Category: Tech news

Augmented reality (AR) — the term does not exactly jump off the tongue. But the concepts behind the technology are beginning to change what we think of ourselves, objects and the people in the world that surround us.

I am no expert on AR but over the past few months I have seen enough examples of the way mobile devices change our reality to start wondering if what I am looking at is really what I think it is. With Google Glass people will see a data layer that is not visible to the human eye. Through an iOS or Android device, a person can now use apps to provide a different context for playing games, monitoring environments or tracking one’s brain activity.

I asked people developing technology for the AR world what they emerging. Here’s what they said:

Vikas Reddy, Co-Founder of Occipital wrote in an email interview that AR has not quite lived up to its potential due to the lacking capability to track and map the real world. But as computer vision algorithms and hardware improve, the camera will become the most important sensor and input mechanism not just for AR but for all computing:

Think about how much visual information each person processes on a daily basis while going about their lives. Almost none of this information is accessible for computation … yet.

Today, your smartphone’s computational reach into its surroundings end at its touchscreen surface. To your device, the real world isn’t a canvas of interactivity. Soon, however, computer vision will be used to make real-world environments computationally interactive and fun, thereby extending the computational reach of your device into the visual space around you.

At the Blur Conference, Sphero CEO Paul Berberian gave me a demo of a new game called “Sharky the Beaver,” which TechCrunch’s Romain Dillet wrote about earlier this month. Sharky is essentially a robotic ball that serves as a rolling marker. The user controls the ball through a Bluetooth-enabled device. As the ball rolls across the floor, the user sees Sharky bounce around eating cupcakes. By creating two streams of data, the experience goes between the real world and the virtual one fairly seamlessly.

Sharky is available to developers as an SDK. A likely outcome is a library of avatars that people control via the little, flashing robotic balls. For instance, a furniture company may create a network of avatars that people can use to see how tables and chairs look by rolling the ball around the living room.

I also had the chance to talk at Blur with InteraXon Co-Founder Ariel Gartern about the company’s brain-sensing headband that allows your brainwaves to serve as a way for monitoring concentration levels or as a means for controlling window shades or the lights in a house. Its first in-house app helps with brain fitness for “better attention skills, improving your memory, reducing anxiety, building a more positive attitude and staying motivated.”

Chris Aimone, InteraXon’s CTO told me in an email how this form of technology intersects with AR.

There are a number of excellent ways that brainwaves and AR fit together. There are predominantly two kinds of AR that people refer to: glass style AR, where one wears a pair of glasses and the world is augmented or mediated on the screen; and iPhone-camera type AR, where one holds up an iPhone and new layers are added to a scene.

Google glass-style AR provides the opportunity for collecting brainwave data because you have a continuous-wear device that can continuously record brainwave signals. Adding brainwaves to this environment allows you to show real-time activity about you, presented all the time. For example it could continuously register and stream your level of stress throughout the workday. It also allows the computer system to do a better job of presenting contextually aware overlays. It can provide content and augmentations that take into consideration not just information informed by place or visual input, but also the context of the user. Many of these systems are “context aware,” adding the context and state of the user, thus informing what kind of information is presented and in what way it will be presented. For example, are you sleepy and therefore want information about hotels in the area? Are you cognitively mazed, so only pertinent info should be presented?

Brainwaves in an AR system also allow for real-time neuro feedback. This would allow you to know your brain state and have the opportunity to optimize it — being able to choose and be guided into the desired state as you go about your day.

But what is the future of augmented reality? Cyborg Anthropologist Amber Case and Co-Founder of Geoloqi, said augmented reality will become interesting when the barriers to creating custom objects, animations, apps and experiences is drastically lowered. Similar to Flash or the App Store, AR becomes interesting when these experiences become very personal or shared between friends.

She added:

Games and tacky 3D animations will only go so far in AR. The real measure of AR is when it solves real-world problems that may seem boring and everyday with realistic and minimal interface. When designing for AR, think of the minimum viable interface instead of the shiny one and work from there. Most AR has had the exciting “wow” factor which lasts for about 15 seconds. It is a big jump from there to useful everyday applications. Think of the interface of Google. There’s practically nothing there. It doesn’t get in the way of interaction – it causes the data to be exposed in such a way that it can be interacted with.

Bonus! If you want to think of the future of AR, think about how it can be abused or pranked with. People think about negative things, but it’s always focused on adults. Think of kids growing up with this tech with the ability to code. Think of a future in which AR bullying is a fun prank of kids that are just learning to hack and code. A bunch of kids can put an AR kick-me sign or augment some other kid and share that layer of reality with a small group of friends. Someone takes a picture and gets a bunch of upvotes from a bunch of friends. This is AR+social permissions. The person who is getting made fun of can’t see the augmentation, but they understand and have to retaliate.

The Microsoft Surface is a great kitchen computer, and sadly, that’s about it. You can tell a lot about a new product by how well you integrate it into your life, and for the Surface, the product has been largely sitting on my kitchen countertop for the past couple of weeks, except for that one time my daughter’s iPad was charging and she wanted to watch Netflix. Or that other time when I carried it to Startup Weekend, then ended up using it as a hard surface to press down on while writing with pen and paper.

Oh, Surface. You just don’t fit in. At least not for me.

This is not another Surface review, to be clear. I don’t review gadgets. We have people for that. Lots of them. Professionals. You should read those posts. This is an opinion. These thoughts have been itching inside my mind since my Surface arrived, and they’re dying to get out.

If anything, I’m biased to like the Surface. I wanted to like it, even.

I was a late switcher to Apple products. I didn’t care for the fervor that surrounded Apple, and having once worked in I.T., I was more comfortable in the Windows universe. I didn’t want to deal with the switching costs: productivity loss during the adjustment period, not ever really knowing the OS as well as I knew Windows, leaving behind software programs I had come to rely on, etc.

But the iPhone, as it turns out, was an ideal gateway drug. I switched. I learned. I adjusted. After the iPhone, came the MacBook Pro. Then an iPad. Now I’m a slave to the iPhone upgrade cycle. Today, to return to Windows feels like the same kind of struggle as leaving it ever was in the first place. But I’m predisposed to want to try on some level, if only to assuage the guilt and penalties associated with complete Apple ecosystem lock-in. (Well, complete except for that year and half using the Nexus S, and carrying an early Windows Phone 7 device for backup).

Overall, I don’t dislike Windows 8 as an operating system. Actually, there are parts of it I like very much. The Windows 8 “desktop,” for example, with its live-updating tiles is a welcome change from Apple’s incredibly boring interface involving app icons and folders. Even Google long ago out innovated Apple on this front, with Android’s customizable homescreens and widgets, live wallpapers and thumbnail-based application switcher. Apple’s iOS homescreen feels dated, and the upgrades we’re being fed (or those withheld!) are too often serving Apple’s own interests, not ours as users. Like everyone, I miss the native Google Maps app. I didn’t care for Apple’s delay on Facebook integration because the two companies couldn’t figure out how to work together. I don’t like pre-installed apps I can’t delete (like many of Apple’s native ones on iOS). I don’t like the inability to better customize the device to my own needs. (Why 12 icons in a folder? Why?!)

