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September 24 2012

What caused New York’s startup boom?

Google's New York officeGoogle's New York officeSince the crisis of 2008 New York City’s massive financial sector — the city’s richest economic engine, once seen to have unlimited potential for growth — has languished. In the meantime, attention has turned to its nascent startup sector, home to Foursquare, Tumblr, 10gen, Etsy and Gilt, where VC investment has surged even as it’s been flat in other big U.S. tech centers (PDF).

I’ve started to poke around the tech community here with a view toward eventually publishing a paper on the rise of New York’s startup scene. In my initial conversations, I’ve come up with a few broad questions I’ll focus on, and I’d welcome thoughts from this blog’s legion of smart readers on any of these.

  • How many people in New York’s startup community came from finance, and under what conditions did they make the move? In 2003, Google was a five-year-old, privately-held startup and Bear Stearns was an 80-year-old pillar of the financial sector. Five years later, Google was a pillar of the technical economy and among the world’s biggest companies; Bear Stearns had ceased to exist. Bright quantitatively-minded people who might have pursued finance for its stability and lucre now see that sector as unstable and not necessarily lucrative; its advantage over the technology sector in those respects has disappeared. Joining a 10-person startup is very different from taking a job at Google, but the comparative appeal of the two sectors has dramatically shifted.
  • To what degree have anchor institutions played a role in the New York startup scene? The relationship between Stanford University and Silicon Valley is well-documented; I’d like to figure out who’s producing steady streams of bright technologists in New York. Google’s Chelsea office, opened in 2006, now employs close to 3,000 people, and its alumni include Dennis Crowley, founder of Foursquare. That office is now old enough that it can generate a high volume of spin-offs as Googlers look for new challenges. And Columbia and NYU (and soon a Cornell-Technion consortium) have embraced New York’s startup community.
  • Does New York’s urban fabric make its labor market more liquid? Changing jobs in Silicon Valley can mean an extra 40 minutes on your commute if you have to slog up the 101 during rush hour. New York’s main business districts are much more compact; if you change jobs from a bank in Midtown to a startup on 28th Street, your commute won’t change by more than 10 minutes.
  • What are the dominant practice areas in New York’s tech scene, and how do they relate to the human capital available here? Have refugees from the finance, media and advertising industries brought with them distinctive skills from those areas? How much of the startup community here is targeted at acquiring those industries as clients?
  • What’s the city doing in response to the growth of its tech industry, and what can other cities learn from New York’s model? Other old, established cities like Chicago, Pittsburgh, Philadelphia and Washington claim to have robust startup communities. What do these cities have in common, and how have their governments reacted to the emergence of their tech communities? The emergence of a tech startup scene here could be particularly fortunate for New York in light of its dependence on the finance industry (at the peak of the finance boom, the industry contributed 20% and 13% of New York State’s and City’s income tax revenues, respectively; those figures in 2011 were 14% and 7%). To what degree can a city or state government desperate for diversification bring a startup community into existence?

Send along any ideas in the comments below!

September 16 2011

02mydafsoup-01

P2P Foundation » Blog Archive » P2P Essay of the Year? The Radical Implications of a Zero Growth Economy - 2011-09-15



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commentary by oAnth:

Generally I would like to state, that sustainable growth in future is no more to describe simply by the amount of produced goods, but in the efficient differentiation from energy sources as well as the circular use of commodities.

The article neglects a lot of recent developments in energy support technologies, which might guarantee a much higher sustainability than the traditionally centralized energy supply, like burning all forms of carbon and waste or nuclear based energy centrals.


Further insists the article IMO too much on data given by a supposed status quo (I remember that e.g. the FAO comes to quite other conlusions), and proposes as alternative a kind of subsistence economy, which in its use today is historically to see as a socially useful last remain at the country side e.g. in South Europe of a feudal society economy (supposedly with commons). This income source today is nevertheless depending on a centralized industrial production economy, and by this on the incomes of family members (away in other parts of the countries, or in work migration), which are not in particular a part of the subsistence economy household and are supporting still by a monthly amount of money parents, brother, sister, working in the  subsistence unit. Means, in those countries, where it is still in use, it has the function of a kind of social assurance, but hardly as a basic economic factor [ cf. actual tendencies in Greece of unemployed populations to return from Athens to the country side, where family members have still a smaller business or some (minor) agriculture].


I can't see how a world population would reduce its means in such a way, taking in account, that industrial production of any kind would be technological restricted in its development in order to keep the technological concurrence between all market participants in a constant balance to avoid any uncontrolled innovation impulses, from which could result again unwanted growth. etc. etc.


oAnth - Muc - 2011-09-16

April 12 2011

Big data: Global good or zero-sum arms race?

Last month, Netezza CEO Jim Baum gave a talk at the GigaOM big data event. If I'm honest, I was checking my email and missed most of it, but I do remember tuning in just in time to hear him say something like "big data is going to have a huge economic impact."

