Derrick Harris has the latest. Oh and Microsoft makes a bold play for startups by ponying up $500K in Azure cloud credits starting with the Y Combinator Winter 2015 class. That ups the ante pretty significantly compared to what Amazon Web Services, Google and IBM offer. Your move boys.

No, you don't need a ton of data to do deep learning

O’Reilly’s Ben Lorica chats with Kira Radinsky, CTO and co-founder of SalesPredict, about predicting events using machine learning, NLP, and semantic analysis.

Forecasting events, from disease outbreaks to sales to cancer research

Not surprisingly, Joseph Sirosh, has big ambitions for his product portfolio at Microsoft which includes Azure ML, HDInsight and other tools. Chief among them is making it easy for mere mortals to consume these data services from the applications they're familiar with. Take Excel for example.

If a financial analyst can, with a few clicks, send data to a forecast service in the cloud, then get the numbers back, visualized on the same spreadsheet, that's a pretty powerful story, said Sirosh who is corporate VP of machine learning for Microsoft.

But as valuable as those applications and services are, more and more of the value to be derived from computation over time will be the data itself, not all those tech underpinnings.  "In the future a huge part of the value generated from computing will come from the data as opposed to storage and operating systems and basic infrastructure," he noted on this week's podcast. WHich is why one topic under discussion at next month's Structure Data show will be who owns all the data flowing betwixt and betweeen various systems, the internet of things etc.

When it comes to getting corporations running these new systems Microsoft may have an ace in the hole because so many of them already use key Microsoft tools -- Active Directory, SQL Server, Excel. That gives them a pretty good on-ramp to Microsoft Azure and its resident services. Sirosh makes a compelling case and we'll talk to him more on stage at Structure Data next month in New York City.

In the first half of the show, Derrick Harris and I talk about the Hadoop world has returned to its feisty and oh so interesting roots. When Pivotal announced its plan to offload support of Hadoop to Hortonworks and work with that company along with IBM, GE on  the Open Data Platform the response from Cloudera CEO Mike Olsen in a blog post with his take. 

Also on the docket, @WalmartLabs massive OpenStack production private cloud implementation.

Microsoft's machine learning guru on why data matters sooooo much

A social media mistake for the record books, and a quiet saint of Wikipedia. 

Reply All from Gimlet Media

#14 The Art of Making and Fixing Mistakes

The latest Chrome OS stable channel update is here and with it comes remote access to Chromebooks and Chromeboxes. Until now you could only remote out of such devices; now you can remote in to them; handy for tech support and other use cases. We also discuss why Acer's new Chromebook 15 isn't yet available and share a useful Chrome extension that lets you run Linux inside of a Chrome OS window.

Chrome Show: Remote Chromebook Access Arrives For All

O'Reilly's Ben Lorica talks with Angie Ma, co-founder and president of ASI, about the concept of the ASI, the structure of their training programs, and the data and startup scene in the UK.

Turning Ph.D.s Into Industrial Data Scientists and Data Engineers

A weekly podcast from GigaOM providing the latest news, analysis and interviews about the cloud, infrastructure and big data spaces. 

No, you don't need a ton of data to do deep learning

Gigaom Structure