So I created a list of awesomeness, innovation and disruption, including topics such as ‘Mobile is big’, ‘Phones are getting better’, and ‘People pay for stuff on their phones’.

Here’s the full article; 10 awesome, innovative and disruptive things about mobile.

Mobile is an exciting sector to work in. It’s growing fast, and it’s being fundamentally disrupted from all sides, by all kinds of awesome innovation.

Here’s my current list of awesomeness, innovative and disruption in mobile. If this stuff sounds interesting, you should consider working in mobile. We need your help!

01. Mobile is big

You just won’t believe how vastly, hugely, mind-bogglingly big it is.

The global mobile phone subscriber base is 4.6 billion. By comparison, mankind owns a mere 800 million cars, 1.1 billion PCs and 1.5 billion TV sets.

Mobile phones will become ubiquitous within a few years as manufacturing costs drop as low as US$10 per phone.

Mobile internet is already bigger than desktop internet. Over 1 billion people access services using the mobile internet on their phone, more than the number of desktop internet users.

More data is consumed on the mobile internet than the desktop internet. Mobile data traffic will grow from 1 petabyte per month to 1 exabyte per month in half the time it took fixed data traffic to do so.

And mobile is big business. Mobile data services deliver more than US$200 billion of revenue, more than global desktop internet access and internet advertising revenues combined.

02. Phones are getting better

Long after mobile phones become ubiquitous, we will still buy them because of the continual advancement of hardware, battery life and software.

We are buying 1.2 billion new phones every year, gradually upgrading to smartphones (currently there are only 500 million) &/or 3G devices (currently only 1 billion).

At Myriad Group, we write a lot of mobile software to enable high-end smartphone features in lower price-point mobile phones.

03. People pay for stuff on their phones

The huge majority of desktop web users are either unwilling or unable to pay for stuff online.

But on mobile, every subscriber has a billing relationship with a telco, either prepaid or postpaid, that is suitable for micro-payments.

According to Portio Research, the market for mobile ringtones, wallpapers, games and other paid mobile content is US$85 billion, bigger that music, Hollywood and videogames combined.

04. App Stores disrupt paid mobile content

Traditionally, most of that revenue from paid mobile content goes to the telcos. However, the telco walled gardens are rapidly crumbling, and thanks to the emergence of the App Stores, revenue from paid mobile content is being redistributed.

By selling apps on iTunes, Nokia Ovi Store and Android Market, developers can now expect to keep around 70% of the sale price, with the remainder being shared between the App Store and possibly the telcos

Gartner predicts we will download 4.5 billion apps from various App Stores in 2010, spending US$6.8 billion.

Also disruptive to paid mobile content is GetJar, the App Store for free J2ME apps, funded by advertising, and currently bigger than Nokia Ovi Store and Android Market.

05. Mobile advertising is better

In times or places of information overload, a mobile phone can be an excellent information filtration device.

Mobile phones increasingly know who you are (and who your friends are), and where you are (even which direction you are looking), meaning that mobile advertising promises to become better targetted than other forms of advertising, including desktop web advertising.

Google recently spent US$750 million on AdMob, the biggest mobile ad network.

Personally, I believe that given enough local inventory, mobile advertising will eventually cease to be intrusive and will become useful local information.

Another innovation in this area is Google Latitude Proximity Alerts. By recognizing the patterns in your geolocation movements, Google can go beyond the ‘who’ and the ‘where’ and start to detect the why, or your intent, to better target its advertising inventory.

Gartner estimates mobile advertising revenues will leap from US$900 million this year to surpass US$13 billion by 2013.

06. Push Notifications disrupt SMS and MMS

Over 3 billion people are sending 5 trillion SMS messages per year. SMS is worth US$80 billion to the telcos, and MMS is worth US$27 billion.

Apple’s Push Notification Service, launched in 2009, allows an iPhone to receive similar short messages from a server controlled by an app developer. The cost to the sender reduces by a factor of 100, from an average of $0.10 for an SMS, to a few hundred bytes of mobile data, average cost around $0.001.

