Placing a value on a company is always a tricky business. History is filled with examples of disastrous valuations that are hard to credit in retrospect. The dotcom bubble of the late 90s is one of the best known examples.

And yet crazy valuations continue apace. One current bubble involves social media companies such as LinkedIn, Twitter, Groupon and, of course, Facebook. In July, the latter announced that it had 750 million users, an astronomical number that is dwarfed only by the company’s valuation which stands at anything from $65 billion to north of $100 billion.

By that measure, the company’s current and future users will each have to generate a remarkable amount of income for the company, numbers that reek of the boom and bust economics of the dotcom era.

So how much is Facebook really worth? Today, Peter Cauwels and Didier Sornette, econophysicists at the Swiss Federal Institute of Technology in Zurich, inject a little sanity into the debate. They argue that it is actually easier to value social media companies than other firmS because their revenue is so obviously based on a singe simple metric: the number of users.

All that is required is a reasonable model of user growth and a good understanding of the profit each user can generate.

For Facebook, user growth is pretty straightforward. Cauwels and Sornette argue that although Facebook’s growth has been exponential in the past, this cannot continue if only because of the finite number of people on the planet. Instead, Facebook user numbers will eventually level off, following a classic s-shaped curve.

Indeed, they say Facebook’s growth has already changed. In 2010, they say it switched from exponential to s-shaped.

The only question now is how high it will reach. Cauwels and Sornette offer three scenarios in which Facebook eventually plateaus at a base case of 840 million, a high growth case of 1.1 billion or a case of extreme growth reaching 1.8 billion users within a few years.

Cauwels and Sornette then calculate a value for the company based on the prospect of each user generating $1 profit per year, the approximate average over the last five years. This gives a value in the base case of $15 billion, in the high growth case of $20 billion and in the extreme growth case of $33 billion.

{ The Physics arXiv Blog | Continue reading }

When tracked against the admittedly lofty hopes of the 1950s and 1960s, technological progress has fallen short in many domains. Consider the most literal instance of non-acceleration: We are no longer moving faster. The centuries-long acceleration of travel speeds — from ever-faster sailing ships in the 16th through 18th centuries, to the advent of ever-faster railroads in the 19th century, and ever-faster cars and airplanes in the 20th century — reversed with the decommissioning of the Concorde in 2003, to say nothing of the nightmarish delays caused by strikingly low-tech post-9/11 airport-security systems. Today’s advocates of space jets, lunar vacations, and the manned exploration of the solar system appear to hail from another planet. A faded 1964 Popular Science cover story — “Who’ll Fly You at 2,000 m.p.h.?” — barely recalls the dreams of a bygone age.


The official explanation for the slowdown in travel centers on the high cost of fuel, which points to the much larger failure in energy innovation. (…)

By default, computers have become the single great hope for the technological future. The speedup in information technology contrasts dramatically with the slowdown everywhere else. Moore’s Law, which predicted a doubling of the number of transistors that can be packed onto a computer chip every 18 to 24 months, has remained broadly true for much longer than anyone (including Moore) would have imagined back in 1965. We have moved without rest from mainframes to home computers to the Internet. Cellphones in 2011 contain more computing power than the entire Apollo space program in 1969.


{ National Review | Continue reading }

Back in the day, when bad guys used telephones, the FBI and other law enforcement agencies would listen in with wiretaps. As long as phone companies cooperated—and they had to, by law—it was a relatively straightforward process. The Internet, however, separated providers of communications services—Skype, Facebook, Gmail—from those running the underlying infrastructure. Thus, even if the FBI obtains a suspect’s traffic data from their Internet service provider (ISP)—Comcast, Verizon, etc.—it may be difficult to make sense of it, especially if the suspect has been using encrypted services. This loophole has not been lost on child pornographers, drug traffickers, terrorists, and others who prize secret communications.

