5 Stories of Innovation and 5 Stories of Dis-integration

It’s a widely covered topic, but innovation truly is the lifeblood of any business. Stagnation can lead to disaster: while a company could appear strong on the surface, as a dominant force within a particular sector, it might crumble in a few years if they are unable to adapt to changing markets, let alone lead the market in innovation.

To put this in perspective, we’ve identified some of the greatest innovators of recent times and given a brief analysis of what has allowed them to be so successful. As a comparison, there also some companies that were once market leaders, but their failure to adapt and innovate has led to significant drops in value and status.

Domination through Innovation

It’s no coincidence that some of the biggest companies in the world are also the biggest innovators. Below are some companies that not only adapted to changing markets, but have in fact led the charge in innovating and transforming our lives.


We’ve discussed previously how innovative Google can be, but it’s worth another look at this famously dynamic company. The search engine and its fantastically adaptive algorithms have helped define the way the vast majority of the world uses the internet. However, the true innovations for Google often happen behind closed doors, as the company constantly refines and optimises processes many users take for granted. This innovation is frequently in the form of developing and adapting machine learning programs, encapsulated under the name “Google Brain”. For example, in the past the process of transcribing addresses captured by Google’s street cameras to be usable in Google Maps was done by human engineers, who would spend hours pouring over countless images and deciding whether what was captured was an address or not. A team of google engineers were able to train their machines to handle this duty. The process has been streamlined to an almost ridiculous degree: all of the addresses captured in France could be transcribed in about one hour. Google Brain and machine learning has become the lynchpin for many of the company’s innovations beyond the realm of search engines: autonomous cars, advertising, voice recognition (in fact Google reports that machine learning reduced the error rate of their voice recognition software by 25% in only a year), and Google Translate, to name but a few. All of it is built around discovering innovative applications for their machine learning software. Rather than reinventing the wheel, Google are taking their seemingly simple tools and applying them in exciting new ways. By freeing up their staff from menial tasks, Google is allowing employees more freedom to develop exciting and innovative ideas.


It would be almost impossible to discuss innovative companies without discussing Tesla and its founder, Elon Musk.  Tesla and Musk have become bywords for innovation in recent years due to their revolutionary and innovative contributions to a broad range of fields. The results speak for themselves: the Tesla Model S car is widely considered one of the best cars currently available and has been for 2 years in a row according to Consumer Reports. Tesla currently operates at a loss (although they are poised to instantly become market leaders as the auto-industry shifts towards electric), and yet investors continue to sink increasingly large sums into the business, which is a testament to the faith that people have in the innovative capability and vision of both Tesla and Musk. As we’ve discussed previously, focussing purely on profits can be one of the biggest counters to innovation in a company, and it’s amazing to see Musk and Tesla defy this philosophy.

So what makes Tesla successful?  Innovation is built into the DNA of Tesla. Hiring policies are based on prospective employees’ ability to adapt and problem solve, rather than experience in relevant fields. Promotions and bonuses are innovation driven, with top-end category bonuses only available as a result of employee innovation at every level. Musk’s vision extends beyond cars. With his SpaceX project and developments into efficient public transport, Musk, and by extension Tesla, are poised to become some of the defining innovators of the 21st century.


Apple is known for being an innovator, and yet oddly enough the company has rarely been a true pioneer. The MacBook wasn’t the first laptop, the iPod wasn’t the first MP3 player, the iPhone wasn’t the first smart phone.  And yet their products have become market leaders and dominated their respective industries.

Their key innovations come from the features of their products. Take, for example, the Apple iPod. When it launched in 2001, it faced stiff competition from established brands, such as the Sony Walkman. But the innovative features the iPod offered gave it the boost it needed to become the symbol of the digital revolution: the ability to create playlists, shuffle songs and the integrated iTunes software were all revolutionary at the time and have now become staples of any kind of MP3 compatible device. The successes of the innovative services offered by Apple are key to the “halo effect” (a good product makes consumers more likely to trust other products from the same company) that has pushed customers to utilize Apple products across a broad range of devices: it’s not uncommon for a customer to utilize Apple devices for every electronic device they use.