I spend most of my days considering how the component pieces of this big data transformation will impact the corporate enterprise. Baum's comment got me thinking, though, about a more meta question: Is "big data" a key to some kind of industrial revolution reboot? Or, is it just going to be expensive table stakes for previously simple-to-understand businesses?

For 200-plus years the industrial revolution* has been a kind of Moore's law of human productivity. Over that period our economic output per person has been growing like clockwork, and whatever you think of the various political -isms that sprung from industrialization, this march of productivity has pulled a lot of people out of poverty and is cause for the first sustained increase in wealth across human history.

But like Moore's law in a single core, our industrial revolution in advanced economies is kinda playing out. Our economy has been shifting for some time toward services that are proving to be impervious to order-of-magnitude productivity gains. The thousand-fold increases in productivity we saw on the farm and in the factory just don't seem likely to happen in health care and other service intensive sectors.

Of course our economy continues to grow, but at a rate that is staying just a skosh ahead of population growth. And since the top 1% are taking all of that (and perhaps more), for the first time in American history parents are worrying that their kids won't have opportunities better than their own. Voila! There stems the populist anger that feeds the Tea Party.

That's the U.S.-centric view. Of course on a global basis there is tremendous growth as late-stage industrial revolution innovations are applied with vigor to developing economies. The 8% growth rates many countries are achieving will double their population's wealth every 10 years. But for the U.S., achieving growth requires parallelism. Of course, in this context we call it globalism and it means if we can't be more productive in one place, we have to take advantage of modern communications to do it in a bunch of other cheaper places. The problem is, after a few decades of those 8% overseas growth rates, there will be less comparative advantage for us to take advantage of and if we want continued economic growth, we really will need to find ways to be more productive.

So, that's why Baum's comment stuck in my head.

At the risk of way over generalizing, so far "big data" has mostly been about behavioral analysis to better target ads. Is that what Baum meant? That more effectively matching producer and consumer long tails through precision ad placement is going to fundamentally change the economy? That type of matching can promote economic activity, which is good, but I don't see the link to fundamentally improved productivity. If this kind of innovation pulls another tranche of the bell curve out of poverty it will do it by putting more people to work doing the same stuff, not by making our economy fundamentally more efficient.

When I heard "huge impact on the economy," my first thought was maybe it's just a throw-away comment. Maybe he just meant the economy as seen through the narrow lens of his company revenues. But then I tried to think about this on a deeper level: What's here that I haven't considered? Could he somehow be saying that this is a catalyst for the next big phase of productivity growth in our 200-year-old industrial revolution? Is this the industrial revolution equivalent of nanometer chip design, which starts the next decade of doubling? Is it the thing that gets the middle class growing again and eases all this populist anger?

Yeah, that might sound kind of absurd, but that's how my head works — a daily stream of ADHD-fueled big dreams immediately dashed on the rocks of reality.

(As an aside, half way through writing this I came across a prediction of the "wine and roses" we'll all experience with this "New Information Age." Don't sweat the death of privacy, the surveillance state is highly unlikely.)

So, back to the question: Is big data an economic driver or just a must-have to be in the game?

As early as the 1950s it was obvious that robotic automation was going to fundamentally change manufacturing. As automobiles increasingly were built by robotic labor, the industry saw incredible productivity gains. The hours of human labor per automobile dropped by orders of magnitude over the next 30 years. Naturally, cars didn't just get cheaper, they also got more complex and feature-rich. But anyone could understand the return on capital of installing robotic lines. What's the return on capital look like for a Hadoop cluster?

It's worth noting that robots didn't just increase productivity, they also reshaped labor's relationship with management. If you're labor, competing with a robot sucks. This was presciently described by Norbert Weiner in his classic "The Human Use of Human Beings, Cybernetics and Society." Of course we don't need history's warning to know that big data might have a dark side, too. If you don't see it now, you will when you download a new car stereo software version and it resets all your radio station presets based on Toyota's notion of people like you. Of course, for a car company to be as obnoxious as your software and search bar providers have long been, they have to learn as much about you as those software guys do, and that's weird. We aren't really used to the idea of a manufacturer knowing where we go and who we go there with.

There obviously are places where large-scale data and analysis will improve efficiencies and productivity. Particularly in areas like smart grid, where it will reduce the investment necessary in power plant construction, or financial services, where it promises to help fight fraudulent transactions. What else? Are there big opportunities for order-of-magnitude productivity gains out there that come to mind? Or is most of the value created by this "new information age" going to be in some mushy upper region of Maslow's hierarchy? Some kind of middle class feel-good machine that remains completely irrelevant to the working poor dreaming of their first homes?

Norbert Weiner was concerned that automation-based productivity gains would disrupt the working man and woman's living. He held that concern in the face of the obvious and compelling productivity gains that were sure to flow through to GDP as wealth.

As we enter the big data era of the information age and give up what's left of our privacy, I'd like to think that it will be for more than a zero-sum game of musical chairs to decide the next winners.

* For the purposes of this post, I'm treating the industrial age and the information age as two parts of one continuum.

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