Windows 8 feels modern and different. The Metro design – or whatever you call it now – appeals to me. And the stripped down version known as Windows RT – the only version the Surface currently supports – is tolerable for light computing.

Now I know that a lot of ink has been shed over the ridiculousness of cramming the old-school “desktop” interface into the re-imagined Windows 8, but I can see where Microsoft felt like it had no choice in the matter in terms of supporting legacy software (and legacy users, resistant to change). Yes, it feels awkward to switch between the old and new. Jarring. But the ridiculous part to me is not legacy support – this is Microsoft! – but rather the decision to remove the “Start” menu from this old-fashioned interface. It’s like, “here’s your stupid old Windows. Now good luck using it!” [Insert evil laugh here]. Yeah, thanks a lot.

Still, while I’m attracted to the sheer “differentness” of the new Windows OS itself, one thought kept running through my head while using the Surface hardware: God, I wish I could use this OS on an iPad. And therein lies the problem. The Surface, well-built and sturdy as it may be, is a bizarre, bizarre machine.

It’s simply an awful tablet. If you remove the keyboard and try to use in portrait mode, the thing is too long and too narrow. It feels heavy because it’s too thick, despite being about on par with the iPad in weight. But if you attach the keyboard, you then have to be sitting at a desk or table where you can prop the thing up. It’s not a lap computer, which is nutty because tablet computers are for untethering you from a desk, and laptops have the word “lap” in them for a reason. Only Microsoft could come up with a way to make a tablet/laptop combo that forces you back to your desk no matter the configuration you select.

Only Microsoft could make a tablet that’s actually desktop PC.

And as a desktop PC, it’s too small for work day computing. It’s a secondary device at best. iPad users won’t buy this instead of a new iPad. Laptop users will still buy laptops. Price sensitive Android users won’t bite for the price ($499+, but unusable without a keyboard which is an extra $119 for the less expensive Touch Cover option). E-reader buyers will look for something lighter.

Who, then, is this tablet/laptop for? And where the heck are you supposed to use this thing?

As for me, the Surface sits in my kitchen. And it works pretty well there for quick web searches, email checks, recipe lookups, a little YouTube and the like. There’s no point getting into details about how well Office performs, or the lack of apps available for the Surface with Windows RT, or other details – this is an occasional use machine.

Anyway, the kitchen not the worst place for an oddball computer to end up – the PlayBook, after all, quickly became the bathroom tablet. (That thing is the perfect size for leaving on top of the toilet.) But if I were to invest in switching to Windows 8 from OS X or iOS, I go for a “real” laptop or a “real” tablet, not this odd halfling creation which is, in reality, neither.

It’s been a big year for BitTorrent, said Matt Mason, the company’s executive director of marketing. Mason and his team have been working with big names like DJ Shadow and Tim Ferriss to figure out how to turn file sharing into a source of revenue.

I met with Mason (who also wrote The Pirate’s Dilemma) last week to discuss how BitTorrent can work with the music industry and the company’s plans for next year. Mason joined BitTorrent almost exactly a year ago, and since then, the company has run a total of 16 artist campaigns. It hasn’t found the One True Solution to monetizing music yet, and Mason said the answer won’t come in the next few months, but the next quarter “will get us closer.”

Not that he actually believes in a single answer. Instead, he said BitTorrent wants to provide “the layer of tools” that artists need to monetize file sharing in whatever way makes sense for them.

“We don’t want to dictate what the business model is, because we don’t know what it is,” Mason said. “There’s not a business model for content in the digital world. There’s a new business model for every piece of content you release.”

The emphasis is very much on artist partnerships, not deals with record labels or movie studios. Since most people associate BitTorrent with illegal file sharing, I assumed the big entertainment companies want nothing to do with it, but Mason said that’s not entirely true. (He also pointed out that BitTorrent drove 124 million legal music downloads in the first six months of the year, accounting for nearly one-third of the total 405 million music downloads on BitTorrent that were tracked by Musicmetric.) The bigger problem, he said, is that the entertainment industry’s terms are too onerous: “The deals just don’t make sense.”

So BitTorrent works with artists on one-off experiments. For example, it collaborated with DJ Shadow and his digital marketing agency Fame House to create a bundle with exclusive content around his release Hidden Transmissions From The MPC Era (1992-1996), and it ran ads for free software alongside those bundles. Mason said the company wasn’t happy with the download interface, so it limited the ads to a few geographies, but even so, the campaign saw 18.5 million impressions, with 4 million people agreeing to check out the free software — an impressive conversion rate of around 21.5 percent.

Mason described another partnership where BitTorrent worked with the filmmakers behind the movie Kumaré to create a bundle of promotional content (including the first 10 minutes of the film), spurring a fan campaign that helped expand the release from a single theater to 15 cities.

Listening to Mason’s examples, I noted that they covered a lot of ground, but never involved charging the consumer directly — instead, BitTorrent drove purchases elsewhere (for example by promoting movie ticket sales or iTunes downloads) or monetized through advertising. He responded, “That’s what we’ve been able to do so far, but maybe we’re just not very good at this.” As BitTorrent expands its efforts, it could add tools for fans to pay artists directly, Mason said. At the same time, he said the company doesn’t want to repeat its past mistakes, which include an unsuccessful experiment with opening a storefront (an effort that eventually led to the company giving back its Series C and downsizing dramatically). BitTorrent needs to focus on his strength, he said, namely “moving data,” and around that core focus it aims to build whatever tools artists might need.

Mason was willing to make one generalization about the way the music industry is changing. Music was once a “fast-moving consumer good” and could be marketed accordingly, he said. Now it’s more “relationship based.” Instead of running an ad and trying to convince someone to buy a song or an album immediately, musicians need to focus on building a relationship, then in six months they can sell their fans a t-shirt or a digital download — and hopefully continue selling to those fans for the rest of their career.

But doesn’t that sound like a lot of work for relatively little reward? Mason countered that in the traditional system, convincing radio DJs to play your single wasn’t easy, either.

“It’s a hard business — only 0.1 percent of people are going to make it,” he said. “That’s always going to be true. People ask me, ‘Shouldn’t artists have all the time in the world to create great music?’ But most of the creative artists I’ve had the fortune to work with have also been great hustlers. The hustle is changing, and what it means now is understanding data.”

Short Version

The Nokia Lumia 820 is a Windows Phone 8-powered smartphone, with a generously sized 4.3-inch screen. It packs 4G/LTE and is powered by a dual-core Snapdragon chip. As well as running the latest version of Microsoft’s mobile OS, WP8, it comes loaded with Nokia apps including Nokia Maps, turn-by-turn sat-nav Nokia Drive and subscription-free music service Mix Radio.

Long Version

Features:

• 4.3 inch ClearBlack display
• Dual-core 1.5GHz Snapdragon S4 processor
• 4G/LTE
• 8-megapixel camera, Carl Zeiss lens
• Interchangeable backplates in range of colours
• Expandable memory (MicroSD card)
• Windows Phone 8 OS
• Suite of Nokia apps: Nokia Maps, Drive, City Lens, Mix Radio

Info:

• MSRP: From $50 on two-year contract/From £25 per month on two-year contract; £360 SIM-free/£380 pay-as-you-go
• Available: Now
• Retailers: AT&T (U.S.); EE, O2, Carphone Warehouse, Phones4u, Clove (U.K.)
  