You can pretty much create a timeline for this halo effect business model the progression:

Apple’s iMac created consumer trust for Apple devices > iPod created consumer trust for Apple’s portable devices > iPhone created the trust for Apple’s hand held computer and communication devices > the iPad launches and pretty much kick-starts the tablet market.

Once again, for most of these products, Apple was by no means the pioneering force. However through innovative solutions and applications, Apple continues to be a market leader and a force to be reckoned with.


IBM has been a giant in tech and computing since the industry’s infancy.  A key factor in IBM’s longevity has been its ability to adapt and evolve over time, a process that embraces innovation and abhors stagnation. Its current focus is Watson, its famous quiz show winning adaptive intelligence program. We’ve covered some of the innovative applications for Watson in the past, but the applications for the program are limited only by imagination. IBM shows how the development of an innovative and adaptive product can kick-start innovation for other companies, across a broad range of sectors.


Once a humble online bookseller, Amazon has grown to become a dominant force in the tech industry, offering services that are revolutionizing almost every aspect of our lives. This can be seemingly little things: 1-Click and next-day delivery have transformed consumer expectations for online retail. It can be big things: getting in on the ground floor for commercially available cloud services has allowed Amazon to become one of the market leaders in the cloud industry. In a similar way to Apple, Amazon frequently relies on the halo effect to expand its influence across various sectors. The trust built up by the efficiency of its online retail platform has granted its licence to be adventurous and ground-breaking in its projects. Any other company that promised drone-deliverywould likely get laughed out of the building, but Amazon’s status and reputation as a cutting edge innovator grant it a unique position to drive and transform entire industries.


Honorary Mentions

  • Netflix
  • Facebook
  • Uber


The mighty have fallen 

It’s a fact of business that just as there are victors, there must be losers. Below are some of the largest falls-from-grace as a result of a lack adaptation and innovation.


Although we didn’t go into detail on Netflix’s innovations, the implications of the company are quite clear:  from humble origins as a DVD-by-mail subscription service to the most popular TV network in America. But this rise has left many of its competitors in the dust, most notably Blockbuster. Once a byword for video-rental and a standard part of an average family’s routine, Blockbuster’s failure to change its business model, relying solely on its established brand name, led to its downfall. Customers expect ease of access from the comfort of their own home, something that Netflix quite famously offers, without the peril of Blockbuster’s infamous late fees. To add insult to injury, Blockbuster passed on the opportunity to acquire Netflix for a mere $50 million in 2000.


Once the device of choice for professionals, Blackberry failed to adapt to a changing market and customer demands. Actively rejecting the touch-screen popularized by smartphones such as the iPhone, Blackberry was left behind. As consumers enjoyed the freedom and ease-of-use offered by touch-screen in their personal lives, a shift in workplace policy arose and BYOD (Bring Your Own Device) became standard. In a similar manner to Blockbuster, Blackberry failed to address shifts in consumer demands which allowed them to be overtaken by their rivals and left playing catch-up.

Polaroid & Kodak

Both companies were once giants of the photography industry. Kodak dominated the affordable camera industry, while Polaroid was a household name for its near-instant available photographs. However, the rise of digital photography in the 90s left them reeling. The initial cost of the technology meant that Kodak was unwilling to invest (also, much of their profits came from the photograph film, rather than the camera devices), meaning that by the time digital cameras became more ubiquitous as cheaper models appeared, there were already established and trusted digital camera brands in the market which Kodak simply couldn’t compete with. Polaroid’s unique selling point of quickly viewable photographs was eclipsed by digital’s even faster ability, a feature enhanced by producing higher quality images than Polaroid could.  As the 2000s rolled around, both companies were in dire straits with Polaroid filing for bankruptcy in 2001, while Kodak kept going until 2012.

To add more salt to their wounds, it was actually Kodak researchers who developed the technology for digital cameras back in the 1970s, but the board decided against moving forward with a commercial model. Kodak did make billions from the technology patent, but that ran out in 2007 (which perhaps explains why they were able to hold on so much longer than Polaroid).


