Love and Money and in an Indeterminate Age

Posted on by Max K Goff Posted in Big Data, Data Science

Peter Thiel’s Strategy Quadrant

PayPal founder Peter Thiel is obviously a prescient individual with ample cognitive gifts.

You should take the time to view his session at SXSW this year: You are Not a Lottery Ticket

The future has always been uncertain. But the extent of uncertainty has increased quite markedly since the dawn of the Network Age. Just as disintermediation and productivity are amplified by 21st century tech, so too is risk. But because we are now ever-better at the gathering and analysis of ever-more data, an emergent “new religion” informs our thinking. The physics of this faith are more quantum than newtonian, and more probability than design. Thiel poses a most interesting question: Is optimism a cogent strategy in a fundamentally uncertain world?

Thiel’s quadrant approach reminds me of Costanza’s Four Futures with world view juxtaposed to reality blending and bending reality to enable emergence of the future we cannot yet imagine.

The implications of Thiel’s observations are quite enormous:

  • Bubbles, for example, are a natural result of high uncertainty mixed with Helicopter Ben’s much maligned solutions to remedy the global economic malaise. High uncertainty and high optimism? Let Ben help.
  • Engineering stuff is very 20th century — it’s about finance now. The Maker Movement not withstanding, most Network Age stuff-based tech is simply consumables; commodities (unless, of course, you’re Apple). The engineering of great stuff is less likely to garner investment than is a complex financial instrument, when compared to the world of just 20 years ago.
  • Along with banks, insurance companies will own everything. No surprise there, he? The greater the threshold of uncertainty, the greater the pessimism. Insurance is a sensible choice if you’re on a career reinvention path.
  • Money itself is uncertain. Holding cash? With the twin scepters of negative interest rates on one hand and Cypriot Haircuts on the other, is it any wonder Bitcoin has garnered the attention it has? Alas, it is only a question of time before regulators curtail that little p2p experiment. It’s not a question of if regulations will choke the life out of it, but which agency gets to do it.

The new religion: probability and statistics. Sentiment analysis is the new liturgy and A/B testing our perennial penance for our sins, which are, as is everything else, TBD.

It’s the Luck Ethic now. There’ll be more on that later.

Microsoft Puts Free Portable WiFi In Forbes Magazine Print Issues

Posted on by Max K Goff Posted in Big Data


Perhaps one day we will wake up to find that over night a next-generation network access devices were dropped from above, like particles of fertilizer sprayed by crop dusters over corn fields.

Who said print was dead? 🙂

I wonder if the folks at Forbes considered that fact that they’re helping ensure the demise of their own hard-copy magazine with this experiment?

Free portable WiFi devices — in a magazine.

Shame.css

Posted on by Max K Goff Posted in Big Data

I laughed out loud when I read Harry Roberts’ blog touting shame.css — but as I think about it, he may be onto something.

In the spirit of Convention Over Configuration, why not cloister hacks whenever possible? Wouldn’t doing so better serve the “I’ll fix it later” school of coding? For web work, a shame.css or kludge.js exposed to those prone to view source might yield surprising positive consequences.

Here’s the example from Harry’s blog:

/**
 * Nav specificity fix.
 *
 * Someone used an ID in the header code (`#header a{}`) which trumps the
 * nav selectors (`.site-nav a{}`). Use !important to override it until I
 * have time to refactor the header stuff.
 */
.site-nav a{
    color:#BADA55!important;
}

I wonder if airing dirty laundry as such might invite contributions from developers? It seems to me to be another spin on open source yet to be explored.

Data Science in the Facebook World

Posted on by Max K Goff Posted in Big Data, Data Science

If you’re a geek and haven’t yet read Wolfram’s A New Kind of Science think of this as a goad — at least buy the tome. The basic premise is simple — specifically, that those classes of simple programs that give rise to very complex (and interesting) behaviors can and ought to point us in a different direction insofar as the philosophy of science is concerned. Wolfram advocates computational models as adjuncts to traditional mathematical models, as legitimate candidates for scientific inquiry. Methinks dear Stephen is correct. But he’s viewed as quite the radical in the more established worlds of scientific dogma. Alas, so it must be with pioneers.

How Many Facebook Friends Do You Have?

His recent blog one Data Science in the Facebook World offers a glimpse into the power of Wolfram Alpha and, at the very least, lets you know how many Facebook friends you ought to have if attaining some level of mediocrity is an objective your harbor.

Dude, Who Printed My Car?

Posted on by Max K Goff Posted in Big Data, Data Science, Platforms & Tools

Wow. A car, printed via 3-D printing technology, making the NY to SF sojourn on 10 gallons of gas! Today’s article on Wired has got to be a mind blowing, hope radiating, consciousness expanding trip!

The 3-D Printed Car

JavaScript Idea Goose

Posted on by Max K Goff Posted in Big Data

I’m working with my fellow Rotarians at Club 24 on a fundraising event.