Why send an expensive SMS when you can send a Facebook message that will be pushed to your iPhone friends?

07. Open source

The mobile operating system, previously a competitive battleground, has recently been commoditized by Android, the open source mobile platform from Google and its partners, including Myriad Group, in the Open Handset Alliance.

Nokia has now also open sourced its Symbian operating system, the most popular on the planet.

Handset manufacturers no longer need to pay a license fee for an operating system; Symbian used to cost about US$4, while Microsoft charges about US$15 for Windows Mobile, so this represents a significant saving, especially for lower price-point phones.

By not being locked into a closed platform, handset manufacturers and telcos are now able to easily customize mobile phones to suit their brand proposition. This has shifted the competitive battleground to innovation in mobile software and cloud-based services, which will generate a lot of demand for mobile software engineers, and which will ultimately deliver more awesomeness and innovation to the benefit of subscribers.

08. Open contracts

Subscribers can also benefit from the flexibility of not being locked into a two year phone contract.

Since January 2010, subscribers in the US, UK, Hong Kong and Singapore can now choose to buy an unlocked Nexus One phone direct from Google rather than subsidized by a telco and locked into a two year contract.

Apple has also announced the iPad as an unlocked device.

This isn’t completely revolutionary. Already in many parts of the world, subscribers buy lower price-point phones directly from manufacturers and switch frequently between telcos competing mainly on voice pricing.

What’s different here is that smartphones consume as much data as 30 lower price-point phones, so we should expect mobile data pricing to become more competitive in markets with a high penetration of smartphones.

Elsewhere, the launch of mobile number portability in large markets including China, India and Indonesia will also encourage subscribers to switch and telcos to compete on voice and data pricing.

09. The Facebook Phone

The INQ Facebook Phone was launched in 2008 but it wasn’t a great user experience, IMHO because Facebook wasn’t deeply integrated into all the places on the phone that it should have been.

Nowadays, Facebook accounts for over 5.5% of all Internet usage, Facebook Mobile has 100 million monthly active users, and 40% of the UK’s mobile internet users are using Facebook.

These numbers reveal an emerging market of subscribers who might like to use Facebook as the Address Book and Inbox on their phone, caring more about a decent mobile social networking experience than who manufactures their phone or who is their telco provider.

Facebook works with many handset manufacturers and telcos to distribute their service, so will they have the courage to do what Google has done with the Nexus One and launch a phone to compete with those channels? You bet! I would expect Facebook to launch a phone within the next couple of years, probably built on Android, further disrupting both the handset manufacturers and the telcos.

Aligned with this prediction is the interesting fact that Facebook still does not expose friend phone numbers through its API, despite that being the most requested feature by third party developers. We should expect the Facebook Phone to leverage this data as an exclusive differentiator.

0A. Mobile Maps disrupts GPS navigation

There turned out to be more than ten things, so let’s continue the list in hexadecimal.

60% of the 421 million GPS chips sold in 2009 were put inside a mobile phone.

Google Maps Navigation is a killer mobile app with lots more features than the standalone GPS devices sold by TomTom and Garmin. And it’s free.

On 28 October 2009, the day when Google announced the app, TomTom’s share price fell 20% and Garmin’s dropped 16%.

Recently Nokia (which has invested heavily in geo, including its US$8 billion acquisition of Navteq) announced free voice navigation for its GPS smartphones, resulting in an 11% drop in the share price of TomTom, and a 5.5% drop in the share price of Garmin.

If you are still holding shares in TomTom or Garmin, be aware that Apple is also expected to launch free maps navigation.

0B. VoIP disrupts voice

Apple and AT&T have recently allowed iPhone VoIP calls to be placed over a 3G network connection, dramatically reducing the cost of voice calls, particularly long distance calls.

Previously this was only available over a Wi-Fi connection.

Fring was first to launch its iPhone 3G VoIP app. Skype is expected to follow in spades. And might it be a possibility that Facebook becomes a new entrant in the VoIP market?