Yahoo’s glory days have long faded. In the early 00s, they were the kings of the internet, commanding roughly 20% of online advertising. Now they struggle to keep up with the top competitors such as Google, Facebook, and Microsoft. The reasons for this are quite extensive, but the most obvious one was their inability to rapidly invest in innovation. A quick glance at some of their missed opportunities can create an almost audible groan of frustration:

  • In 2002, Yahoo had the opportunity to acquire Google for $5 billion. Yahoo’s board balked at the sum (which in retrospect is an absolute steal) and rejected them. As of 2016, Google is worth over $500 billion.
  • In the late 90s and early 00s Doubleclick were the dominant force in internet display ads. In 2007 they were acquired by Google for $3.1 billion, an acquisition that has supported Google’s ascension to the undisputed champions of internet advertising. Yahoo missed its chance to acquire Doubleclick, and as such it has fallen well behind Google in terms of advertising.
  • In 2006, Mark Zuckerburg turned down a $1 billion acquisition offer for Facebook from Yahoo. Rumour has that if they’d offered slightly more, Zuckerburg would have been forced to acquiesce, and Yahoo would now own a company that, as of 2016, is valued at $328 billion.

It’s not to bold a claim to state that if these deals had gone through, Yahoo could be a very different beast entirely. Perhaps I would have been yahooing examples for this article.

(Dis)Honourable Mentions

  • Borders Group
  • Nokia


What we can learn

The examples I’ve given above are all from big companies, but we can draw some advice from them that can be integrated into any level of business.

DO let your imagination off the reins. Both IBM and Google have shown that creative applications of simple tools can lead to enormous success and innovation.

DON’T be overconfident in your current strengths. All of the examples of failing businesses we gave can be traced back to one root cause: overconfidence that their services or products will always be in demand.

DO branch out. In contrast to the above, all of the successful businesses have used their strong core business as a platform to expand into a large variety of different fields.

DON’T ignore the competition. Failing to pay attention to competitors and how consumers are responding to their products can lead to disaster. If a competitor is offering something that you do not, and there is a positive response to it, it might be worth investigating adapting something similar into your own business. As Apple shows, it’s not necessarily about being a pioneer, it’s about doing it better than anyone else.

DO encourage innovation in the workplace. Tesla and Google both invest resources directly into encouraging their employees’ innovation. Remember, just because you can’t see a way to improve something, doesn’t mean other people can’t.

DON’T be overly cautious over costs. When it comes right down to it, innovation can be risky, and an expensive risk at that. However being too timid can lead to massive missed opportunities, as with Kodak and Yahoo, while being willing to take the plunge has left Tesla poised to dominate the auto-industry in forthcoming years.

Image attribution

Image provided courtesy of Boegh

Further Reading

eWeek: 10 ways Amazon keeps pushing the innovation envelope

Fast Company: The Most Innovative Companies of 2016

Forbes: The World’s Most Innovative Companies

Investopedia: Companies that went bankrupt from innovation lag

Telegraph: Apple’s greatest innovations in pictures

Vocoli: 10 Companies that failed to innovate and what happened to them.


Small innovations in big companies

Further to my recent post on how “EBITDA killed innovation”, I thought I would do a post on how small innovations can still occur in big companies – and sometimes that’s all it takes to make a big difference: a small innovation.

Companies are increasingly being encouraged to ‘think entrepreneurially’ – looking at how they can harness the entrepreneurial side of their workers to make a difference at the corporate level.  It’s sometimes called “intrapreneurship” – but it can be very difficult to effect change within a large, multinational organisation where each decision needs to be approved by ten tiers of management.  Big companies that span the globe, with tens of thousands, if not hundreds of thousands, of employees struggle to act with the agility and speed that entrepreneurship requires.  An employee could have a fantastic idea, it could be supported by all of management, but bureaucracy and red tape get in the way – and the idea wilts eventually.

Some companies, such as Lockheed Martin, have tried to recreate the small team type entrepreneurial approach by having dedicated teams focused on developing revolutionary new ideas – and perhaps this separation between the bloated corporate company and the individual teams is what is needed – maybe entrepreneurship cannot be scaled across hundreds of thousands of employees.

The other issue with large companies is that in order to get large, they have probably been around a long time.  And if they have been around a long time, then they have spent many years doing things a certain way, or developing processes and procedures to manage each activity.  This is not an enabler when it comes to innovation – this is trying to build something new with old tools and old thinking.  It’s rarely possible.

