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Before we begin talking about the impact of Artificial Intelligence over the next half decade, here is a quick introduction to AI.

AI does not aim at accomplishing repetitive tasks based on a given set of rules. It aims at learning new ways of acting from either having performed or watched repetitive tasks; so, having the ability to make subjective decisions with the goals of improving the initially established process. AI means moving away from programming and stepping into “Machine Learning”, where an AI is trained to “acknowledge” certain patterns, hence making its own decisions on how to proceed. Nevertheless, once you enable AI to create code which will instruct RPA, then you have reached Cybernetics and created an A2IM (Autonomous Artificial Intelligence Mechatronics), such as some military drones, but we will come back to that ahead in the text.

Some facts about AI :

  • An experiment was initially performed in 2011 where both humans and AI were “asked” to identify what was shown in a blurred image. Human error rated at 5% while AI at 26%. In 2013 the experiment was repeated and AI error dropped to 3%.
  • In 2015 an AI managed to almost beat the top Poker players in the U.S. (and poker is a strategic “thinking” game where not merely the cards “have a role to play”. The main point was that it learned how to “bluff”, … yes, … really!
  • Also in 2015, an AI was able to accurately draw a picture which mirrored what was written in a given text.
  • Still, in 2015, Professor Pieter Abbeel and his team at UC Berkley AI Laboratory were able for the first time to “teach” a robot to “think for itself”. PR2 (the robot’s name) was able to successfully deal with pieces of clothing (something that does present itself twice in the same shape or form).
  • In 2016 some AI challenges have produced unbelievable results:
  • Analyzing a still picture (from a video clip) and producing a short video (5 seconds) showing what would happen in a sequence of what the image shows. The AI could predict things such as someone falling to the ground or someone opening a bottle and drinking it or a dog running into the water at a beach, amongst other with 96% accuracy towards what really happened next.
  • Another experiment “asked” an AI to predict how a human would behave when faced with an unprecedented situation, after having analyzed videos of that same human behaving in other contexts. Again a 92% accuracy rate was achieved. Have you watched “The Minority Report”? Yes, I know …
  • On January 2017, the AlphaGO AI managed to beat the best GO player in the world. OK. What is it so relevant?!

Go is the most difficult game humans have managed to come up with; it has more permutations in terms of possible moves than the sum of all the atoms that have been calculated to exist in the universe!

  • A clear example of exponential AI evolution (although rudimentary and limited to one single purpose) is now starting to populate our daily life in the form of Self-Driving In 2013, Google was struggling along with BMW (and others although in secrecy) to just make it work and today both along with Tesla have worked almost error-free self-driving AI installed on their vehicles at client’s request and other manufacturers are soon to follow.



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