The Nokia Lumia 820 is…

… a mid-range Windows Phone 8 handset made by Nokia. It’s a more affordable offering than the flagship Lumia 920. The biggest difference between the two — apart from the price — is that the camera is not quite so fancy, lacking the PureView tech that’s inside the 920 (so there are no stabilizing springs to smooth out shaky camera footage). You do still get a Carl Zeiss lens. Elsewhere the 820 offers a middling resolution (800 x 480) and a rather plain (bland) design — but you can jazz things up by opting for one of the brightly coloured backplates. It’s also possible to get a backplate with support for wireless charging. Like the 920, the 820 includes 4G and has a dual-core Snapdragon chip under the hood.

The Lumia 820 runs the latest version of Microsoft’s OS, WP8, which is built on a different kernel than Windows Phone 7. Despite this you can still run apps built for WP7. As with all of Nokia’s Windows Phone handsets, the Lumia 820 is preloaded with a suite of Nokia apps, including its fully featured sat-nav app, Nokia Drive; Nokia Maps and Mix Radio, Nokia’s subscription-free streaming music service.

Buy the Nokia Lumia 820 for…

… Windows Phone fans stuck on the wrong side of the WP7 vs. WP8 schism.

The Lumia 820 won’t wow high-end gadget fans, being as it’s a middling offering rather than a flagship handset, but it delivers almost the same software experience as the Lumia 920 for a more affordable price tag.

Because…

… the Lumia 820 is neither the slickest nor sexiest Windows Phone handset around, but it runs the latest iteration of Windows Phone so will get future OS updates. Add to that, given Nokia’s software additions — a fully featured streaming music service, sat-nav app, rich maps and more — you’re gifting a fair amount of functionality for a mid-range smartphone price.

Of course you can pick up an iPhone 4 for less, or an iPhone 4S for a similar price (not to mention the scores of app-packed Android phones available at this price range) so make sure your intended recipient is a dyed-in-the-wool Windows Phone fan.

The iPad seems to have dominated online shopping from tablets, according to an IBM report, and in fact won out over all other devices in mobile e-commerce. Arguably, that’s because it has far more market share compared to its Android rivals, and because it offers more of a full-web experience, which is more pleasant for browsing standard online retailer sites than what a smartphone screen provides. But tablet-based shopping continues to be a less than optimal experience, and it represents a largely ignored growth area where new solutions and innovative e-commerce experiences can’t come fast enough.

The state of online shopping for iPad isn’t exactly thrilling, despite the obvious market opportunity. IBM says that mobile shopping sales climbed over 6 percentage points this year, and mobile visits to e-commerce sites were made by 24 percent of all online shoppers, up a huge 10 percent form last year. Research from earlier in the year saw mobile commerce double in size in 2011, to a total of $65.6 billion. Tablets have been shown to drive more e-commerce spending than smartphones, meaning they’re the perfect target for custom experiences.

But why bother? The whole point of the iPad is that it delivers standard websites without really sacrificing usability, right? That’s true, but just because an experience does work on a platform doesn’t mean efforts should stop there.

Not that everyone’s just leaving well enough alone. Best Buy has a dedicated tablet version of its website that it serves if you visit from an iPad; Amazon has an iPad app and a more playful, experimental take on tablet commerce with its Windowshop app. But these are exceptions, rather than rules: Walmart isn’t optimized, nor is Amazon’s web experience, as just a couple of noteworthy examples.

But even the exceptions have significant drawbacks. Best Buy’s tablet experience is okay, but it does little to truly explore the benefits of the platform, and it feels a little hastily thrown together in places. Amazon’s Windowshop was a fun, novel experimental take on how tablet shopping might differ from traditional desktop web experiences when it came out in 2010, but it has remained relatively unchanged since then, and it doesn’t seem like the e-tailer learned any valuable lessons to fold back into its main portal from the effort. In other words, where Amazon originally looked to have begun building a playground to figure out the future of tablet-based retail, Windowshop actually seems to have been more of a one-trick pony.

There are startups out there that are stepping up and trying to rectify the relative stagnation of the bigger players. Shopmox is a great example. The Toronto-based startup has created an app that combines the best elements of paper and online catalogs with an interface tailored to the iPad for a shopping experience that’s actually pleasant, not just functional, on Apple’s tablet. The startup is in the process of signing up more retailer partners, CEO and co-founder Kevin Lister told me, but stores and brands should be jumping on this kind of thing faster.

There are and were good reasons for retailers to be cautious with products designed specifically for a new device category. There was definitely a chance that the consumer love affair with tablets would be short-lived, but I think nearly three years on, with no end of growth in sight, we can agree they’re not just a flash in the pan. There’s also the possibility that economic worries could put a damper on all consumer activity in the near future, including mobile commerce. But regardless of whether the market overall contracts, I think mobile will continue to make up a growing percentage of business, so if brands want to get as much of the remaining spend that’s out there, it makes sense to develop shopping experiences that shine on the devices they’re using most.

Tomorrow’s Cyber Monday, and that means we’ll probably be inundated with even more stats later this week about how much shopping was done on tablets. But I can’t help but wonder how much higher those numbers would be if more companies were actually paying proper attention to the needs of tablet shoppers, instead of taking a half-cocked, wait-and-see approach that is definitely leaving money on the table.

For your postprandial pleasure I present the an open-source vibrator that you (or your partner) can play like a theremin. The story of how it came to be is pretty amazing and involves FCC chip lookups, bit-tracing, and lots of assembly code. In short, it’s an amazing effort in DIY hardware hacking that serves the dual purpose of education and giving pleasure.

Built by Beth Scott and based on an off-the-shelf vibrator model called the Lyla, the device uses an Arduino board and sonic transducers to create an interactive, invisible cone of sound that you can move your hand through in order to control the vibrator. Writes Scott:

Scott has included the plans she used to build the device as well as the 3D models for the case and battery holder. She used the aptly-named Anker battery case and programmed the firmware to interact with various body parts.

“There could be a lot more to electronic sex toys than just a battery and a motor. I want the future to be full of toys that know how to play,” wrote Scott. Amen.

A jury might not have acquitted Casey Anthony of the ‘drowning’ death of her daughter if they knew she Googled “foolproof suffocation” on the last day little Caylee was seen alive. It’s the latest example of Google search history becoming evidence in murder case. But this time the digital footprints were found too late and the suspect has already been set free. Are police paying enough attention to browser breadcrumbs?

The death of Caylee Anthony became a media spectacle in 2011 as the nation watched her mother mislead law enforcement, yet still be found ‘not guilty’. Caylee went missing on June 16th 2008, and her body wasn’t found until December 11th in Orlando, Fla., Casey’s defense claimed Caylee had drowned, and despite being found guilty of four accounts of providing false information to police, the mother was acquitted of the first degree murder of her daughter.