To catch up with the new technologies of malfeasance, FBI director Robert Mueller traveled to Silicon Valley last November to persuade technology companies to build “backdoors” into their products. If Mueller’s wish were granted, the FBI would gain undetected real-time access to suspects’ Skype calls, Facebook chats, and other online communications

{ Boston Review | Continue reading }

The patent world is undergoing a change of seismic proportions. A small number of entities have been quietly amassing vast treasuries of patents. These are not the typical patent trolls that we have come to expect. Rather, these entities have investors such Apple, Google, Microsoft, Sony, the World Bank, and non-profit institutions. The largest and most secretive of these has accumulated a staggering 30,000-60,000 patents.

{ SSRN | Continue reading }

images { 1 | 2 }

An Australian technology expert has discovered Facebook tracks the websites its users visit after they leave the social networking site. Nik Cubrilovic said his tests showed Facebook did not delete its tracking cookies when you logged out but modified them, maintaining account information and other unique tokens that could identify you.

So whenever you visited a web page containing a Facebook button or widget, your browser was still sending the details back to Facebook, said Mr Cubrilovic. “Even if you are logged out, Facebook still knows and can track every page you visit,” he wrote in a blog post. “The only solution is to delete every Facebook cookie in your browser, or to use a separate browser for Facebook interactions.”

{ Sydney Morning Herald | Continue reading }

Facebook filed paperwork today to start FB PAC, a political action committee that will support candidates dedicated to protecting the online privacy of ordinary Americans at any cost. Kidding! The PAC will fund candidates who support “giving people the power to share,” i.e. stripping them of what few government privacy protections remain.

{ Gawker | Continue reading }

{ If you are wondering why Tumblr just raised $85 million, all you have to do is look at its pageviews. | Tumblr, Now Bigger Than Wikipedia | The Porn and Spam Behind Tumblr’s Meteoric Rise }

With the growing permeation of online social networks in our everyday life, scholars have become interested in the study of novel forms of identity construction, performance, spectatorship and self-presentation onto the networked medium. This body of research builds upon a rich theoretical tradition on identity constructivism, performance and (re)presentation of self. With this article we attempt to integrate the work of Italian playwright Luigi Pirandello into this tradition.

Pirandello’s classic 1925 novel Uno, Nessuno, Centomila (“One, No One and One Hundred Thousand”) recounts the tragedy of a man who struggles to reclaim a coherent identity for himself in the face of an inherently social and multi-faceted world. Via an innocuous observation of his wife, the protagonist of the novel, Vitangelo Moscarda, discovers that his friends’ perceptions of his character are not at all what he imagined and stand in glaring contrast to his private self-understanding. In order to upset their assumptions, and to salvage some sort of stable identity, he embarks upon a series of carefully crafted social experiments.

Though the novel’s story transpires in a pre-digital age, the volatile play of identity that ultimately destabilizes Moscarda has only increased since the advent of online social networks. The constant flux of communication in the online world frustrates almost any effort at constructing and defending unitary identity projections. Popular social networking sites, such as Facebook and MySpace, offer freely accessible and often jarring forums in which widely heterogeneous aspects of one’s life—that in Moscarda’s era could have been scrupu- lously kept apart—precariously intermingle. Disturbances to our sense of a unified identity have become a matter of everyday life.

Pirandello’s prescient novel offered readers in its day the contours of an identity melee that would unfurl on the online arena some 80 years later.

{ Alberto Pepe, Spencer Wolff & Karen Van Godtsenhoven, Re-imagining the Pirandellian Identity Dilemma in the Era of Online Social Networks | PDF }

It looks like the future is finally here. I wasn’t quite sure how it was going to present itself, but it seems to have come in the form of UC Berkeley scientists who have developed a “decoder” that can measure our brain activity and reconstruct our visual experiences. In other words, 20 years from now we might not ask eye-witnesses to describe a suspect… we’ll just analyze their brain activity and reconstruct the suspect’s image for ourselves.

{ Try Nerdy | full story }

photo { Howard Bond, Car Hood I, Ontario, 1984 }

There are four ways to deal with system damage: 1) reliability, 2) redundancy, 3) repair, and 4) replacement.