An innovative way of thinking is being employed by larger companies, who are inevitably seeing the benefits that innovation brings to smaller, agile companies – PWC for instance runs competitions where staff compete to come up with innovative new ideas and products.  This relies on gamification to take the emphasis away from being ordered by a manager to create new products, and further towards a system where employees come together of their own accord to try and ‘win’ – and that win is a win for bother the employee and the company alike.

And maybe we have reached the reason why innovation fails in big companies.  Because in smaller companies, innovation is usually borne out of the enthusiasm of the staff who are self-motivated to come up with ideas and new solutions.  Maybe innovation cannot be summoned, ordered or demanded.

Forbes cites Tesla, Salesforce.com and Amazon.com in its top ten most innovative companies’ list.

Tesla is known as a disruptor – and its innovative approach is down to the fact that it has always operated in a different way to the rest of the industry.  Whilst its competitors were chasing cheaper manufacturing methods, Tesla focused on the high-end – outperforming other manufacturers and focusing on developing better power systems.  Its innovation was on where to focus, rather than purely developing new products.  The innovation spectrum is wide, and companies of all sizes are trying to introduce small innovations into their operations in a bid to stay relevant, fresh and, most importantly, in business.

Some corporations are now launching ‘entrepreneur in residence’ programs – hoping that the entrepreneur will advise them on new directions and provide much-needed inspiration amongst existing staff.  The bi-product of such programs is that they probably create more motivation for the staff – making it a more exciting and interesting place to work.

But we are now focusing on making the employees innovative.  What about those leading the company.  McKinsey reckons that aspirations are critical for a company, and have the power to be a “compelling catalyst” – so company leaders need to think about how they inspire their workforce, their clients and also the wider industry.  Innovative people go to work at Google, because Google put out messaging that they are a future-thinking, anything-is-possible organisation.  Innovation begets innovation.

So how can we start making those small innovations, whilst working for big companies?

Here are a few ideas I have had:

  • Use the right words: Make sure that your words, whether you are a company leader or a member of staff, are encouraging opportunity. Negative handling of employee ideas will unfortunately discourage others from coming forward with opportunities.
  • One eye on the future: Think about innovation as you would a sales pipeline – there are innovations to focus on now, innovations for the near future and grand ideas about the distant future. What’s around the corner, what’s coming in ten years’ time and how can you make steps now to put in place the foundations for innovation in the future?
  • Make an effort to be close to innovation: Partner with innovative companies, sell to innovative clients and get close to them, choose staff who have worked for innovative companies previously – get as close as you can to innovation. There are lots of ways – think about all of your business connections across your entire organisation.  Turn the innovation scale up by just 10%.
  • Don’t let targets get in the way: Like my EBITDA Innovation article, targets are important but if you’re not in business in five years’ time then those targets will have been in vain. Have a target for innovation – an idea today might be your revenue tomorrow.


Here is a Ted talk I’d recommend you watch about “Where good ideas come from” and how we can harness innovation in our daily lives, and also in business:




Image provided courtesy of Cristian Carrara

You have to love Google Cardboard

You really need to see this cardboard hack they made which turns out to be a little bit of a dig at the Oculus Rift, but also intriguing in and of itself:

Google Glass is hopping the pond.

The Mountain View, California-based search giant announced Monday it is opening up its Glass Explorer program to the United Kingdom–the first time Google Glass will be sold outside the U.S. U.K. residents who are 18 or older will be able to purchase Glass for £1,000, the equivalent of about $1,700, $200 higher than its price tag in the U.S.

For more information please visit http://www.fastcompany.com/3032276/most-innovative-companies/google-opens-up-glass-explorer-program-outside-us


Now that Google is allowing anyone with a cool $1,500 lying around to score themselves a pair of Glass, you’ll probably start seeing a lot more tech geeks wearing headsets in public talking to themselves. Our hands-free, hyper-tethered future is well on its way! So if voice command interfacing is the wave of the future, what good is something seemingly as reductive as an input keyboard?

For further information please visit – http://www.fastcompany.com/3030617/fast-feed/take-a-look-at-the-first-keyboard-for-google-glass-in-this-twee-tastic-video

Your Big Data Is Worthless if You Don’t Bring It Into the Real World

In a generation, the relationship between the “tech genius” and society has been transformed: from shut-in to savior, from antisocial to society’s best hope. Many now seem convinced that the best way to make sense of our world is by sitting behind a screen analyzing the vast troves of information we call “big data.”

