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Artificial Intelligence (AI) and Machine Learning (ML) and Neural Networks are all the buzz these days. All over the internet, you see articles about how these technologies are flourishing beyond anyone’s wildest dreams. And anyone who writes about will most likely bring up how we only thought this would exist in the paragraphs of science fiction books and in scenes of science fiction Hollywood thrillers.

Well, I was one who knew we would reach this age sooner or later. I never once doubted I would live to see machines making decisions for people. I mean, they had already started building cars a couple of decades ago.

A survey was done by Narrative Science in 2016 which discovered that 38 percent of companies are already using AI. They further project that it will grow to 62 percent by 2018, which is right around the corner. Another prediction set by Forrester Research claims a 300 percent increase in investment in AI in 2017 compared with 2016.

Well, we are half way through the year. What is crazier is to think that some people are even predicting the AI market will grow from $8 billion this year to almost $47 billion in only two more years.

“Artificial Intelligence” was first coined in 1955 to describe what then was considered not only a totally alien concept but actually a new computer science sub-discipline.

If you really want to know what is hot, and what we should be focusing our energies on, Forrester has recently published a TechRadar report specifically concerning Artificial Intelligence (specifically for application development professionals). The report gave a detailed analysis of 13 technologies companies really should think about adopting in order to support human decision-making.

Here are five sectors you should really pay attention to:

  1. Natural Language Generation: This is where customer service, report generation and summarising business intelligence insights are made into the text from the computer data. Some vendors dealing in Natural Language Generation are: Yseop, SAS, Narrative Science, Lucidworks, Digital Reasoning, Cambridge Semantics, Automated Insights, and Attivio.
  2. Biometrics: Usually used in market research, this technology enables more natural interactions between humans and machines, including but not limited to image and touch recognition, speech, and body language. Some of these vendors deal in this sort of tech: Tahzoo, Synqera, Sensory, FaceFirst, Agnitio, Affectiva, Mindset Consulting SAP, and 3VR.
  3. Deep Learning Platforms: A subset of actual AI, this special type of machine learning consists of artificial neural networks with multiple abstraction layers, much like a human brain. Currently, this technology is used in pattern recognition and classification applications supported by very large data sets. Some good examples of vendors who deal in such technology would be Sentient Technologies, Saffron Technology, MathWorks, Fluid AI, Ersatz Labs, and Deep Instinct.
  4. Text Analytics and NLP: Using support text analytics by facilitating the understanding of sentence structure and meaning, Natural Language Processing (NLP) is used for security applications and fraud detection, in applications for mining unstructured data and a wide range of automated assistant based applications. Vendors that deal with such technology are Synapsify, Stratifyd, Sinequa, Mindbreeze, Linguamatics, Lexalytics, Knime, Indico, Expert System, Coveo, and Basis Technology.

These are only four out of a long list of sectors within the Artificial Intelligence industry that are booming and only going to continue to grow exponentially. And though those within the SAP community pretty much stay on top of such technologies, it is always nice to read some new perspectives and share among ourselves how each of us view the situation. And with that, I will end with one of my favorite quotes:

“The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.” ― Edsger W. Dijkstra

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