During the trial, the prosecution’s experts also testified that the Anthony family computer had been used to Google words and phrases including:

• Chloroform
• Chest trauma
• Internal bleeding
• How to make chloroform
• Neck breaking

But this last week Orlando’s WKMG TV station reported that police had overlooked a key piece of evidence. Someone had Google searched “foolproof suffocation” from the Anthony family computer on June 16th, the day Caylee disappeared. A book about the case by Anthony’s defense lawyer Jose Baez had previously reported that someone made the search, but had the timing off. The book suggested Caylee’s father had Googled the murder method.

Now WKMG reports that search happened an hour later, after George Anthony may have already been at work, and that Casey is likely to have typed it in. If the mother had Googled a way to suffocate someone on the last day anyone saw her daughter alive, the jury might have concluded differently.

Google searches have already been used in several murder convictions. In 2005 Mac specialist Robert Petrick was convicted of murdering his wife after evidence surfaced that he had Googled “neck snap break,” downloaded a document named “22 ways to kill a man with your bare hands” and researched how deep the lake was where his wife’s body was later found.

In 2006, Justin Barber was sentenced to life in prison for murdering his wife on a beach. He had previously searched for ”Florida & divorce,” as well as the words trauma, gunshot, right chest, and cases. He’d also downloaded and then deleted the Guns N’Roses song “Used To Love Her” that details murdering one’s significant other. Search Engine Land has an old list of several more convictions where Google played a roll.

Yet still, the Google search history of the Anthony family computer wasn’t examined closely enough. It seems that detectives and police may benefit from greater training in digging for digital evidence. I doubt it will be long before mobile search history and other smartphone evidence starts popping up in trials. However, law enforcement will need to be careful not to violate the Fourth Amendment, which protects against unreasonable search and seizure. A murder case was overturned in September after police read a suspect’s text messages without a warrant.

Dusting for fingerprints and DNA evidence may always be critical parts of detective work. But as the ways we learn and communicate increasingly move online, forensics must evolve as well.

[Image Credit: MSNBC, JonesDykestra]

We’ve seen the reports that Black Friday online sales increased this year, but the numbers are finally in. comScore is reporting that U.S. retail e-commerce spending was $1.042 billion on Black Friday, an increase of 26 percent from Black Friday last year. This is the first time Black Friday sales surpassed $1 billion in online spending, says comScore.

For the holiday season-to-date, $13.7 billion has been spent online, which is a 16 percent increase versus the corresponding days last year. Consumers spend $633 million on Thanksgiving Day, a 32 percent increase from last year.

“Despite the frenzy of media coverage surrounding the importance of Black Friday in the brick-and-mortar world, we continue to see this shopping day become more and more prominent in the e-commerce channel – particularly among those who prefer to avoid crowds at the stores,” said comScore chairman, Gian Fulgoni, in a release.

“With Black Friday online sales up 26 percent and surpassing $1 billion for the first time, coupled with early reports indicating that Black Friday sales in retail stores were down 1.8 percent, we can now confidently call it a multi-channel marketing phenomenon. Meanwhile, Thanksgiving Day – which has historically been a lighter online holiday shopping day – continues to gain steam and grew well ahead of the current pace as more consumers opted to kick off their holiday shopping immediately after the big meal to take advantage of aggressive retailer promotions. With Thanksgiving now behind us and most consumers returning to work tomorrow, we can look forward with anticipation to Cyber Monday, which according to norms we’ve observed over the past three years should be the heaviest online shopping day of the season with sales approaching $1.5 billion or even higher.”

In terms of specific retailers, Amazon was the most popular e-commerce site by visits, followed by Walmart, Best Buy, Target, and Apple. In total, 57.3 million Americans visited online retail sites on Black Friday, representing an increase of 18 percent versus a year ago. Amazon also posted the highest year-over-year visitor growth rate among the top five retailers.

Digital Content & Subscriptions is the top-growing online retail product category (up 29 percent versus year ago). Toys are seeing a gain of 27 percent, followed by Consumer Packaged Goods (up 23 percent), Video Game Consoles & Accessories (up 18 percent) and Consumer Electronics (up 18 percent). For Black Friday, the most amount of dollars online was spent on Apparel & Accessories, accounting for more than a quarter of all dollars spent online. The category has historically ranked No. 2 behind Computer Hardware, as it did on Black Friday 2011.

It looks like signs are pointing to online spending surging on Cyber Monday (tomorrow) as well, as retailers push personalized offers and promotions. Stay tuned.

Editor’s Note: Semil Shah is an EIR with Javelin Venture Partners and has been a contributor to TechCrunch since January 2011. You can follow him on Twitter at @semil.

Recently, while traveling, I came across a “traditional print business magazine” and read it on the plane. It had nothing to do with startups, so it felt novel. There was one segment in the magazine where the editors solicited a few business leaders to share the single most important advice they’ve ever received and one that they still remember today, and I found it to be unexpectedly powerful. So, I decided to try it on people that I look up to in the startup world, and below is what they wrote. I figured for folks in the startup community, the advice that stuck with others that we recognize as leaders could have a positive impact. Below is what a few folks shared with me, and I see the result as sort of an experiment. I just emailed a good handful of folks, asked for some contributions, and seven folks were kind enough to write back. Their contributions are interesting because of what they remember, and how they remember it. I hope you enjoy it. (I’m trying to experiment with new content styles to expand out from the type of posts I normally write here. I’d appreciate any suggestions you may have.)

Josh Felser, two-time entrepreneur, currently a co-founder of Freestyle VC: “Even if it takes you weeks, return every legitimate email or call you receive, even if the response is short, because it reminds you where you came from,’” says Felser. He received this advice back in 1992 from Strauss Zelnick, who was then President of FOX, where Felser, now an early-stage VC, once worked in business development. “Especially now that I am a VC,” says Felser, “I need to remember what it was like as an entrepreneur trying to build your dream in the face of rejection at every turn.”

John Lilly, former CEO of Mozilla, currently a Partner at Greylock Partners: “Figure out who your crew is, who you want to work with over the long arc of your career, and really invest in them, build relationships over a long period, help each other, stay in touch.” Lilly, at partner at Greylock Partners, received this advice from Stanford Professor Tom Kosnik. “The reasons why it’s stuck with me: (1) It’s created a wonderful context and environment to live a life in, with people I respect and learn from constantly, (2) It’s been effective in creating countless unexpected opportunities for me, and (3) After awhile, it becomes second nature, like breathing oxygen, to invest time and effort in relationships that reinforce and can grow.”

Sam Shank, serial entrepreneur, current founder/CEO of HotelTonight: “My father, an architect, who told me that tons of people will have the same idea as you, but few, if any, will ever do anything with it. He told me this when I was 10, in the context of a flooring system he decided to patent and earned royalties on. I thought about it when starting HotelTonight – an idea many had, but no one pursued (at least until we launched).”

Ross Fubini, former engineering executive, founder, and seed-stage investor, now Venture Partner at Canaan Partners: “It’s gotta be from my grandfather. After quizzing me on series of calculus fundamental, he said: ‘If you don’t know these facts, you aren’t ready to learn. Come back when you know your facts.’ While the statement was made with a grandfather’s affection — it also had the judgement of a world-class assessor of ideas. It was clear not know thing the fundamentals meant you weren’t ready to have a real conversations on a topic. It scared the bejeezus out of me and made a huge impression. It comes to mind every time whenever I formulate an opinion. What facts do I really know? My grandfather was genuinely wise (as evidenced by his opinions being sought by Presidents of CalTech, Cabinet members, etc). I think his foundational understanding of science, technology and people formed a foundation for how to see the world with insight. Which is something I aspire too.”