Just look at Google Flu Trends. When it was launched in 2008 many in Silicon Valley touted it as yet another sign that big data would soon make conventional analytics obsolete.

But they were wrong.

If the big-data evangelists of Silicon Valley really want to “understand the world” they need to capture both its (big) quantities and its (thick) qualities.

Not only did Google Flu Trends largely fail to provide an accurate picture of the spread of influenza, it will never live up to the dreams of the big-data evangelists. Because big data is nothing without “thick data,” the rich and contextualized information you gather only by getting up from the computer and venturing out into the real world. Computer nerds were once ridiculed for their social ineptitude and told to “get out more.” The truth is, if big data’s biggest believers actually want to understand the world they are helping to shape, they really need to do just that.

It Is Not About Fixing the Algorithm

The dream of Google Flu Trends was that by identifying the words people tend to search for during flu season, and then tracking when those same words peaked in the real time, Google would be able alert us to new flu pandemics much faster than the official CDC statistics, which generally lag by about two weeks.

Screen Shot 2014-04-10 at 2.33.09 PM

For many, Google Flu Trends became the poster child for the power of big data. In their best-selling book Big data: A Revolution That Will Transform How We Live, Work and Think, Viktor Mayer-Schönberger and Kenneth Cukier claimed that Google Flu Trends was “a more useful and timely indicator [of flu] than government statistics with their natural reporting lags.” Why even bother checking the actual statistics of people getting sick, when we know what correlates to sickness? “Causality,” they wrote, “won’t be discarded, but it is being knocked off its pedestal as the primary fountain of meaning.”

But, as an article in Science earlier this month made clear, Google Flu Trends has systematically overestimated the prevalence of flu every single week since August 2011.

And back in 2009, shortly after launch, it completely missed the swine flu pandemic. It turns out, many of the words people search for during Flu season have nothing to do with Flu, and everything to do with the time of year flu season usually falls: winter.

Now, it is easy to argue – as many have done – that the failure of Google Flu Trends simply speaks to the immaturity of big data. But that misses the point. Sure, tweaking the algorithms, and improving data collection techniques will likely make the next generation of big data tools more effective. But the real big data hubris is not that we have too much confidence in a set of algorithms and methods that aren’t quite there yet. Rather, the issue is the blind belief that sitting behind a computer screen crunching numbers will ever be enough to understand the full extent of the world around us.

Why Big Data Needs Thick Data

Big data is really just a big collection of what people in the humanities would call thin data. Thin data is the sort of data you get when you look at the traces of our actions and behaviors. We travel this much every day; we search for that on the Internet; we sleep this many hours; we have so many connections; we listen to this type of music, and so forth. It’s the data gathered by the cookies in your browser, the FitBit on your wrist, or the GPS in your phone. These properties of human behavior are undoubtedly important, but they are not the whole story.

To really understand people, we must also understand the aspects of our experience — what anthropologists refer to as thick data. Thick data captures not just facts but the context of facts. Eighty-six percent of households in America drink more than six quarts of milk per week, for example, but why do they drink milk? And what is it like? A piece of fabric with stars and stripes in three colors is thin data. An American Flag blowing proudly in the wind is thick data.

A piece of fabric with stars and stripes in three colors is thin data. An American Flag blowing proudly in the wind is thick data.

Rather than seeking to understand us simply based on what we do as in the case of big data, thick data seeks to understand us in terms of how we relate to the many different worlds we inhabit. Only by understanding our worlds can anyone really understand “the world” as a whole, which is precisely what companies like Google and Facebook say they want to do.

Knowing the World Through Ones and Zeroes

Consider for a moment, the grandiosity of some of the claims being made in Silicon Valley right now. Google’s mission statement is famously to ”organize the world’s information and make it universally accessible and useful.” Mark Zuckerberg recently told investors that, along with prioritizing increased connectivity across the globe and emphasizing a knowledge economy, Facebook was committed to a new vision called “understanding the world.” He described what this “understanding” would soon look like: “Every day, people post billions of pieces of content and connections into the graph [Facebook’s algorithmic search mechanism] and in doing this, they’re helping to build the clearest model of everything there is to know in the world.” Even smaller companies share in the pursuit of understanding. Last year, Jeremiah Robison, the VP of Software at Jawbone, explained that the goal with their Fitness Tracking device Jawbone UP was “to understand the science of behavior change.”

