Stephen Wise Blog

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Those Incredible AI Flying Machines | Stephen Wise | Integration Professionals

Today start-ups are promoting flying vehicles that do not require a human pilot. These innovative companies are applying their products to improve productivity and profitability. The business case is easier to understand then the technologies involved – an AI enabled flying vehicle could work longer, faster, and more reliably on certain repeatable tasks then a drone with a human pilot.

A drone without AI is a device with sensors collecting data - a human pilot is still needed. A drone with hard-coded responses to given conditions (such as maintaining height given changing terrain) is fun but not equipped for demanding tasks.

AI enabled capabilities allow human-like performance in reasoning, problem-solving, and planning for specific tasks without ongoing human intervention. No one wants to look at thousands of images 24 X 7 to pick up anomalies. The ability to give the drone a general mission and specific tasks to be completed in a safe and reliable way opens the door for commercial applications.

Farmers could continually scout their fields to test for issues related to disease, irrigation, or infestation. For example, follow the crop furrows and identify sectors that require additional spraying. Energy companies could monitor their transmission lines and pipelines for early signs of damage. For example, do a high-speed pass monitoring for signs of encroachment or corrosion and a repeat detailed pass when certain warning signs are found. These are not new practises – but in the future, decisions can be made based on acquiring more complete data faster, and less expensively.

Tesla received a patent[1] for controlling his boat but did not achieve commercial success on that one. New high value enterprise applications for AI enabled flying machines are imminent. What is your company doing in order to participate?

Stephen D Wise
Integration Professionals
Dramatically Improve Traction

[1] Method of And Apparatus For Controlling Mechanism Of Moving Vessels Or Vehicles. Nikola Tesla of New York, N.Y Patent No. 613,809 (1898)


Artificial Intelligence ABC | Stephen Wise

According to Google's CEO, “AI is one of the most important things humanity is working on. It is more profound than, I dunno, electricity or fire”. The head of Tesla said AI was probably humanities “biggest existential threat”.

Artificial Intelligence isn’t a new concept. Check out the beautifully filmed movie, Metropolis, from 1927. There are other older references in literature. There are also many more recent research and practical applications of "Artificial Intelligence" over the last thirty years.

Today, it is a field of computer science dedicated to solving certain problems which otherwise require human intelligence – specifically, pattern recognition, learning, and generalization. The leap forward in the last few years is that we are gaining the ability to collect, store and analyze ever ginormous amounts of data.

Yesterday, we could write a computer program to predict when it is a good time to cross-sell or up-sell a specific product to a consumer. For example, based on some demographic data and purchase history. The explosion of travel/points programs in the 90's are good examples of this. You agreed to provide your purchase history and demographic data in return for points and the sponsor of the program received data useful for targeted marketing. In these programs, all the rules were hard-coded.

Tomorrow, we can start with the original algorithm to predict the cross-sell opportunity. Then merge it with ever ginormous data collected and the ability to analyze for new patterns. Instead of relying on the initial algorithm to predict the sales opportunity, the system will rely on additional characteristics that it detects and validates within the very data to alter the business rules it relies on. 


But how will it impact the industries around us?

According to the first futurist I followed, Roy Amara, "We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run," coined by Roy Amara, past president of The Institute for the Future.

Here are sample industries and applications. Wherever we have complex systems – people can get overwhelmed by the amount of data and selecting the best course of action. AI is being applied in research setting today in many fields to use what we already know in better and faster ways.

Keep in mind Roy Amara.

  1. Medical
    1. Diagnosis, Drug design/mfr, ICU monitoring
  2. Education
    1. Guided learning, Automated testing and marking
  3. Manufacturing
    1. Quality checking, Supply-chain communication, Maintenance detection
  4. Energy
    1. Demand prediction, Supply distribution


I ask that you take a few minutes right now. Take a sheet of paper, write down the industry you are in at the top. Along the side, list of major business processes you have along the left. Then, along the right, write down some notes about cost savings you could reap if you were able to improve your ability to predict the issues during the process or the outcome.

It may be that one day, the implementation of AI to that process will lead to exponential benefits in your business.


P.S. Feel free to share your analysis via email – I’m interested your findings.


Stephen D Wise

Stephen Wise Integration Professionals

Dramatically Improve Traction



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