{ Overcoming Bias | Continue reading }

photo { Dylan Collard }

Yahoo has a bureaucracy problem that I attribute to former CEO Terry Semel, who hired legions of vice presidents. (…) Since Semel didn’t seem to get what Yahoo was about, he hired lots of people to keep him from having to personally deal with it.

Here’s how my friend Randy put it: “My beef with Yahoo is that they have way too many layers (I might have the exact titles wrong, but the number of layers is right) — associates, senior associates, managers, senior managers, directors, senior directors, general managers, VPs, SVPs, EVPs, regional presidents. This is absolutely crazy. They have more VP-level employees than you could ever imagine. Their product and engineering talent sits under all of these layers. It’s no wonder they’re not a technology company anymore. That’s what they need to fix first — flatten the company. Firing a bunch of senior execs who can’t get it done and not replacing them would go a long way.”

{ Robert X. Cringely | Continue reading }

A fundamental difficulty in artificial intelligence is that nobody really knows what intelligence is, especially for systems with senses, environments, motivations and cognitive capacities which are very different to our own.

Although there is no strict consensus among experts over the definition of intelligence for humans, most definitions share many key features. In all cases, intelligence is a property of an entity, which we will call the agent, that interacts with an external problem or situation, which we will call the environment. An agent’s intelligence is typically related to its ability to succeed with respect to one or more objectives, which we will call the goal. The emphasis on learning, adaptation and flexibility common to many definitions implies that the environment is not fully known to the agent. Thus true intelligence requires the ability to deal with a wide range of possibilities, not just a few specific situations. Putting these things together gives us our informal definition: Intelligence measures an agent’s general ability to achieve goals in a wide range of environments. We are confident that this definition captures the essence of many common perspectives on intelligence. It also describes what we would like to achieve in machines: A very general capacity to adapt and perform well in a wide range of situations.

{ Shane Legg and Marcus Hutter | Continue reading | PDF }

Artificial general intelligence (AGI) refers to research aimed at tackling the full problem of artificial intelligence, that is, create truly intelligent agents. This sets it apart from most AI research which aims at solving relatively narrow domains, such as character recognition, motion planning, or increasing player satisfaction in games. But how do we know when an agent is truly intelligent? A common point of reference in the AGI community is Legg and Hutter’s formal definition of universal intelligence, which has the appeal of simplicity and generality but is unfortunately incomputable. (…)

Intelligence is one of those interesting concepts that everyone has an opinion about, but few people are able to give a definition for – and when they do, their definitions tend to disagree with each other. And curiously, the consensus opinions change over time: consider for example a number of indicators for human intelligence like arithmetic skills, memory capacity, chess playing, theorem proving – all of which were commonly employed in the past, but since machines now outperform humans on those tasks, they have fallen into disuse. We refer the interested reader to a comprehensive treatment of the subject matter in Legg (2008).

The current artificial intelligence literature features a panoply of benchmarks, many of which, unfortunately, are very narrow, applicable only on a small class of tasks. This is not to say that they cannot be useful for advancing the field, but in retrospect it often becomes clear how little an advance on a narrow task contributed to the general field. For example, researchers used to argue that serious progress on a game as complex as chess would necessarily generate many insights, and the techniques employed in the solution would be useful for real-world problems – well, no. (…)

Legg and Hutter propose their definition as a basis for any test of artificial general intelligence. Among the advantages they list are its wide range of applicability (from random to super-human), its objectivity, its universality, and the fact that it is formally defined.

Unfortunately however, it suffers from two major limitations: a) Incomputability: Universal intelligence is incomputable, because the Kolmogorov complexity is incomputable for any environment (due to the halting problem). b) Unlimited resources: The authors deliberately do not include any consideration of time or space resources in their definition. This means that two agents that act identically in theory will be assigned the exact same intelligence Υ, even if one of them requires infinitely more computational resources to choose its action (i.e. would never get to do any action in practice) than the other.

