More than a currency, bitcoin is an enabling technology

The O'Reilly Radar Podcast: Balaji Srinivasan on the bigger picture of bitcoin, liquid markets, and the future of regulation.

The promise of bitcoin and blockchain extends well beyond its potential disruption as a currency. In this Radar Podcast episode, Balaji Srinivasan, a general partner at Andreessen Horowitz, explains how bitcoin is an enabling technology and why it’s like the Internet, in that “bitcoin will do for value transfer what the Internet did for communication — make it programmable.” I met up with Srinivasan at our recent O’Reilly Radar Summit: Bitcoin & the Blockchain, where he was speaking — you can see his talk, and all the others from the event, in the complete video compilation now available.

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The bigger picture of bitcoin

More than just a digital currency, bitcoin can serve as an instigator for new markets. Srinivasan explained the potential for everything to become a liquid market:

“Bitcoin is a platform for programmable money, programmable interchange, or anything of value. That’s very general. People have probably heard at this point about how you can use a blockchain to trade — in theory — stocks, or houses, or other kinds of things, but programmable value transfer is even bigger than just trading things which we know already exist.

“One analogy I would give is in 1988, it was not possible to find information on anything instantly. Today, most of the time it is. From your iPhone or your Android phone, you can google pretty much anything. In the same way, I think what bitcoin is going to mean, is markets in everything. That is, everything will have a price on it — everything will be a liquid market. You’ll be able to buy and sell almost anything. Where today the fixed costs of setting up such a market is too high for anything other than things that are fairly valuable, tomorrow it’ll be possible for even images or things you would not even think of normally buying and selling.”

Read more…

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Forecasting events, from disease outbreaks to sales to cancer research

The O'Reilly Data Show Podcast: Kira Radinsky on predicting events using machine learning, NLP, and semantic analysis.

Editor’s note: One of the more popular speakers at Strata + Hadoop World, Kira Radinsky was recently profiled in the new O’Reilly Radar report, Women in Data: Cutting-Edge Practitioners and Their Views on Critical Skills, Background, and Education.

When I first took over organizing Hardcore Data Science at Strata + Hadoop World, one of the first speakers I invited was Kira Radinsky. Radinsky had already garnered international recognition for her work forecasting real-world events (disease outbreak, riots, etc.). She’s currently the CTO and co-founder of SalesPredict, a start-up using predictive analytics to “understand who’s ready to buy, who may buy more, and who is likely to churn.”

I recently had a conversation with Radinsky, and she took me through the many techniques and subject domains from her past and present research projects. In grad school, she helped build a predictive system that combined newspaper articles, Wikipedia, and other open data sets. Through fine-tuned semantic analysis and NLP, Radinsky and her collaborators devised new metrics of similarity between events. The techniques she developed for that predictive software system are now the foundation of applications across many areas. Read more…

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A tale of two clusters: Mesos and YARN

With Myriad, analytics can be performed on the same hardware that runs your production services.

This is a tale of two siloed clusters. The first cluster is an Apache Hadoop cluster. This is an island whose resources are completely isolated to Hadoop and its processes. The second cluster is the description I give to all resources that are not a part of the Hadoop cluster. I break them up this way because Hadoop manages its own resources with Apache YARN (Yet Another Resource Negotiator). Which is nice for Hadoop, but all too often those resources are underutilized when there are no big data workloads in the queue. And then when a big data job comes in, those resources are stretched to the limit, and they are likely in need of more resources. That can be tough when you are on an island.

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Isolated clusters. Source: Mesosphere and MapR, used with permission.

Hadoop was meant to tear down walls — albeit, data silo walls — but walls, nonetheless. What has happened is that while tearing some walls down, other types of walls have gone up in their place.

Another technology, Apache Mesos, is also meant to tear down walls — but Mesos has often been positioned to manage the “second cluster,” which are all of those other, non-Hadoop workloads.

This is where the story really starts, with these two silos of Mesos and YARN. They are often pitted against each other, as if they were incompatible. It turns out they work together, and therein lies my tale. Read more…

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Software engineers must continuously learn and integrate

Four ways programmers can thrive in their careers.