These goals are as big as the data that is supposed to achieve them. And it is no wonder that businesses yearn for a better understanding of society. After all, information about customer behavior and culture at large is not only essential to making sure you stay relevant as a company, it is also increasingly a currency that in the knowledge economy can be traded for clicks, views, advertising dollars or simply, power. If in the process, businesses like Google and Facebook can contribute to growing our collective knowledge about of ourselves, all the more power to them. The issue is that by claiming that computers will ever organize all our data, or provide us with a full understanding of the flu, or fitness, or social connections, or anything else for that matter, they radically reduce what data and understanding means.

By claiming that computers will ever organize all our data, or provide us with a full understanding of the flu, or fitness, or social connections, or anything else for that matter, they radically reduce what data and understanding means.

If the big data evangelists of Silicon Valley really want to “understand the world” they need to capture both its (big) quantities and its (thick) qualities. Unfortunately, gathering the latter requires that instead of just ‘seeing the world through Google Glass’ (or in the case of Facebook, Virtual Reality) they leave the computers behind and experience the world first hand. There are two key reasons why.

To Understand People, You Need to Understand Their Context

Thin data is most useful when you have a high degree of familiarity with an area, and thus have the ability to fill in the gaps and imagine why people might have behaved or reacted like they did — when you can imagine and reconstruct the context within which the observed behavior makes sense. Without knowing the context, it is impossible to infer any kind of causality and understand why people do what they do.

This is why, in scientific experiments, researchers go to great lengths to control the context of the laboratory environment –- to create an artificial place where all influences can be accounted for. But the real world is not a lab. The only way to make sure you understand the context of an unfamiliar world is to be physically present yourself to observe, internalize, and interpret everything that is going on.

Most of ‘the World’ Is Background Knowledge We Are Not Aware of

If big data excels at measuring actions, it fails at understanding people’s background knowledge of everyday things. How do I know how much toothpaste to use on my toothbrush, or when to merge into a traffic lane, or that a wink means “this is funny” and not “I have something stuck in my eye”? These are the internalized skills, automatic behaviors, and implicit understandings that govern most of what we do. It is a background of knowledge that is invisible to ourselves as well as those around us unless they are actively looking. Yet it has tremendous impact on why individuals behave as they do. It explains how things are relevant and meaningful to us.

The human and social sciences contain a large array of methods for capturing and making sense of people, their context, and their background knowledge, and they all have one thing in common: they require that the researchers immerse themselves in the messy reality of real life.

No single tool is likely to provide a silver bullet to human understanding. Despite the many wonderful innovations developed in Silicon Valley, there are limits to what we should expect from any digital technology. The real lesson of Google Flu Trends is that it simply isn’t enough to ask how ‘big’ the data is: we also need to ask how ‘thick’ it is.

Sometimes, it is just better to be there in real life. Sometimes, we have to leave the computer behind.

Editor: Emily Dreyfuss

Source: http://www.wired.com/2014/04/your-big-data-is-worthless-if-you-dont-bring-it-into-the-real-world/

Tomorrows World Infographic

What a great infographic, the information has been taken from various sources some interesting highlights:

2015 the first immortal mouse created
2020 Many humans permanently wearing devices that record and store information
2030 The moon has been claimed as a territory by China
2040 Cars are now purely automated and driver free

Google, Consumer Durables and the Internet of Things (IoT)

Thanks to http://eaglepointadvisors.com/

Google pays $3.2B for a hardware (industrial) startup called Nest who has sold just over $250 million of its cool looking thermostat since its launch in November 2011.

These are crazy numbers!!

See below for our perspective on why every consumer durables company should be developing a strategy around IoT — the Internet of Things

Q: How much did Google pay?
A: Probably between 3-6x future revenues for an industrial company.