{ Tom Schaul, Julian Togelius, Jürgen Schmidhuber, Measuring Intelligence through Games, 2011 | Continue reading | PDF }

ICANN, the Internet’s ruling body, is going to allow anyone to create a new Top Level Domain (…) allowing anyone with $200,000 to become a provider of everything from .eco to .gucci.

Existing top level domains — .com, .org, etc. — have become crowded. It’s as if the inventors of the Internet never imagined that the metropolis represented by .com could ever fill up. But so it has — and, for the most part, with some rather unseemly characters.

{ Mims’s Bits | Continue reading }

This article looks at how previous practice of portraiture prepared the way for self-presentation on social networking sites. A portrait is not simply an exercise in the skillful or “realistic” depiction of a subject. Rather, it is a rhetorical exercise in visual description and persuasion and a site of intricate communicative processes. A long evolution of visual culture, intimately intertwined with evolving notions of identity and society, was necessary to create the conditions for the particular forms of self-representation we encounter on Facebook. Many of these premodern strategies prefigure ones we encounter on Facebook. By delineating the ways current practices reflect earlier ones, we can set a baseline from which we can isolate the precise novelty of current practice in social networking sites. (…)

Although a Velasquez portrait does not look much like a Facebook page, it fulfills many of the same functions. A portrait by Velasquez, hanging in the grand palace of Madrid, articulates an image of royal power and privilege to those permitted to view it, and thus reinforces the sitter’s right to certain prerogatives and respects.

{ SAGE | Continue reading }

In a bizarre repeat of a high-profile incident last year, an Apple employee once again appears to have lost an unreleased iPhone in a bar.

Last year, an iPhone 4 prototype was bought by a gadget blog that paid $5,000 in cash. This year’s lost phone seems to have taken a more mundane path: it was taken from a Mexican restaurant and bar and may have been sold on Craigslist for $200. Still unclear are details about the device, what version of the iOS operating system it was running, and what it looks like.

{ CNET | Continue reading }

The Apple idea is that instead of the personal computer model where people own their own information, and everybody can be a creator as well as a consumer, we’re moving towards this iPad, iPhone model where it’s not really as adequate for media creation as the real media creation tools, and even though you can become a seller over the network, you have to pass through Apple’s gate to accept what you do, and your chances of doing well are very small, and it’s not really a person to person thing, it’s a business through a hub, through Apple to others, and it doesn’t really create a middle class, it creates a new kind of upper class. (…)

Google has done something that might even be more destructive of the middle class, which is they’ve said, ‘Well, since Moore’s law makes computation really, really cheap, let’s just give away the computation, but keep the data.’ And that’s a disaster.

If we enter into the kind of world that Google likes, I mean, the world that Google wants is a world where information is copied so much on the Internet that nobody knows where it came from anymore, so there can’t be any rights of authorship. However, you need a big search engine to even figure out what it is or find it. They want a lot of chaos that they can have an ability to undo. (…) When you have copying on a network, you throw out information because you lose the provenance, and then you need a search engine to figure it out again. That’s part of why Google can exist.

{ Jaron Lanier/Edge | Continue reading }

It’s email, it’s the Internet, it’s video games, then when texting comes along, it’s texting, and when social networking comes along, it’s social networking. So whatever the flavor of the month in terms of new technologies are, there’s research that comes out very quickly that shows how it causes our children to be asocial, distracted, bad in school, to have learning disorders, a whole litany of things.