Manu Kumar, former entrepreneur and technologist, now runs K9 Ventures: ”‘Entrepreneurship is insane perseverance in the face of complete resistance.’” This quote is from Jack Thorne, the Morgenthaler Professor of Entrepreneurship, Carnegie Mellon University. That line is what got me going and gave me the courage to never give up. The full story of the impact of that line on me is chronicled in this blog post. Thorne taught the entrepreneurship class at CMU. When I decided I wanted to do a startup, I figured I should go learn as much as I can about entrepreneurship first, so I wanted to take Jack’s class. When I approached Jack about it, he told me the class was already full and so I couldn’t take his class. I showed up on the first day of class anyway. The definition of entrepreneurship was the first topic/slide that Jack presented. Right there I knew what I had to do to get into Jack’s class — and so started my journey as an entrepreneur — one with insane perseverance. This line has stuck with me after all these years because startups are never easy and always hard, and, you need something to hold on to to get you through it all. Perseverance is what makes founders win. I should point out, however, that perseverance doesn’t mean simply mean beating your head against a brick wall, but it means being determined, resourceful and relentless. The day when I snuck into Jack’s class was a turning point for me, one I remember fondly, and, I only hope that I can have even half as much impact on the lives of the founders I get to work with.”

DJ Patil, currently a Data Scientist at Greylock Partners: “What starts as simple becomes complex. What starts as complex becomes intractable.” That quote is from one of my Ph.D. advisors, Jim Yorke, who named the field of Chaos Theory. Even though Jim gave me this feedback in context of our work on new ways to improve weather forecasting, it’s become a guiding principle for me. Whether it’s been working in national security or developing new products, I’ve found it’s a hard-learned lesson. We often love to go for the hard problem, but the hard problem starts off easy and becomes complex quickly.

Pete Skomoroch, currently a data scientist at LinkedIn: “’Character is what we do when we no one is watching.’” I’ve heard this in various forms over the years. The version which really stuck with me came from Adam Nash while he was my manager at LinkedIn. Adam took extra time to help with issues that meant a lot to me, but that most people would never hear about. I had just started reporting to him, and he was responsible for several major product areas at the company. When I asked why he was helping me out, he said ‘character is what we do when we no one is watching.’ When you have many competing demands, you focus your time and energy on high priority things that move you closer to your objectives. At the same time, it is important not to lose sight of things you should still do as a matter of principle. If you cut corners in work and life, then you will pay for it later. Adam delivered similar advice on his blog, where he said you should ‘be the type of person who paints behind the refrigerator.’ My corollary to this is that you should surround yourself with people who try to do the right thing, especially when it isn’t easy or politically expedient for them. It is hard to build something of long term value if you are on a team that takes the path of least resistance and might not back you up when things get tough.

Photo Credit: Mara 1 / Flickr Creative Commons

It’s really a rather curious thing that the most popular devices in the world right now are, arguably at least, the best designed. Not to cheerlead for Apple, but we can all agree that whatever their faults, the original iPhone and the iPhone 4 (from which the slightly disproportionate 5 has descended) are impressive examples of one-upping the competition in both material and industrial design.

In a way, it’s a bit like if the most popular car in the world were a Lamborghini instead of a mass-market compact. Except, of course, that part of the draw of a Lamborghini is exclusivity. If everyone owned Lamborghinis, they would likely be seen as pedestrian. That’s the paradox of the iPhone’s success — high design coexisting with ubiquity.

But the lustre of the iPhone is diminishing, partly because of a lack of imagination on Apple’s part, and partly because of three other factors.

First, there is a massive and continuing migration onto smartphone platforms in places where the iPhone has little cachet. That the iPhone could be considered a Western affectation is potentially a huge block to uptake in expanding markets like India and China. This is a complicated, unpredictable, global economic thing and not at all what I wanted to talk about, but there it is.

Second, mass manufacturers of poorly-made widgets, which have sold hundreds of millions for decades, are slowly becoming aware of the necessities and realities of a “premium” product, which is another name for something that isn’t garbage. So you have the likes of the latest Nokia and HTC devices. The movement away from disposable electronics is a slow and strange process, and is also not exactly what I want to discuss, though it’s part of it.

Third is the incredible improvement in decentralized product creation. It’s things like the Ouya on Kickstarter, the Shine on Indiegogo, and a hundred other devices and pieces of kit. These are made possible by the wide availability of design and prototyping equipment, and the ability to insert themselves into a process that was once uncomeatable (I am bringing this word back).

What the teams do is abstract only the portion of the productization process that is necessary for their purposes. Previously something like a mobile phone could only be created by a large, vertically-integrated company like Samsung. And really, that’s still true. A Samsung-like entity is necessary for the creation of a mobile phone. So is a Hon Hai, and an aluminum mill, and a shipping company, and an oil refiner… the list, like the minimum viable society in Plato’s Republic, quickly grows when you consider everything that’s involved in making and delivering a product.

There’s no way a Kickstarter project is going to create everything from scratch. But what they can do is cherry-pick from a list of requirements the items that they think they can improve on. You can’t remove Sony from the equation if you want image sensors, but that doesn’t mean Sony has to make the camera. Or Nikon, or Apple, or whoever.

To get to the point: When you remove the aged, inefficient, and rather inherently unhip design departments of the big companies, like Sony and Samsung, and put their tools in the hands of talented and motivated individuals or groups, you change the landscape immensely.

What a small team has is not just the singularity of vision to create a unique and desirable product, but the choice to do things on whatever scale they choose. This is important. It costs millions — hundreds of millions — for a large company to launch a device. They produce five million to start and lock up entire factories for months at a time, saving fractions of pennies per unit to maximize margins. They’re like tech industry Glamazons: they won’t get out of bed for less than a $100 million a quarter.

Meanwhile, the consumer class has been turned into a creative class, and you have teams on Kickstarter whose goal in life is to sell a thousand devices to a niche audience who will pay through the nose for anything made with them in mind. Furthermore, to bring things back around, such devices have the added benefit of exclusivity. The long tail (and haute couture) is coming to manufacturing with a vengeance.

Artisanal, free-range iPhones

Fans of William Gibson will have already intuited where I’m headed. In Idoru, one of the characters has a highly custom and personalized computer made by a group called Sandbenders. “They melt old cans they dig up on the beach and cast it in sand molds. These panels are micarta. That’s linen with this resin in it,” she says.

Gibson’s remarkable prescience in these matters is proved once again. Years ago, when Idoru came out, such a device was very much a fantasy — how could some beach tribe make a computer? Today, it’s a business model, albeit with some significant restrictions resulting from the monopolies of a few large companies on things like processors and display modules. Ten people can now reach an audience of ten million, and refine from that an ultra-concentrated, self-selecting market of ten thousand. And by cutting out the middle man, they can imitate the long-tail success of small businesses selling via eBay or Kindle. The increasing mobility of currency will only accelerate this process.