And it’s not limited to the iPhone. Any phone with a data connection can potentially make VoIP calls if the telco is willing and able to support it over their data network. It will be interesting to watch how many telcos like AT&T are willing to cannibalize their own voice revenue in this way, and how they will re-shape their voice/data plans to align with this.

0C. Mobile web apps or native apps?

Native apps are great because they currently offer the deepest integration to the full capability of the phone, for example using device APIs to access Contacts, the Camera Roll, an Accelerometer, or the GPS chip.

On the other hand, emerging HTML5-based mobile browsers are aiming to standardise integration to such device APIs, starting with geolocation APIs; meaning that location-aware mobile web apps are now becoming viable.

The deciding factor for me choosing to build a mobile web app for GeoMeme rather than a native app was development speed. A mobile web app enjoys far greater code re-use from the desktop web version, and it is possible to push regular updates and improvements to users, without having to wait for iTunes approval or for users to upgrade.

Looking at recent evidence, mobile web apps are becoming more prevalent than native apps for mobile social applications, shopping and services, while native apps remain preferred for mobile games and entertainment.

It all comes down to the economics of mobile software development and the App Stores. For free apps, including all those funded by mobile advertising, while mobile browsers continue to advance with HTML5, reducing development costs will increasingly outweigh the marginal benefits of native apps. For paid apps, mostly games and entertainment, native apps will survive while the App Stores remain the only way for app developers to make money.

0D. Google Voice disrupts voicemail

Google Voice isn’t VoIP, but it’s still highly disruptive to telcos.

Innovative features include free voicemail transcription and visual voicemail, free SMS, cheap long-distance calls, and (very useful) call forwarding to multiple phones.

Apple controversially un-approved the Google Voice iPhone app, possibly under pressure from AT&T who were reportedly a little bit fed up with all this disruption.

Google has since released Voice as a mobile web app instead of a native app, thus bypassing the iTunes approval process. Touché! The only restriction I can see with the web app is that contacts from your iPhone need to by synced via GMail, because the iPhone Safari browser does not support the HTML5 Contacts API, yet.

0E. Dumb pipe or smart pipe?

One of the common threads here is that telcos are getting a rough deal at the moment, disrupted from all sides.

But the telcos are also busy innovating, adding value to mobile services to become a smart pipe rather than a dumb pipe.

Vodafone and Telstra are among the telcos who have announced App Stores, to leverage their existing billing relationships with subscribers.

And besides plugging an App Store into their billing systems, telcos can also fight back by providing access to their other network infrastructure and information, including subscriber geolocation.

Geolocation can be calculated by telcos even for lower price-point phones without a GPS chip, using triangulation of base station data. Exposing this geolocation data for app developers to build location-based services is a great opportunity for telcos, but also needs to be carefully controlled to avoid privacy abuses.

Another example: at Xumii our Social Stream product allows telcos to play a unique and valuable role in mobile social networking. Push notifications are sent to ordinary mobile phones using telco SMS capacity, and telco authentication systems are used to provide zero-click sign-in to all your social updates from multiple social networks including Facebook, Twitter, MySpace and Flickr.

0F. Hard bloody work

To all the technologists and engineers still reading this; building mobile technology is hard bloody work.

Getting software to run in a tiny memory footprint, with a slow CPU and constrained user interface, then getting the same software to work on 100 other devices, and then on an unreliable telco data connection, forces you to build efficient and elegant and innovative solutions. This is awesome, and mobile is a good place to work if you agree.

10. And there’s more…

Finally, check out WiMax, Augmented Reality, Google Goggles, and Foursquare for more mobile awesomeness, innovation and disruption.

I hope this list has been of interest to those outside of mobile wondering what all the fuss is about.

To those already working in mobile, yes I know this list is incomplete, and biased by my own interests in mobile + geo + social, so let’s discuss what’s missing in the comments or via @hitching

Murdoch had apparently failed to grasp the significance of the interwebs.

However, ten years later Time Warner has regained its mojo and is now trying to offload a spent and jaded AOL. Did Murdoch get it wrong ten years ago, or did it simply take a whole decade for him to be proven right?

In 2009, the mob is rushing once again to the conclusion that Murdoch is losing his marbles, planning to charge for his online content and blocking the Googlebot from stealing it.