Q: Why on earth would Google pay that much?
Google spends stupid money and shuts down acquisition failures all the time. This is just going to be another one.
Google needed Nest’s team because their thermostat project was going nowhere
Google played an end-around Apple, who has been carrying the Nest in their stores
Google has its eye on something much bigger than just thermostats
Google had to outbid a term sheet that put Nest’s valuation at $2 billion
A: 2,3,4,5
Google is focusing on deep infrastructure across the planet. They have been investing in groundbreaking, gamechanging and hugely disruptive technologies that will change the behavior of consumers, not just make their lives a little easier.
Examples include:

driverless cars frees up over 45 minutes to an hour of productive time for hundreds of millions of workers all over the world
intelligent eye-glasses potentially change the nature of human interaction and human perception of reality
high altitude balloons circling the earth delivering high bandwith to remote and rural areas of the world that do not have internet access.
reverse aging
test tube burgers
home automation

Q: So why did Google buy Nest in particular
A: Energy and Home Automation
Google wants to be at the center of the energy grid collecting tons of data on energy usage. No better place to start than at the point of consumer consumption whose data can be collected in exchange for improvements in usability and potential cost savings.Home automation is the second leg of this purchase. By picking off the most obvious of home instruments, the thermostat, Google gets a great baseline to build on top of. With a world class set of engineers, we can see Google layering many other home appliances into their grid.

Q: What does this mean for Consumer Durable Goods Companies?
A: Big opportunity and big trouble — must be digitally great

Big Opportunity for companies who seize the opportunity to innovate with their customers, providing easy to use products that provide feedback loops that are meaningful and change behavior.Big Trouble if:

“Digital” is defined only as a new website. Digital means user experience. Nest has demonstrated that industrial products can be digitally sophisticated yet easy to use.
Products must setup easily. Durable goods products cannot require a degree in electrical engineering to decipher manuals and implement these new devices.
Products must work to expectation. The Jawbone Up is a great example of not living up to its promise. It measures steps for calories spend but can’t track the calorie spend from doing cross-fit or yoga. It’s supposed to track your sleep, but if you fidget a lot, even as a deep sleeper, it does not register your sleep accurately.
Consumer Durables Next Steps

Companies will have to think outside the box, experiment and build out their user experience and expertise in mobile and networking.

Thanks to http://eaglepointadvisors.com/2014/01/26/google-consumer-durables-internet-of-things-iot/

The 4 Flavors of The Internet of Things

Two years ago, Fast Company reported on the “great tech war” of the four leading horsemen of the Internet–Facebook, Amazon, Google, and Apple (let’s call them the FAGA Four).  The race for Internet dominance has intensified since then, with Amazon pitting the Kindle Fire against the iPad and Google responding to Facebook with Google+.  Each of these four companies has moved from its base to capture more social, mobile, local, delivery, advertising, devices, and design dominions.

Even their emergent competition for the enterprise IT market has intensified lately, when Google introduced its Compute Engine and slashed the prices for its cloud services. Looks like it finally decided to make a more serious attempt to diversify from the $0.5 trillion global advertising market—where it gets almost all of its revenues—to the $3.7 trillion IT market. Facebook is the only one of the “Gang of Four” (Eric Schmidt’s term) that has stayed away from the enterprise. But for how long? After all, it has been leading the Open Compute project for the past two years, aiming to “spark a collaborative dialog” about designing and enabling “the delivery of the most efficient server, storage and data center hardware designs for scalable computing.”

A visionary statement like this befits a leading horseman of the Internet.  In the rapidly changing Internet landscape, when new, attention-grabbing companies rise from nowhere every few months (and have the audacity to refuse Facebook’s $3 billion acquisition offer), you sustain your leadership by pursuing a vision or at least being perceived as having one. “Vision envy” is how one of Leo Laporte’s guests on a recent This Week in Tech described the latest moves of the Internet’s leaders.

Today’s vision must revolve around the most significant Internet trend so far in this second decade of the 21st century: The Internet of Things or more broadly, the Internet of Stuff (the earliest mention of the term I could find is this 2009 SlideShare presentation). By 2020, IDC tells us, it will connect 212 billion “things.” And machine-generated data,according to IDC, will account for 42% of all the data created in the year 2020.

Based on recent news regarding visionary announcements or actions by the Gang of Four, I would like to offer the following four flavors of The Internet of Stuff.

