Artificial Intelligence (AI) has become a buzzword in industry. With a preponderance of movies like the Terminator series, A Space Odyssey and The Matrix, where AI is presented in a sinister manner, there is a high level of wariness around the subject. However, understanding how AI can benefit businesses should not be in the domain of rocket science.
Bernard Senekal, director at Naxian Systems, says that the company makes use of AI with machine and deep learning as well as referencing back to expert databases when it comes to the diagnostics of device and system data for the purposes of predictive and preventative maintenance.
Yoshua Bengio, a computer scientist at University of Montreal points out: “The truth is that you can have intelligent machines that have no self-conscience, no ego, and have no self-preservation instinct because we build these machines. Evolution gave us an ego and a self-preservation instinct because otherwise we wouldn’t have survived. We were evolved by natural selection, but AIs are built by humans. We can build machines that understand a lot of aspects of the world while not having more ego than a toaster.”
The threat is not in applying AI to the business world, but rather in not applying it. Senekal explains that in simplistic terms AI is the ability of machines to process information in a way similar to the human brain, with the quest for AI driving towards duplication and extension of the abilities of the human mind.
Is there a difference between AI and machine learning? According to Senekal, machine learning is an applied mathematical technique that makes use of algorithms in order to facilitate the reading of large sets of data. The result of the applied algorithms to these datasets provides an output that allows the machine to produce a predictive result.
“It knows this because it builds relationships between various different patterns in the data and can detect and predict when something in the data is outside the arena of ‘typical’. Essentially, machine learning presents itself as a category or type of artificial intelligence because of its ability to learn from data, without being programmed to do so,” says Senekal.
Deep learning is the next evolutionary step in machine learning and AI. Deep learning is applied in far larger datasets than the datasets in which machine learning is applied. Deep learning builds a neural network that simulates the working of the human brain. Like the human mind, deep learning analyses data and assigns a weighting against, for example, the question that it is trying to answer. The weighting applies to many streams or layers of data and at the end of the weighting it provides an answer in the direction of for example ‘YES’ or ‘NO’.
“The mathematics that deep learning used to reach the specific result then ‘grows’ (much like oxygen grows neural paths in the human brain) the artificial neural networks’ ability to provide far quicker results when presented with the same or similar questions or tasks than it has dealt with before,” Senekal points out.
Expert systems are used in combination with AI, deep learning and machine learning. They apply mathematical techniques while referencing back to existing data that can be found in libraries of, for example, human history, medical science or legal databases.
“A good example of an expert system would be the following: I am feeling a little sick and use my mobile phone to submit a sample of my saliva, blood and a reading of my temperature into an AI cloud environment provided by a medical aid provider. This data, along with data sent to the same provider from my smart watch, references back into medical good practice guides that general practitioners typically used to study for diagnosing symptoms that result in a root cause diagnostic and a remedy to deal with the symptoms of the illness,” says Senekal.
“I then receive automatic diagnostics back from the cloud provider. If you add automation to this, my HR department will receive an email that is automatically generated by the cloud provider notifying them of my leave of absence. Simultaneously, while I drive home, my digital assistant is automatically rescheduling meetings for me when I return to work, while a drone is dropping the required medicines at my front door. Now imagine this going to work for you in the business space.”
Naxian Systems offers a comprehensive consultative process that considers all elements of an organisation’s operations and includes the application of an XaaS (everything as a Service) business model which is based on the IoT (Internet of Things) technology and employs patented AI and deep learning principles.
For more information contact Naxian, +27 (0)87 820 0620, bernard@naxian.co.za, www.naxian.co.za
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