And then the Pew Foundation and MacArthur Foundation started saying, about three or four years ago: “Wait, let’s not assume these things are hurting our kids. Let’s just look at how our kids are using media and stop with testing that’s set up from a pejorative or harmful point of view.” (…)

The phenomenon of attention blindness is real — when we pay attention to one thing, it means we’re not paying attention to something else. When we’re multitasking, what we’re actually really doing is what Linda Stone calls “continuous partial attention.” We’re not actually simultaneously paying equal attention to two things: One of the things that we’re doing is probably being done automatically, and we’re sort of cruising through that, and we’re paying more attention to the other thing. Or we’re moving back and forth between them. But any moment when there is a major new form of technology, people think it’s going to overwhelm the brain. In the 1930s there was legislation introduced to prevent Motorola from putting radios in dashboards, because it was thought that people couldn’t possibly cope with driving and listening to the radio. (…)

We used to think that as we get older we develop more neural pathways, but the opposite is actually the case. You and I have about 40 percent less neurons than a newborn infant does. (…) They are learning to process that kind of information faster. That which we experience shapes our pathways, so they’re going to be far less stressed by a certain kind of multitasking that you are or than I am, or people who may not have grown up with that.

{ Interview with Cathy N. Davidson | Salon | Continue reading }

illustration { Geneviève Gauckler }

Historically, the two main types of obstacles to information discovery have been barriers of awareness, which encompass all the information we can’t access because we simply don’t know about its existence in the first place, and barriers of accessibility, which refer to the information we do know is out there but remains outside of our practical, infrastructural or legal reach. What the digital convergence has done is solve the latter, by bringing much previously inaccessible information into the public domain, made the former worse in the process, by increasing the net amount of information available to us and thus creating a wealth of information we can’t humanly be aware of due to our cognitive and temporal limitations, and added a third barrier — a barrier of motivation. (…)

If we somehow stumble upon an incredible archive of, say, digitized “rare” vinyl LP’s or unpublished manuscripts by a famous author, and it tickles our fancy, perhaps we bookmark it, perhaps we save it to Delicious or Instapaper, perhaps we take a quick skim, but more likely than not, we shove it into some cognitive corner and fail to spend time with it, exploring and learning, assuming that it’s just there, available and accessible anytime. The relationship between ease of access and motivation seems to be inversely proportional because, as the sheer volume of information that becomes available and accessible to us increases, we become increasingly paralyzed to actually access all but the most prominent of it — prominent by way of media coverage, prominent by way of peer recommendation, prominent by way of alignment with our existing interests. This is why information that isn’t rare in technical terms, in terms of being free and open to anyone willing to and knowledgeable about how to access it, may still remain rare in practical terms, accessed by only a handful of motivated scholars.

{ Nieman Journalism Lab | Continue reading }

There’s one prediction about driverless cars that I can make with confidence: If millions of them ever roam the public highways, they will be far safer than cars driven by people. My confidence in this assertion does not derive from mere faith in technology. It’s just that if robotic drivers were as dangerous as human ones, then computer-controlled cars would never be allowed on the roads. We hold our machines to a higher standard than ourselves.

Over the past decade, the number of auto accidents in the United States—counting only those serious enough to be reported to the police—has been running at about six million a year. Those accidents kill about 40,000 people and injure well over two million more. Estimates of the economic impact are in the neighborhood of $200 billion. Much of that cost is shared among car owners through premiums for auto insurance.

This safety record certainly leaves ample room for improvement. An appropriate goal for automated vehicles might be to reduce highway carnage to the same order of magnitude experienced in other modes of transport, such as railroads and commercial aviation. That would mean bringing road fatalities down to roughly 1 percent of their current level—from 40,000 deaths per year to 400. (In terms of deaths per passenger mile, cars would then be the safest of all vehicles.)

{ Scientific American | Continue reading }

I thought the purpose of patents was to spur innovation by giving people who invent something the exclusive use of their innovation for a limited time.

There’s still some of that. But out in Silicon Valley, patents have become the competitive weapon of choice, used by high-tech giants to bludgeon rivals and crush upstarts.

It turns out that the more patents you have, the more likely it is that you can extort exorbitant royalties from people who might have easily come up with the same idea or the same feature that you did but never thought to patent it. And the more patents you have, the more your competitor wants so he can retaliate with a patent suit of his own, claiming that it was you who stole the ideas from him.

{ Washington Post | Continue reading }

{ Face recognition technology can reveal much more than your image. Researchers could identify people based on nothing more than a photo, as well as predict part of their Social Security numbers. }