The Fourth Industrial Revolution is Here and Why Google is Getting it Right

Industrial revolutions are about harnessing the power of the day to drive a breakthrough in business or social conventions to produce a sea change in our everyday lives.

The First Industrial Revolution used water and steam power to drive industrial activity. We saw the rise of the locomotive that enabled rapid transport of people and goods. Suddenly commerce could span the once insurmountable mountain passes and open prairies that kept civilization in pockets. Mechanization of the farm also meant less people were needed in food production, freeing people to explore 

more academic topics. 
The Second used electricity to fuel the rise of the modern factory and around the clock productivity aided by multi-shift workers and the light bulb. This in turn drove further urbanization and accelerated moving people off an agrarian lifestyle and the rise of centralized cities and a suburban lifestyle.
The Third used microprocessors and information technology to automate production planning. This saw the rise of process efficiency. Former manual processes were now handled by computers freeing up people to again rise above these manual task e.g. ERP, Supply Chain and CRM efficiency, ATM’s, Self-checkout, ecommerce.

Now a Fourth Industrial Revolution is here.

This new revolution is happening because of a few things that have come together in recent years.

The rise of hyper scale cloud computing.  At the click of a mouse I can rent computing power that 10 years ago would have taken millions of dollars of investment, floor space, people and power to access.  The democratization of compute.

IOT – Sensors are everywhere. These sensors are continually exhausting unparalleled amounts of data. Whether it’s bio-informatics as simple as your Fitbit to genomic sequencing to predict your propensity for thyroid cancer and formulate a targeted therapeutic and improving outcomes that just a decade ago were trial and error guess work. Or IOT sensors on each stalk of corn in a farmer's field driving higher yield and eliminating crop loss from over/under watering, fertilizers and pests.

And lastly advanced algorithms in Machine Learning and Artificial Intelligence. In March of 2016, the world was stunned when Google DeepMind defeated a legendary Go champion Lee Se-Dol from South Korea.  Most AI experts thought that type of deep neural networking was a decade away. Go is a simple game and take only a few minutes to learn, but the possible combinations of moves are endless. The number of potential board positions is: (That big number over there) a number greater than the number of atoms in the universe. That's a lot of atoms.  Because there are so many different combinations, Go is the “Holy Grail” of AI.

Which brings me to why Google is getting it right.

Cloud computing takes scale.  Check

A hyper scale network free from the public internet.  With a private fiber network in 70 points of presence in 33 countries.  Check.

But AWS, Azure and even IBM and Oracle would argue “me too” on the above.

So why is Google poised to be the center of the Fourth Industrial Revolution? 

YouTube, Vision API, Video API ,Tensor Flow and the democratization of AI that's why.

For instance, every minute of every day, 300 hours of Video are uploaded to YouTube.  1.3 Billion people watch 5 Billion videos every day. (That’s democracy in action) When you search for “Dogs” on YouTube, you’re not just searching meta-data tagged manually to a video. YouTube uses the open source Tensor Flow library to find all images of a dog embedded in ANY video.  Even if the video has nothing to do with a dog or a dog just happen to stroll across a few frames of an hour long video about baseball.  But how did the algorithm know what a dog looks like? There’s lots of different dogs out there and coding a traditional algorithm to cover all dog conditions would be ridiculous.  Google Machine Learning and Google compute with its ability to process billions of references to hone the algorithm to statistically predict that image is a dog. That’s how.

So how does the ability to find a dog in a video spell a sea change for mankind? 
It’s not just about the videos or the images or the audio, it’s about combination of massive amounts of compute on demand, a super-fast network, the advanced ML algorithms and the ability to unlock immense amounts of intelligence from the unstructured and machine generated sources.  Couple this on top of the open source nature of the Tensor Flow libraries and you have the flywheel effect of Billions of people, data sources and compute engines. (More democracy in action)

Imagine next generation apps to predict fraud, money laundering, powering self-driving autonomous cities that optimize people’s needs to get somewhere with the capacity constraints of the freeways. But this time, everyone is humming along at 80 MPH with zero accidents.

Insurance claims being handled quickly, paid efficiently with minimal fraud because the corpus of accident video, image and report data has seen this exact scenarios 1000’s of times before.

Applications were once constrained by how fast a human could type or a printer could print. That’s all changed.  Say you want to learn how to replace the transmission in a delicate piece of engineering like your late model BMW. Wouldn’t you much rather learn by watching a video specifically customized for you with the aggregated relevant clips from the largest video library on the planet with each step by step procedure and pitfalls?  A video tailored perfectly to your experience level and perspective.  The alternative would be a dry manual written from one perspective and for a mass audience without regard to your needs and reference points. Life is good when the worlds data and compute resources come together.

The platforms have arrived and are getting more powerful by the minute.  The application possibilities are gated only by our creatively.

Affinity establishes community, community builds trust, trust lubricates commerce

People establish trust based on commonality.  Facebook recently launched a competitive offering to Craigslist.  But just like eBay is an efficient market for sellers due to its high liquidity of buyers therefore creating the most efficient market for sellers driving to the optimal price, Facebook did something really smart as they are encouraging people to build localized groups where buyers and sellers of personal items can meet. But unlike Craigslist, Facebook uses their built-in community to create trust to drive to an efficient market.

I like selling things.  There I said it. But truth be told, I’m always selling something.  In my personal life, I’m constantly listing things on Craigslist, eBay and now Facebook. It’s the thrill of fishing with multiple lines in the water.

I’m fascinated by and a perennial student of different selling models and dynamics. Facebook is my latest fascination.  You can create a Facebook affinity group and sell, trade or barter stuff within that group.  Why? Because affinity establishes community and community builds trust and trust lubricates commerce.