All these factors amount to a powder keg under the feet of the companies that make and sell items on the scale of millions. A lot has to happen before Sandbenders is possible, and it’s not like Sony and Apple will suddenly lose all their business to a legion of basement-dwellers cooking up custom phones in Maya. Nevertheless, we’re approaching one of those points that Apple has been so good at exploiting, but to which it is now (as an iconic and ubiquitous brand) vulnerable. The point when people realize what they want, and find that no one is providing it.

The fact is that the enormous growth in consumer numbers and diversity has not been matched with a corresponding growth in product diversity. The illusion of choice presented by a handful of companies offering one-size-fits-all options is being exposed for what it is, as devices and services become increasingly personal.

Unimaginative offerings devised to fit the needs of millions, offered by an aristocratic class of companies who have only each other for competition. How long can it last? History suggests their way of doing things must adapt or die. We don’t really care which.

[image: The Hamlet – The Forge]

Editor’s note: Ross Rubin is principal analyst at Reticle Research and blogs at Techspressive. Each column will look at crowdfunded products that have either met or missed their funding goals.

Like a Kickstarter campaign, Apple’s embrace of technologies tends to be an all-or-nothing affair. The company was early to support Wi-Fi and now supports Bluetooth throughout its product line. However, it has remained at an arm’s length from technologies, such as Blu-ray, DLNA, wireless charging and NFC. Apple VP Phil Schiller has said it’s not clear what NFC is good for. The answer: lots of things, mostly having to do with initiating different kinds of transactions, including payments and Wi-Fi transfers.

Backed: FloJack

Some of those things should soon be possible with the aid of the Kickstarter project by Miami-based NFC wizards Flomio and its project FloJack. It’s not a device that enables you to track stolen boats with GPS. Rather, in the spirit of the Square credit card reader, it is a small white lollipop of a device that plugs into the headphone jack of mobile iOS or legacy Android mobile device and allows it to read and write data via NFC. The company has wisely avoided getting wrapped up in payments at this point, but it is supporting other NFC functionality, such as tag reading via Samsung’s TecTiles or its own similar Zapps.

The Flomio Kickstarter page includes a four-minute intro video that takes prospective backers through a cutesy “NFC party” in which iOS devices aren’t on the guest list, the standard CAD-drawing development segment and a concept “day in the life” where we see shoppers tapping FloJacks to access special deals. Still, the FloJack campaign started off slow, no doubt leading many backers to wistfully wonder, “Flomio, wherefore art thou?” The Kickstarter campaign has come down to the wire, with about $6,000 needed to reach the $80,0000 funding goal needed in the next 60 hours as of this writing.

When one breaks down the backers at this point, most have gone for either the $99 FloJack dev kit or the $49 FloJack pack for NFC enthusiasts. The real boost, though (half of the project’s funding), has come from three backers who have shelled out $10,000 each to have Flomio help them create NFC applications and a fourth who shelled out the same amount to have Flomio build them something while they take in a Miami Heat game and relax on the beach — nice work if you can get it done for you.

Like its longer-range radio brethren Bluetooth and Wi-Fi, NFC is best integrated not only into the casing of the phone, but into its operating system as well, which is exactly why Android and Windows Phone have taken that approach. Wi-Fi and Bluetooth USB sticks for laptops lacking those technologies proved that point, and the situation is even worse with a mobile phone, where a need for portability and personal style is at a premium.

Sweetening the deal and taking advantage of a Kickstarter campaign that enables owners to change rewards midstream, the clever Flomio team added a new option, the FloCase. This wraps a FloJack-style NFC reader/writer into an iPhone case. It makes for a far better solution in which you don’t have to be as concerned about the FloJack slipping out of or even breaking off in the headphone jack, which remains free for audio output.

Not only has Flomio been smart about its Kickstarter rules, but it’s also recognized that, for NFC to do anything, it must be supported with an SDK. Flomio’s works across platforms. However, at some point Apple will no doubt support NFC or something like it for transactions, and at that point Flomio will likely have to focus more on its own custom development work. Unil that time, though, developers may be willing to deal with a little protrusion from their iDevices in order to get a taste of at least some of the promise of NFC.

Editor’s note: Dr. Michael Wu is the Principal Scientist of Analytics at Lithium where he is currently applying data-driven methodologies to investigate and understand the complex dynamics of the social Web.

The value of any data is only as valuable as the information and insights we can extract from it. It is the information and insights that will help us make better decisions and give us a competitive edge. The promise of big data is that one could glean lots of information and gain many valuable insights. However, people often don’t realize that data and information are not the same. Even if you are able to extract information from your big data, not all of it will be insightful and valuable.

Data ? Information

Many people speak of data and information as if they are synonymous, but the difference between the two is quite subtle. Data is simply a record of events that took place. It is the raw data that describes what happened when, where, and how and who’s involved. Well, isn’t that informative? Yes, it is!

While data does give you information, the fallacy of big data is that more data doesn’t mean you will get “proportionately” more information. In fact, the more data you have, the less information you gain as a proportion of the data. That means the information you can extract from any big data asymptotically diminishes as your data volume increases. This does seem counterintuitive, but it is true. Let’s clarify this with a few examples.

Example 1: Data backups and copies. If you look inside your computer, you will find thousands of files you’ve created over the years. Whether they are pictures you took, emails you sent, or blogs you wrote, they contain a certain amount of information. These files are stored as data in your hard drive, which takes up a certain amount of space.

Now, if you are as paranoid as I am, you will probably back up of your hard drive regularly. Think about what happens when you back up your hard drive for the first time. In terms of data, you’ve just doubled the amount of data you have. If you had 50 GB of data in your hard drive, you would have 100 GB after the back up. But will you have twice the information after the back up? Certainly not! In fact, you gain no additional information from this operation, because the information in the backup is exactly the same as the information in the original drive.

Although our personal data is not big data by any means, this example illustrates the subtle difference between data and information, and they are definitely not the same animal. Now let’s look at another example involving bigger data.

Example 2: Airport surveillance video logs. First, video files are already pretty big. Second, closed-circuit monitoring systems (CCTV) in an airport are on 24/7, and high-definition (HD) devices will only increase the data volume further. Moreover, there are hundreds and probably thousands of security cameras all over the airport. So as you can see, the video logs created by all these surveillance cameras would probably qualify as big data.

Now, what happens when you double the number of camera installations? In terms of data volume, you will again get about 2x the data. But will you get 2x the information? Probably not. Many of the cameras are probably seeing the same thing, perhaps from a slightly different angle, sweeping different areas at slightly different times. In terms of information content, we almost never get 2x. Furthermore, as the number of cameras continues to increase, the chance of information overlap also increases. That is why as data volume increases, information will always have a diminishing return, because more and more of it will be redundant.

A simple inequality characterizes this property: information ? data. So information is not data, it’s only the non-redundant portions of the data. That is why when we copy data, we don’t gain any information, even when the data volume increases, because the copied data is redundant.

Example 3: Updates on multiple social channels. What about social big data, such as tweets, updates, and/or shares? If we tweet twice as often, Twitter is definitely getting 2x more data from us. But will Twitter get 2x the information? That depends on what we tweet. If there is absolutely zero redundancy among all our tweets, then Twitter will have 2x the information. But that typically never happens. Let’s think about why.