The Internet of flying stuff: Connected “things” that move above the earth’s surface. The most recent move in developing the vision or the reality of the Internet of flying stuff was of course Amazon’s unveiling of its experimental Prime Air and its delivery drones. That this is not entirely pie in the sky or just a successful PR stunt by Amazon was made clear by the FAA’s announcement on December 30 of the six public entities that will develop research and testing sites for commercial drones. Earlier in 2013, Google unveiled Project Loon, “balloon-powered Internet for everyone.” It’s Google’s vision for extending the Internet to remote and rural areas. Adding a public sector dimension to this vision, the Brazilian government followed a few months later with its own version of a balloon-based Internet of flying stuff, Project Connect.

The Internet of moving stuff: Connected “things” that move on and below the earth’s surface.  There’s emerging interest in the potential benefits of connecting to underground systems, but the focus today is on the most visible moving things in our world: cars. The newly redesigned Ford Fusion has 74 sensors, including radar, sonar, cameras, accelerometers, temperature gauges and rain sensors, soon to substitute for drivers. By 2020, says Nissan’s CEO Carlos Ghosn, mainstream automakers will offer driverless cars, to avoid being “disrupted” by Silicon Valley. Google has led the effort to get drivers to use the Internet rather than waste their time driving but it may now be expanding the vision to include any autonomous moving thing. It recently acquired Boston Dynamics, a leader in mobile robots technology, and the eighth robotics company it has acquired in 2013. “Google is intent on building a new class of autonomous systems that might do anything from warehouse work to package delivery and even elder care,” said The New York Times. In a statement that captures the essence of the Internet of moving stuff, Google’s Andy Rubin told the Times— “computers are starting to sprout legs and move around in the environment”—promising that his Moonshot project will yield commercial products “in several years.”  One place to see mobile robots already in action, albeit indoors only, is Amazon’s distribution centers, especially after it acquired Kiva Systems in 2012. WatchKiva’s Mick Mountz describes his robots “Highway Driving” in the warehouse—how long before they will move to real highways?

Internet of social stuff: Connected content in context or making sense of the quintillions of bytes connected people create every day. Facebook recently announced the formation of a working group that will “use new approaches in AI to help make sense of all the content that people share so we can generate new insights about the world to answer people’s questions.” It then established a partnership with New York University for a new center for artificial intelligence, headed by Yann LeCun.  Understanding context is what “search” is all about and of great interest to all members of the FAGA Four. In 2013, Apple bought Topsy, which “might have been appealing to Apple because of its expertise in searching and indexing the vast amounts of unstructured content that make up Twitter,” says Rob Bailey, CEO of DataSift; Amazon acquired social reading site Goodreads; and, not to be outdone on its own turf, Google launched its “Knowledge Graph,” demonstrating its growing understanding of the relationships between people, places, and things.

Internet of talking stuff:  Connecting moving and stationary “things” that communicate. This is all about user interface and it is Apple’s turf to lose.  In its 1987 mother-of-all-vision-videos, the knowledge navigator, Apple showed—twenty-four years before it launched Siri—a tablet-based “personal assistant” conversing with the user, a text-to-speech system and a gesture-based interface. The aforementioned acquisition of Topsy was considered also as potential boost to Siri’s search capabilities, but more to the point, “Apple has assembled a small team of notable names in speech technology and is looking to expand those efforts in the Boston area,” according to Xconomy. The same report points to an Amazon R&D team whose mission is “to push the envelope in automatic speech recognition (ASR), natural language understanding (NLU), and audio signal processing.” Google, for its part, continued to expand its capabilities in this area in 2013, e.g., recentlyextending voice search to PCs.

Xconomy’s Wade Roush thinks that the next “paradigm shift” will not come from the FAGA Four and Quartz’s Christopher Mims asserts that 2013 was “a lost year for tech,” as “M&A replaced innovation.” Maybe we will not see the Next big Thing emerging from Facebook, Amazon, Google or Apple. Maybe it will come from IBM, Samsung, or a China-based player. Maybe it will come from a startup that will refuse to be acquired and will grow to overshadow the FAGA Four. In any event, the Next Big Thing will probably be in one of the flavors (or a combination of two or three flavors) of the Internet of Stuff.

[Originally published on Inside Tech Talk]

Thanks to http://whatsthebigdata.com/


The Evolution of Big Data Processing at Google (Video)

Google’s Daniel Sturman at the IEEE Computer Society’s “Rock Stars of Big Data” event, October 29, 2013. Great video well worth watching.