Should we rest now that Artificial is actually Real?

Recognition technology now sees computers do much more than manage numbers. This powerful self learning ability matches seemingly obscure connections, to join what neophytes only see as random information.

It is well known that in the last 25 years, as capital productivity grew, labor productivity has remained conversely flat. Sadly the changes to fix the imbalance will be tough on those who worked hard to create what-is now, as that too is being changed by new artificial reality.

Giant leaps forward in the deep learning techniques are enhancing efficiency of all services delivery. Health services are about to turn their ears. That is not only because this is addressing the lack of medical expertise in the world, but it is solving everyday life shortening threats.  Making that possible is hooking innovative artificial intelligence advances cheaply to use what we all already have.

Interpretive computer advances are now so fast that many can now fully self document a processes just by learning from data. Yahoo, now Bing, Facebook, Google and many others, do this with great success, use deep learning robots.

Their Target marketing approach to use information this generates lets the robot systems approach people directly based on what they have leaned about them. Computers have long since been used to find relationships that identify people with potential needs, but now these robots now do the selling.

Using devices attached to your Smartphone to monitor your health a short time ago was seen as an amazing innovative idea, It is now a common place reality.

A chemical prescription may soon be replaced by one for an App which sends data it gathers about you to a computer somewhere. Right now the technology is there to predict with great accuracy heath issues, such as detecting arterial flaking that occurs  in the days and hours before a heart attack  .Being able to send you and your doctor an SMS to say you are in imminent risk of having the heart attack say in the next 48 hours. can save your life

Another good example is curing blindness. caused by disease in third world countries. , Simple interpretive applications use phone camera technology linked to diagnosis tools elsewhere on the planet. These tools, costing less than five dollars, using what people carry or get to easily. Being able to leave these low cost tools with local medical clinics and even patients brings the doctor right to the patient.

“This kind of effective use of artificial intelligence to fix what previously were insoluble problems,” the World Economic Forum says, “is leaping ahead to handle deployment of physicians skills in the developing world that would take about 300 years to train enough people.”

This morning I went to my Pharmacy and they now sell machines to test your blood and others that can be used to shock the heart back to life after an attack.

At the practical level imagine the competitive offerings that will flow from these innovative outcomes. Making the connection with these medical advances clearly change morbidity risk and give the Life offices who relied on it a huge competitive advantage. Those who get there first in populous developing markets, using even 5% Artificial Intelligence capability will gain huge impetus to leapfrog into wider life based financial services.

As industry leaders to start thinking about how to exploit the new options the time is right for community leaders top plan social and economic structures to handle this new reality. Thought leaders who get involved now and extend their creative abilities to put in place strategies to harness the competitive advantage that comes with Artificial intelligence. Winners too will be the fast moving venture capitalists who get on the opportunistic boat to fund it. Traditional cognitive thinkers, even at Ph. D level will need to change or become obsolete.

Nothing is new here as we know at the human end it groups teams in swim lanes of similar skill sets. That has always made it hard to get supply chain flows investment estimates in performance growth very difficult to justify when it follows the ebb and flow of an evolutionary beat.

What is now changing is assuming computers are still dumb. The rate of take up and change indicates that in just five years computers will be off this chart in terms of Artificial Intelligence capability.

If you are not in the game you will have most certainly missed the boat. Embedded deep learning in big data systems already shows artificial Intelligence capability makes growing exponential in real time so the traditional human change and growth rate is no longer an enigma

At the grass roots level many traditional IT people, still think that big data creates big problems. Despite lower storage costs and higher processing power many still constrain database systems administration that by all previous measures already seem to be huge. Good luck with your dreams if you are not able to reorient those guys. That is at the heart of growth issues to be fixed for many companies to progress.

But despair not, as traditionalists will always yield in the end to innovative leaders. I recently had dinner, with a long standing business friend and colleague, who cut his teeth changing processes in Indonesia in the days when change was hidebound in what seemed corrupt and conservatively entrenched.

His success got him a now very high paying VP job which he told me he is leaving to explore artificial Intelligence. Pushing the boundaries of the unknown is what he saw was important and he said also sounds like so much more fun.

We already know systems with embedded artificial intelligence can now do so many things more efficiently by learning from the data. Much more so than humans who spend most of their time being paid to do that.

Creating highly accurate maps is now a few days of work to collect and present pictures to a computer which does the rest, adding street signs distances and so on. Previously that was months of work by a large human team.

And we don’t need Captain Kirk to send a team to find out find out previously disparate SME interests can be easily joined using Artificial Intelligence to determine the common value add. And just one person (perhaps Scotty) can beam it up to the enterprise where deep learning tools can interrogate it further.

As they learn how to focus on and exploit opportunity, partnerships will open up for those on board to not only change business bundling but aid the end user with much more effective and competitive products.

The race now on to build bigger and bigger data vessels with deep learning algorithms to handle and lead that growth.

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