First of all, we retweet each other. Consequently, many tweets are redundant due to retweeting. Even if we exclude retweets, the chance that we are coincidentally tweeting about the same content is actually quite high, because there are so many tweeters out there. Although the precise wording of each tweet may not be exactly the same, the redundancies among all the tweets containing the same Web content (whether it’s a blog post, a cool video, or breaking news) is very high. Finally, our interest and taste in good content remains fairly consistent over time. Since our tweets tend to reflect our interests and tastes, even apparently unrelated tweets from the same user will have some redundancies, because the tweeter is tweeting similar content.

Clearly, even if we tweet twice as often, Twitter is not going to get 2x the information because there is so much redundancy among our tweets (likewise with updates and shares on other social channels). Furthermore, we often co-syndicate content across multiple social channels. Since this is merely duplicate content across multiple social channels, it doesn’t give us any extra information about the user.

Although data does give rise to information, data ? information. Information is only the non-redundant parts of the data. Since most data, regardless of how it is generated, has lots of built-in redundancy, the information we can extract from any data set is typically a tiny fraction of the data’s sheer volume.

I refer to this property as the data-information inequality: information ? data. And in nearly all realistic data sets (especially big data), the amount of information one can extract from the data is always much less than the data volume (see figure below): information << data. Since the naïve assumption that big data leads to a lot of information is not true, the value of big data is hugely exaggerated.

Information ? Insights

Although the amount of information we can extract from big data may be overrated, the insights we can derive from big data may still be extremely valuable. So what is the relationship between information and insights? All insights are information, but not all information provides insights. There are three criteria for information to provide valuable insights:

1. Interpretability. Since big data contains so much unstructured data and different media as well as data types, there is actually a substantial amount of data and information that is not interpretable.

For example, consider this sequence of numbers: 123, 243, 187, 89, and 156. What do these numbers mean? It could be the number of likes on the past five articles you read on TechCrunch, or it could be the luminance level of five pixels in a black and white image. Without more information and meta-data, there is no way to interpret what these numbers mean. Since data and information that are not interpretable won’t offer you any insights, insights must lie within the interpretable parts of the extractable information.

2. Relevance. Information must be relevant to be useful and valuable. Relevant information is also known as the signal, so irrelevant information is often referred to as noise. But relevance is subjective. Information that is relevant to me may be completely irrelevant to you, and vice versa. This is what Edward Ng, a renowned mathematician, means when he says “One man’s signal is another man’s noise.”

Furthermore, relevance is not only subjective, it is also contextual. What is relevant to a person may change from one context to another. If I’m visiting NYC next week, then NYC traffic will suddenly become very relevant to me. But after I return to SF, the same information will become irrelevant again. Therefore, insights are an even smaller subset within the relevant information (i.e. signals), which is already a tiny subset of the interpretable information.

3. Novelty. Information must be novel to be insightful. That means it must provide some new knowledge that you don’t already have.

Clearly this criterion is also subjective. Because what I know is very different from what you know, what is insightful to me may be old information to you, and vice versa. Part of this subjectivity is inherited from the subjectivity of relevance. If some information is irrelevant to you, then most likely you won’t know about it, so when you learn it, it will be new. But you probably wouldn’t care because it’s irrelevant. Even if it is novel, it’s of no value to you.

However, once an insight is found, it’s no longer new and insightful the next time you have it. Therefore as we learn and accumulate knowledge from big data, insights become harder to discover. The valuable insight that everyone wants is a tiny and shrinking subset of the relevant information (i.e. the signal).

If the information fails any one of these criteria, then it wouldn’t be a valuable insight. So these three criteria will successively restrict insights to an even tinier subset of the extractable information from big data (see figure). So the big data fallacy can be summarized by a simple inequality: insight << information << data.

The value of big data is hugely exaggerated, because insight (the most valuable aspect of big data) is typically a few orders of magnitude less than the extractable information, which is again several orders of magnitude smaller than the sheer volume of your big data. I’m not saying big data is not valuable, it’s just overrated, because even with big data, the probability for finding valuable insights from it will still be abysmally tiny.

The big data fallacy may sound disappointing, but it is actually a strong argument for why we need even bigger data. Because the amount of valuable insights we can derive from big data is so very tiny, we need to collect even more data and use more powerful analytics to increase our chance of finding them. Although big data cannot guarantee the revelation of many valuable insights, increasing the data volume does increase the odds of finding them.

Editor’s note: John Hauer is a sales, marketing and technology innovator with a 20+ career of working in print and related industries. He manages a blog which evangelizes 3D printing for traditional 2D printers. Follow him on his blog and on Twitter.

I recently read an article on TechCrunch by Jon Evans entitled 3D Printers Are Not Like 2D Printers. While I would agree with the title (obviously the two devices don’t serve the same purpose), I don’t agree with the argument Jon makes for why 3D printing is not like 2D printing.

His primary argument is that 3D printers make “stuff,” while 2D printers disseminate information. I’d counter that argument by pointing out that packaging, boxes and other forms of dimensional printing not only provide information, but serve as containers – stuff that holds other stuff. Jon’s point is that “our relationship to stuff is thoroughly, extremely, fundamentally different from our relationship to information.” I would agree, noting that, with some amusement, kids sometimes play with the box more than the toy because they perceive the box as more interesting.

More importantly to me however is the implied assertion that 3D printed “stuff” doesn’t or can’t disseminate information. Consider for example the 3D-printed, customizable Android figurines currently for sale on Cubify.com. Other than promoting a brand, what purpose do they serve? And with the obvious exception of an extra dimension, how are they really any different than a poster or wall graphic of a customized Android figure?

For a moment, let’s get beyond this issue of output and think a bit about the workflow. With 2D (digital) printing, the workflow looks like this:

File created ? file submitted to print device ? file is printed ? item is finished (bound, etc.)

The workflow for 3D printing is very similar:

File is created ? file is submitted to print device ? file is printed ? item is finished (decorated, etc.)

Certainly there are myriad other sub-steps along the way, and there are major differences within the two processes. The software to create and print projects in 2D is different than in 3D. The substrates used are different. Finishing is a whole different animal, though it is interesting to note that 2D printing techniques are being used to decorate 3D-printed items.

As far as history goes, 2D digital printing didn’t develop overnight. At first it was painful and expensive. File formats were incompatible, the devices were slow, quality was suspect, substrates were limited, and finishing was manual. Like 2D, as 3D printing matures, file issues will be resolved, speed and quality will improve, substrate options will expand, and finishing will become automated. Breakeven run lengths between digital and traditional processes will rise. At some point the “printers triangle” will be better optimized – you will be able to get quality, turnaround, and price, simultaneously.

Will it ever be as cheap to print 100,000 toys as it is to die-cast or injection-mold them? Probably not, but cost is not the only motivator for people’s buying decisions. Just as with 2D digital printing, people also buy based on the ability to customize or personalize — or because it is more convenient — even when the price is higher than that of a generic item produced in bulk.