As an experiment, I’m selling the same item in the venues of: Craigslist and Facebook.  Although Craigslist is better organized and categorized and would therefore intuitively drive more people in need of my item to me, the power of Facebooks affinity crushes Craigslist. I posted a personal electronics item on Craigslist about a week ago.  I’ve received 2 inquires. Poorly qualified, not ready to buy now. Craigslist trolls. Facebook on the other hand, as soon as I posted the very same item, I was inundated with 15+ Facebook personal messages from people ready to buy my item right now.  Why?

The Facebook selling group is called “Danville for Sale or Free”. It is by invite only, gated by a moderator and “exclusive” to people who live in Danville.  People are driven to trust based on our affinity for our little home-town of Danville.  One person even said, “I trust you, we’re both Danvilleians” That’s the secret code for people who live in Danville.

Kind of odd. But think about it, when you’re in the farthest reaches of Asia or Europe and you hear someone with an American accent, your ears perk up and you say, “Hey, buddy, American?”  When they answer back with “Hell Yes!”, this guy’s your new best buddy.  You’re drinki’n and talking Rogers vs. Brady vs. Brees with him. If you ran into the same schmo in Orange County, you probably
would have cut him off in the In-n-out Burger drive-thru and then flipped him off when he gives you the stink-eye, but now the power and affinity of the blue passport has you huggin and chuggin like old friends.

Mmmm, Affinity establishes community and community builds trust, trust lubricates commerce. (Said in your best Yoda voice)

Threading the Three Needles of a New Product

Have you seen the video of the guy in the Wingsuit threading the needle in a rock wall at around 160KM/Hour?  Watch it. It underscores the point that there is a subtle difference between wingsuit glory and being a stain on a rock wall in the Swiss Alps.

New product introduction at a start-up is kinda like that wingsuit maneuver.  Careful planning, in-flight adjustments followed by moments of self-doubt and shear panic. 

As a fledgling company without established customers, channels and brand, you have the combination that makes start-ups so hard and yet so rewarding at the same time. You see being at an established company you can lean on your stabilizing ballast of revenue, customers, a ramped channel or direct field with established customer relationships.  Introducing a new product into an existing channel presents its own challenges but nothing is as daunting as a new product into a new channel.

This is why new product intro at a start-up is like threading three needles at once. The right message at the right time to the right person.

Subjects that are top of mind and selfishly make a person’s career prosper. In other words, technology that will make them successful individuals in their organization.

You’re asking them to change what they are currently doing, how they allocate their budget and how they train their people. 

Tech people brand themselves as “Certified Professionals” in vendor proprietary technology whether its VMWare, SAP, Microsoft or Oracle, this personal branding is strongly tied to technologists as a badge of achievement and often advancement.

But in introducing a new product, you’re mission is to disrupt this and replace it with branding people as innovators, forward thinkers, visionaries.  Sophisticated orgs are often bifurcated between run-time environments and next-gen platforms each with different groups managing them.  Bifurcated teams introduces politics and turf.

The smart start-up customer org must be highly aware of all of these dynamics, navigate the org, and tune the message and the audience.  Find the innovators and the run-rate teams.  Tailor your message on the fly.  Careful planning, slight in flight adjustments and guts to hit that hole-shot and avoid being a stain on a wall.

Local Clouds and The Coming Death of Legacy Stacks in the Cloud

Let me tell you a little secret about the “cloud.” It’s that right now in the enterprise, it’s a local game. 

A few options come to mind when we think of enterprise, like the predominate force of AWS in test and development environments. Then you have providers like, HP-ES, IBM/SL, RackSpace, Teremark, and Google that are all trying to play enterprise production load catch-up.

For the meantime, I think it’s safe to call the enterprise private cloud a local game.

Take KIO Networks in Mexico City, or LGCNS in South Korea, or T-Systems in Germany; the strength that these local service providers have is that they are entrenched into the local economy. They are tied in with the governmental entities either with contracts, investment tax incentives, or in some cases, board relationships.  Governments encourage these types of business, as they are clean, provide local jobs, and are a good high-tech face for the country.

The key characteristics of these service providers are that they have the local connections and the P&L margin expectations for the long-tail economics of a service provider business.

 In the case of KIO Networks, their margins are so tight that they build their data centers in cooler zones in Mexico City or bury them into the side of a mountain; because not running their chillers for several months out of the year is a competitive differentiator. Coming from a world of plump enterprise software/systems deployments, margins like this seemed like a foreign concept to me.

Just like our friends at AWS, service providers don’t write the books, they just sell them and are perfectly happy living with the retail economics. 

But in this never ending quest for margin, service providers need to standardize on control layers to manage each plane, like, computing, networking, storing, provisioning, and managing charge-back across these heterogeneous, at times customer dictated, and other times, commodity resource pools is vital. 

This long-term platform migration, which is primarily driven by the evolution of the service provider, is what’s posing a sea changing threat to the legacy of major profit pools from the likes of: IBM, HP, EMC, NetApp, etc.

In the early stages of a customer’s journey into the private/public cloud, they generally dictate the same legacy platforms they have run on for decades with these environments lifted and shifted into the services provider data center. In other words, let’s move my expensive proprietary boxes off of my data center floor and onto yours. 

This is precisely where the market is now.  But this phenomenon is just a hosting/colo way station on the way to the true public cloud. 

Going forward, the confluence of software driven reliability, fault tolerance, and compliance are being delivered on top of commodity infrastructure selected by the service providers will be a way of life.   

Service provider’s margins will never tolerate the proprietary stacks of today.  

These business models are too far out of synch. AWS’s cloud doesn’t run on proprietary gear, why should yours?