Software engineers: themes to watch in software architecture, open source culture and code, data, mobile and the Internet of Things

As O’Reilly continues to build and assess our programming content ecosystem — now more than 30 years in the making — we have gone from covering a few key languages, operating systems, and concepts to a diversification of topics that would have made an editor’s head spin in the 1980s. Our goal, however, remains the same: to continue to provide practical content from experts who help you do your job. An important piece of that goal is to keep you informed as we interpret the trends on the horizon. What follows are a few of the core themes we are focusing on at the moment. Expect these to evolve and change with the speed of innovation.

You can also stay in the loop on the latest analysis and developments through our weekly Programming newsletter.

Actually be a software engineer

The term “full-stack” first emerged in a 2008 blog post (no longer readable as the link is dead), and perhaps reached its canonical definition in a post by Facebook engineer Carlos Bueno. He wrote:

“A ‘full-stack programmer’ is a generalist, someone who can create a non-trivial application by themselves. People who develop broad skills also tend to develop a good mental model of how different layers of a system behave.“

Whether you are striving to be a full-stack programmer, a T-shaped engineer, or you choose to rebuff those terms entirely as mere marketing, what now floats around as a “full-stack developer” definition is incomplete. Read more…

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Five things to consider before offering new technology as a cloud service

Entrepreneurs must apply the same decision-making processes used when starting any infrastructure company.

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Editor’s note: Shahin Farshchi will cover these topics and more in an upcoming free webcast, Building Value Into Hardware Start-ups, on March 19 at 1 p.m. PT. Find out more, and reserve your spot.

There are many compelling reasons to package new technology as a cloud service. Connected devices come in many forms: dongles, phones, tablets, televisions, cars, and even buildings. Intel is offering “connected buttons,” and others are introducing connected jewelry and accessories. Internet connectivity is also available through many channels: satellite, cellular, WiFi, bluetooth, and hybrid meshes. The plethora of powerful, beautiful connected devices, coupled with ubiquitous connectivity, creates an incredible channel for delivering novel services.

Hotmail, Salesforce, Workday, and many other software-as-a-service companies have fared well by offering their applications directly through Internet browsers. DropBox and Box, while creating tremendous media attention, have yet to prove they can offer storage services profitably on the cloud. Amazon doesn’t disclose the economics of its Amazon Web Services business in detail, though one would expect the opposite to be true if it were a lucrative business. ASICMiner and KNCMiner are leveraging their proprietary hashing chips to offer bitcoin mining as a service. Nervana is leveraging its proprietary chips as a service for deep learning. As more entrepreneurs attempt to harness the cloud as a powerful distribution channel for their novel technologies, here are a few factors to consider. Read more…

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The Intimacy of Things

At what layer do we build privacy into the fabric of devices?

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Editor’s note: This is part of a series of posts exploring privacy and security issues in the Internet of Things. The series will culminate in a free webcast by the series author Dr. Gilad Rosner: Privacy and Security Issues in the Internet of Things will happen on February 11, 2015 — reserve your spot today.

In 2011, Kashmir Hill, Gizmodo and others alerted us to a privacy gaffe made by Fitbit, a company that makes small devices to help people keep track of their fitness activities. It turns out that Fitbit broadcast the sexual activity of quite a few of their users. Realizing this might not sit well with those users, Fitbit took swift action to remove the search hits, the data, and the identities of those affected. Fitbit, like many other companies, believed that all the data they gathered should be public by default. Oops.

Does anyone think this is the last time such a thing will happen?

Fitness data qualifies as “personal,” but sexual data is clearly in the realm of the “intimate.” It might seem like semantics, but the difference is likely to be felt by people in varying degrees. The theory of contextual integrity says that we feel violations of our privacy when informational contexts are unexpectedly or undesirably crossed. Publicizing my latest workout: good. Publicizing when I’m in flagrante delicto: bad. This episode neatly exemplifies how devices are entering spaces where they’ve not tread before, physically and informationally. Read more…

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