Personally I believe that Murdoch should worry less about the Googlebot, and more about how social media is turning his industry on its head.

The problem is that all of those dotcom upstarts have brought us information overload. There has been an exponential increase in the amount of information and content available to us, way beyond the capacity of the human brain to process.

The solution is social media, which empowers us to easily share the content we care about with our friends and contacts, and adds valuable metadata to that shared content, such as Likes or Retweet counts. This metadata helps us filter the signal from the noise, so that we can focus on just the best quality content from our trusted circle of friends.

This works great for movie reviews. People have always listened to the advice of friends when it comes to choosing what movie to watch. Social media simply provides an efficient and scalable way to do this.

The best example of this social filter is currently FriendFeed, although we can expect to soon see something equally impressive on Facebook. Twitter Search could do this even better if only it were possible to search the entire tweet history of just your friends, or a chosen social distance into your social graph, rather then merely search 7 days of the public timeline. I am hoping that the Google Social Search Experiment will enable this sort of social filter when Google completes its Twitter integration.

Back to Mr. Murdoch… Social media also works for the filtering of news content, however it’s more tricky than movie reviews because there is a need for trustworthy fact rather than mere opinion. This is why Eric Schmidt believes that figuring out how to rank real-time social content, perhaps based on a reliable measure of reputation and authority, is “the great challenge of the age“. It also explains why Twitter’s Retweet feature does not allow the original tweet to be modified, because this makes the Retweet count a more reliable indicator of authority.

So my advice to Rupert Murdoch and other media companies struggling with this; worry less about the Googlebot and more about social media. Focus on improving the quality of your content, so that people share it with their friends.

And if your own social media strategy is not delivering any tangible benefits, try moving it from your Marketing department to your Customer Service department. Use social media to listen more carefully to the needs of your customers, so you can improve the quality of your content to the point where a paid online content model becomes viable.

If Marketing and Customer Service argue about who owns the customer relationship, remind them both that thanks to social media it’s actually the customer who owns and controls the relationship with your business. Not the other way around!

I am pleased to announce the launch of GeoMeme, the fun way to measure and share real-time local twitter trends.

I got thinking about this when a recent Los Angeles earthquake was being measured in tweets per second rather than using the Richter Scale.

Then came the Magnitwude Calculator as a standard way to measure the magnitude of Twitter trends.

[Then came twotspot.com but that domain name was just too damn rude, so it was quickly renamed to GeoMeme.]

What does GeoMeme do?

GeoMeme measures real-time local twitter trends.

Tweeps are located on the map using public data from a number of iPhone twitter apps. When twitter launches its geolocation API, that will be used to locate even more people on the map.

GeoMeme measures and compares how many people on the map are tweeting about each of your two search terms:

The ‘magnitude’ of each search term is equal to the number of unique people tweeting per hour per square kilometer, so it increases when more people are tweeting in a smaller area.

Example: if 100 different people in an area of 10km² have tweeted about ‘love’ in the last 2 hours, the magnitude is 5.0 (100 divided by 10 divided by 2).

So you can search for ‘love’ and ‘hate’ and GeoMeme works out which one “beats” the other with the higher magnitude.

The default search terms are and smiley faces which provides a good measure of local happiness, as an example.

Can I use my iPhone?

Sure, or your iPod Touch. Here’s the screenshot:

Give me an example!

Thanks to some early coverage on The Register, Mashable, and Google Maps Mania, and winning Mashup of the Day on ProgrammableWeb, we’re off to a flying start. I’m glad GeoMeme is hosted on Google App Engine for scalability.

Here’s a selection of the most popular GeoMemes so far:

• beats in New York City
• Mega Shark beats Giant Octopus in LA
• Snow Leopard beats Windows 7 in Cupertino
• bridge beats swimming in San Francisco Bay
• wtf beats ftw in Washington

How does it all work?

I will leave the details of how it all works to another post, stay tuned for that.

“The cloud’s resources scale with user demands. Pay only for what you use” says RackSpace, the latest to join the cloud gang.