In a previous article, Jon made the point that “communal 3D printer shops” will serve the majority of future needs. He forecasts that in high-infrastructure areas, web-to-print providers like Stratasys will supply consumers and that in low-infrastructure areas, people will use local printing facilities. Beyond the desktop, this is how 2D consumers are being served today, though I don’t think it’s as much about infrastructure as it is a matter of convenience. There are times when it makes more sense for me to order print online, pay a bit less and wait for delivery, and other times when I order locally, pay a bit more, and pick the product up.

This level of infrastructure to me is the most important point and why 3D is like 2D printing. Web-to-print solutions exist for both platforms, allowing consumers to enter specifications, upload files, and check out. Days later, the product arrives. What hasn’t been developed yet is the retail side of 3D print. Those who say it’s not print, but rather “additive manufacturing” believe it should fall squarely in the purview of machine shops, injection molders, and the like. The problem is, those businesses are not geared toward consumers. They don’t have retail locations, they don’t market to consumers, and they typically don’t have the business model or point-of-purchase systems to deal with small consumer transactions.

Who does have that kind of infrastructure? Traditional printers, office supply stores, and shipping giants like FedEx (Kinko’s) and UPS (Mail Boxes etc.). They receive files from clients every day (different, I know), offer several printing methods (black and white, color, large format) and multiple finishing methods (trimming, binding, lamination). They are located in retail areas, are used to dealing with and educating consumers, and have the ability to handle and process a lot of small orders.

2D print shops also relatively standardized and well-networked, allowing them to effectively sell the “distribute-then-print” concept. Need copies of a presentation in Altanta? Why print it in Ohio and carry it when you can print it there. How long do you imagine it will be until we’re distributing then printing objects in the same manner? Seems like a pretty clear case of history repeating itself to me.

Editor’s note: Ray Sobol is founder and CEO of EvidencePix, an enterprise-grade secure MDM service. Ray has more than 25 years experience in launching high-tech ventures and disruptive technologies.

No one likes to pay for things they don’t use. If you’ve ever grappled with the fact that you’re paying for 500 channels on your monthly cable bill when you only use a few, you know what I mean. The same problem holds true when it comes to software. An average business purchases more software than is actually needed, and we’ve all had software installed that we used sparingly. It’s time to let customers pay based on what they actually use.

The Evolution Of Software Pricing Models

The past two decades have brought significant changes to B2B software sales. SaaS upended traditional software licenses and made install disks an artifact of the 90s. Then, hefty annual SaaS subscriptions gave way to today’s more flexible, user-friendly monthly plans. Of course, evolution never rests, and consumers will relentlessly drive the market toward cost-efficiency.

With time-based subscription plans, software will always be underutilized. Obviously, annual subscriptions are the most egregious offender, but monthly subscriptions can be just as wasteful, particularly given the fluid reality of today’s workforce.

Employers are increasingly relying on a patchwork of contractors, freelancers, and project-based workers. As a result, it’s hard to predict exactly what resources will be needed on a monthly, weekly, or daily basis. Annual, even monthly, subscriptions can be overkill for a company that needs to get one worker up and running one week and another worker the next.

Even with a full-time workforce, nothing is static in business: Employees transfer departments; businesses pivot their focus; and projects come and go. Each change can result in unused software when subscriptions are purchased. The price of a single month’s subscription may seem harmless enough; however, monthly subscriptions accumulated across a large enterprise can take a serious toll on the bottom line.

The “Pay-Per-Use” Model

The most economically beneficial model for end users is “pay-per-use,” where customers pay based on what they actually use. For example, companies can pay each time an employee uses a service to run a backup, fill out a mobile form, or perform some other task. By forsaking licensing or subscription arrangements, enterprises are able to use any product, at any time, as much as they need, without having to pay for software they don’t use.

With this option, companies don’t have to worry about managing licenses and subscriptions across their pool of workers. They can equip each worker with the tools they need, when they need them, and monthly subscriptions no longer go unused for weeks on end.

Several software vendors are already moving toward this new model. With Windows Azure, Microsoft is offering customers a “pay-as-you-go” alternative to its six-month and 12-month plans. Companies like Twilio are serving up pricing based on the cent, and yet others offer micro activities at a fraction of a cent in combination with reduced monthly rates.

Pay-per-use is a bleeding-edge approach to SaaS revenue and may not apply to every business and software. However, if you think creatively enough, you can find opportunities to break down any software tool into smaller, billable units – such as creating/sending one expense report, playing an online game for one hour, or sending a visual report from a mobile device.

The pay-per-use movement is rooted in a core belief that people should pay only for what they need and use. It’s a radically different model than the original software license from two decades ago, and there will always be resistance to change, even in the fast-paced technology world. However, as the market is continually driving toward greater flexibility and lower costs, the day when you need to offer a pay-as-you-go option may be sooner than you think.

Editor’s note: This is the second in a series of articles by Brad Woodcox that explores the patent system for entrepreneurs. The first examined the basics of the system. Woodcox is a technical specialist focusing on startup development for Novak Druce + Quigg, an intellectual property super boutique law firm. Follow him on Google+ and Twitter.

Now that you have background knowledge of the patent system (at least within the U.S.), we can analyze probably the most difficult question: “Should you pursue patents for your company or invention?” Unfortunately, there isn’t an easy or direct way to answer this question. Each business is unique and requires an individual analysis. This article discusses some frequently asked questions and presents an analysis framework that may be useful for you to explore the applicability of patents for your business/invention.

Given the significant costs of obtaining a patent, should you spend any of your limited capital on them?

It depends. A patent will not directly make your company’s product or service more successful, but it can have a positive financial impact on the business. The best way to analyze your situation is to look at what a patent could do for your company and how it would fit into your company strategy. This self-analysis should include product, finance, and market/competition elements.

For many Internet startups, the timeline to make it or pivot and try something else is often 9-24 months. With a standard patent application taking three-plus years and 80 percent to 90 percent of startups failing in that timeframe, most startups will not be around long enough to enforce the patent.

Given the startup failure rate and patent timeframe, should most Internet startups skip patents?

Not necessarily. A patent (or portfolio of patents) may be useful for both successful and unsuccessful companies. For successful companies, the reason is clear in that patents can be used as an offensive or defensive tool against competitors. An example of this is the patents that are being asserted in the smartphone industry by companies such as Apple and Samsung. For unsuccessful companies, the patented innovations can still hold tremendous value.

An example is Internet search engines. There have been dozens or even hundreds of Internet search engines, but most failed, as Google became the dominant search engine, even though they weren’t the first to market. Some of these now-defunct search companies had patents on innovative elements for search engines that Google later licensed or acquired (see Google acquires Cuil patents). Other large-scale examples are companies, such as Nortel, Novell, and Kodak, that faced financial challenges and were able to sell or are in the process of selling their patent portfolios for billions of dollars. Hence, a company can use patents as a tradable asset, perhaps even earning a profitable return which otherwise wouldn’t have occurred.

How can you determine whether your patent will be valuable?

This is difficult to expound. At the highest level, the patent must be regarding a topic in which other people or companies are interested. You can design the most amazing product, but if no one wants, needs, or buys the product, then it isn’t worth very much. While this sounds trivial, innovation bias can affect intelligent inventors and entrepreneurs. Other factors to consider are: