Tuesday, January 3, 2017

Next IT Shift, back to Distributed

Figure 1.  We're about to swing to Distributed Computing again
There's a lot to be said for the ever changing IT industry and 2017 should be a banner year in new things happening.

As a recap, in 2016 we saw the Digital Shift take hold of IT and give it a really good shake.  Starting 2016 everyone was asking if you had a plan for Cloud Computing.  I now hope that you do and if not......

There's a huge number of predictions for what the focus and industry will be looking at in 2017.  Of these, #Artifical #Intelligence or #AI and its many brethren (#MachineLearning #Robots, etc) are likely to impose a new Transformation Shift in the industry.

The way I think about it is #IoT with some #smarts.  At a most basic level, anything that can have a sensor applied to it is likely to be considered for an IT upgrade in the framework of an #IoT style device.  These upgrades will be sensors that record some type of data, maybe multiple types of data.

The result is a tiny sensor recording something that people find of value and would like to act upon.

This means data.  And when I say data I mean #LotsOfData.  Big Data levels of lots.

Because there will be so much data, it is almost certain that the data will require some culling and curating at the source.  So, there will be a tiny little computer attached to the tiny sensor.

The data from the sensor is going to have to go somewhere and I think this will have an effect on Cloud Computing.  We're about to have another pendulum swing in computing back to distributed processing of a sort.

Just like other swings, it will not eliminate the previous technology area, but it will force it to change.

Ideally, valuable data that needs to be acted on rapidly will need to have most of the computation done very close to the source.  The entire idea behind the #OODA #Loop is needed to take advantage of real time or near real time data.

Something will be needed to jumpstart the #AI training to make it all work.  This may be the resulting use of Cloud Computing, or it may create the need for a "Near Edge" Cloud computing capability.

Once the AI is trained, the tiny computer should be self sufficient enough to handle everything else it needs to do other than store the sensor data, making the "Near Edge" Cloud as much a storage system as anything else.

This means that the next transformation is going to make computing at the #Edge a reality again.

It's also likely to change how we deal with programming languages.  Logic programming will give way to data flow programming.  (Might be time to brush the dust off some old data flow language or build a new one).

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