One problem for the cloud gang, however, is that hosting has always struggled as a low margin commodity business.

Rackspace has just hired Robert Scoble to help spread the message, so we should expect this space to soon get hotter than an Sun SPARC with a loose heatsink.

But where exactly can some value be added in cloud computing, to increase the margins and keep Scoble funded so he can continue to filter the signal from the noise on FriendFeed? Okay, that’s slightly selfish but it’s an interesting question.

The interesting answer IMHO is cloud datasets.

Having useful datasets available in the cloud will unlock value from the data by allowing a new generation of mashup. These aren’t mashups that simply use data from remote web services, like plotting Craigslist ads onto a Google Map. This involves the mashup (joining) of datasets in the cloud using the power and speed of a relational database.

This cloud database approach might also provide Twitter and other owners of valuable data with a revenue model that doesn’t depend on advertising.

Here’s 10 cloud datasets that I’d personally like to mashup, to help explain:

1. Wikipedia. Funnily enough Amazon Web Services has just announced that it now offers a 66Gb dataset of Wikipedia. “The wiki markup for each article is transformed into machine-readable XML, and common relational features such as templates, infoboxes, categories, article sections, and redirects are extracted in tabular form.” One example: imagine the opportunities for a start-up social travel site to mashup its content with the wealth of travel information now available on Wikipedia. Massive.

2. Geonames. It bugs me that everyone who wants to use the geonames database needs to duplicate 800Mb of data. Move it into the cloud! Example: the travel site can now analyse reams of user-generated content (or Wikipedia content) for up-to-date categorization and geo-coding onto a map. Another example: most websites need a simple (but updated-more-often-than-you-would-think) list of countries on the rego form. Wouldn’t it be good if everyone used the same (geonames) list?

3. MaxMind IP address lookup. Turn an IP address into an always accurate city location. Example: targeted ad serving and traffic analysis.

4. Google PageRank. For any URL, what’s the PageRank measure of quality? If this is relational data (rather than from a remote web service), it can be combined with other measures of quality at database speeds.

5. Real-time stock market data.

6. Real-time sports data.

7. Dodgy credit card numbers.

8. Dodgy email addresses.

9. Twitter. Some of the above might be considered proprietary rather than public data, which brings me to Twitter and a potential revenue model for them and the cloud gang. If you’ve got valuable proprietary data like Twitter has got (some would say that’s all they’ve got), then replicating it into a relational cloud database will unlock more value than could ever be extracted (or sold) via a remote web API.

Example: when visiting an e-commerce site, it would be nice to see only the product reviews submitted by people I am following on Twitter, sequenced by a measure of quality based on how often those people have been retweeted. Of course, the cloud gang already have the billing infrastructure and monitoring in place to work out exactly how much proprietary data you have used, and what to charge you for it. Did I mention yet that Jeff Bezos is an investor in Twitter?

The advertising pie is not big enough to fund the whole of the interweb, so perhaps paid data consumption is the revenue model for Twitter and others. Businesses are happy to pay hosting providers for commodity services like CPU cycles and disk space, so why not pay Twitter (via a hosting provider) for valuable information? Did I mention yet that Jeff Bezos is an investor in Twitter?

10. This one is further out there; private foreign keys. Imagine the Twitter dataset including the email address of users, joined using that email address to a Facebook or Digg dataset, but not revealing that email address in the result set. That’s number 10 on my list. It would need to work in a similar way to Facebook’s FQL or Yahoo’s YQL or Google’s GQL, to expose enough information to be useful but to not expose anything that would violate privacy concerns. I hope to write some more about this and the privacy implications in another post.

So, who’s in the cloud gang? Google is well placed with AppEngine and plenty of valuable datasets to get started with. Amazon has all the billing machinery in place to sell proprietary data from Twitter and others. Sun now has MySQL which already supports remote replication and column-level permissions to enforce private foreign keys. And now RackSpace has Robert Scoble. This will be an interesting one.

SearchWiki adds some innocuous buttons to your search results page, enabling Digg -style voting and Friendfeed -style commenting on each result.