Club 24 is over 100 Years Old — yet we don’t have an annual fundraiser that we can call our signature event. So we’ve been brainstorming. As part of that process, I thought I’d jot down the general list of some of the ideas we’ve come up with so far, to create a bit of an Idea Goose to help us along.

My first thought was to start with a “Wheel Of Fortune” type of pattern, like the very cool one from Andrew Brampton’s blog. But thinking about the multiple variables involved, I decided that starting out with a good old slot machine approach made most sense. After poking around for a quick foundation upon which to build, I found an experiment by Matthew Lein, a copy of which I forked from github, to be the easiest to morph into the Idea Goose.

I’d have posted the code for the Goose below on github, were it not for the fact that it’s more of a major paring down of Matthew’s awesome work than it is a legitimate extension. It’s easy enough to download the sources — for those who are interested, click here to open the url referenced from the wordpress iframe widget displayed below — everything you need is there with very little obfuscation.

I hope my fellow Rotarians from Club 24 find the Idea Goose fun and useful. Enjoy!

The Idea Goose



A Decade of E-Commerce Growth

Posted on by Max K Goff Posted in Big Data, Platforms & Tools

The Network Age demands improved modes of learning and communication. By presenting information in compact, creative formats, infographics are able to quickly convey knowledge and engage us. Infographics are visual presentations meant to communicate complex information quickly and clearly.

A litany of online tools make infographic creation easy. This particular one was produced using infogram.

Today there are some 2.4 billion Internet users in the world. (source: Internet World Statistics)

Of those users, some 85% have shopped online. (source: Nielsen Global Survey)

That means that we are now at about 2 billion people who have purchased online — and about half of those have bought something online in the last 30 days!

Is it any wonder that e-commerce sales for 2013 will be well north of $1 trillion? (source: Venture Beat)

The inforgraphic below captures that data in a concise and easy to understand format — using a free (beta) service.


BSD-E-Commerce-infogr-am

created using infogr.am


Get some inforgr.am!

E-commerce and Big Data

Posted on by Max K Goff Posted in Big Data, Platforms & Tools

One of the major pillars of e-commerce is the web store — that virtual shopping garden through which an estimated $230 billion will flow in 2013. Lots and lots of online stores compete for their share of the still-growing e-commerce market.

So how does one start an e-commerce venture, i.e.: a store?

There are three basic approaches:
1. Write the code from scratch.
2. Open a domain-hosted store.
3. Use a framework.

With #1 comes the advantages of more control (or at least the hope of that), but the burden of having to write a lot of code. From initial idea to first sale could mean months of development work just to get rudimentary features ready for a production environment.

The second option is viable, as long as you’re okay with being the step-child of Amazon, Ebay, or Yahoo, or one of the lessers. Your store may never have the serious cachet or bragging rights as a stand-alone site, but if what matters most is getting started quickly, then go for it.

Door number 3 is the approach taken by hundred of thousands of Internet entrepreneurs. Over the last 10 years the emergence of a bunch of very viable opensource e-commerce frameworks has made it easier than ever to open that store for business.

So what does this have to do with Big Data?

Big Data isn’t magic. It’s not that very different from old-fashioned data. Actually, it’s just data — it’s just that there’s a lot more of it being produced a lot faster than ever … distributed, accessible, and increasingly important for e-commerce. Big Data means access and analysis using innovative new tools. E-commerce wants to play with those tools. With the three basic approaches listed above, all three will have a need for and relationship with Big Data. All three approaches present different opportunities and challenges in doing so.

Before you launch your Big Idea e-commerce venture in the salad days of Big Data, the question to asks, “Which of the three approaches will serve me best?” And an increasingly important part of the answer will be how well the approach nurtures your own relationship with Big Data.

The Retailer’s Guide to Big DataMonetate Marketing Infographics

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Big Data University

Posted on by Max K Goff Posted in Big Data

Via Big Data University IBM offers free introductory courses for Hadoop fundamentals, some rudimentary text analytics, and their SmartCloud cluster management services. SmartCloud to initiate and administer a Linux cluster on Amazon’s AWS is decent.

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trait Friendly { def greet() = “Salutations Terra!” }

Posted on by Max K Goff Posted in Big Data, Data Science, Platforms & Tools

With a nod to Kernighan & Ritchie, Big Smart Data begins. The intent of this site is to seek out, organize, explore and understand a layer of software infrastructure characterized by clusters of cooperative processors, machine learning, the wisdom of the crowd, data science, and more.

The theme song of the Network Age is exponential growth.

Intel (among others) asserts that Moore’s Law is good for at least another decade. But data production grows even faster. The growth rate of two of the three V’s of big data (velocity, volume, and variety) eclipses that of Moore.  It might be hype, mere buzz words, or true tipping point, but we are in the Big Smart Data phase … and the stack is evolving.

So, hello world!

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