I think this feature might prove valuable for some users, at least the bad spellers among us and those who prefer to repeatedly type the same search term into Google rather than use bookmarks or their memory.

However this feature becomes massively valuable for Google if enough people bother to vote for their favourite sites and add comments. Harnessing the collective wisdom of all those users is a great way for Google to improve upon its not-so-secret-anymore search algorithm.

Currently your own SearchWiki wisdom impacts only your own search results, nobody else’s. But the words chosen to explain SearchWiki do leave the door open for Google to evolve into a social search engine; “Customize your search results with your rankings, deletions, and notes — plus, see how other people using Google have tailored their searches.”

Personally, I’m not sure how much I want strangers (or bots) to influence (or game) my search results.

But I might want my friends and social networks to influence some of my search results.

If only Google could somehow identify all my friends in all my social networks, and keep track of their searching activity. Wait a minute…

SearchWiki + OpenSocial = mainstream social search.

The web is the their platform.

I’ve already set up my LinkedIn network and my Facebook friends, so why should I have to do it all again on every other site that has decided to go social on me?

When I heard the OpenSocial announcement last year, while I was F5ing the API URL, waiting to see the campfire video, I was imagining that the problem had been solved, by allowing any social networking site to share its social data with any other.

But the first incarnation of OpenSocial, actually the 0.7th as I write this, is more aimed at developers re-using code to make applications more portable, rather than data portability.

Then Plaxo released a LinkedIn sync feature which looked promising, but that was just two social sites, what about all the others?

Now it looks like Google has provided the solution, not as part of OpenSocial but with its new Social Graph API. Social data becomes portable simply by adding some XFN tags to the hyperlinks between your pages and your friends’ pages and your other pages (view the source of this page and search for rel=”me” to get the idea), then letting the Googlebot spider those links to work out the connections. Very simple and powerful. The internet is the platform.

This must upset Facebook, because the social data representing all those friend connections is a big part of their crown jewels. If Facebook changes profile pages to become publically available (or less revealing profile summaries, as LinkedIn has done), and adds some XFN tags, then that social data and the ad revenue extracted from it will start to trickle out onto the wider web. How long can Facebook resist?

Anyone could start to work out who knows who by using the Social Graph API. Reputable sites will put the decision of how to use that social data in the hands of the user. But there’s also a privacy risk here. Perhaps the answer to that is something along the lines of OpenId which puts the user firmly in control of how portable their identity data is.

My mind spins with the opportunities and challenges created by this great innovation. My favourite: combine social graph data portability with always-connected location-aware mobile devices (“phone”), and you can mashup the social landscape with the physical landscape you’re walking through.

Maybe that’s what Judge Dread’s helmet did.

When I got fed up with the games that you could play by copying Spectrum Basic code from the pages of a magazine (and fed up with the seek / transfer times involved), I decided it was time to learn programming. When I got fed up printing rude words for my mates using Spectrum Basic, it was time to get serious and learn Z80 assembly programming.

The outcome was a fruit machine simulator called ‘MegaFruit’ which had some revolutionary graphics and sound for its day, and also speech synthesis! MegaFruit took 7 squeeking minutes to load its 16,384 bytes of Z80 code from an audio cassette tape.

To my delight, I was able to strike a distribution deal with Thor Computer Games, who marketed and sold the game, and paid me money! Here’s the cassette sleeve artwork:

Sometime in the 1990s, my last remaining copy of the MegaFruit cassette tape was lost, I suspect as I moved my possessions around England during Uni days. I was devastated that I would never again see my creation working.

Then came Google to the rescue. I’ve been a fan of Google since their early days, and they did good. My Google Moment came in 2005, when I searched and found the website of a Spectrum addict in Russia who had been creating ROM images of games that could be interpreted by a Spectrum emulator written in Java. Before long I was playing MegaFruit again with a massive smile on my face. I even found a port of the emulator that let me play on my Smartphone.

And here it is using the excellent QAOP emulator (so named after the forward / back / left / right keys of choice back then):

Keys:

F11 = mute
PgUp/PgDn = sound volume