This jargon is of choice and excitement almost everyone i.e. either a tech enthusiast or even for nontech people with a little bit of interest in information technology. There has been a substantial boom in augmented reality in the past five years. Mainly because it allows consumers to visualize a product they like in a 3D environment. As a result, you, as a consumer, get to know more about the product you are looking for and can decide whether to buy it or move on to next. In the coming years, with the help of Artificial intelligence, augmented reality will be more affordable, and many small businesses can quickly start using it for their products.

Generative Adversarial Networks (GANs) – Combination of two neural networks which is very effective generative model network, works simply opposite to other. The other neural network models takes usually complex input and output is simple but in GANs its just opposite. GANs are very young family member of Deep Neural Network Architecture. GANs are class of unsupervised machine learning algorithm. As per the definition of word "Adversarial" from open internet "Involving two people or two sides who oppose each other i.e. adversary procedures.

Machine learning is the process of a machine attempting to accomplish a task, independent of human intervention, more efficiently and more effectively with every passing attempt i.e learning phase. At this point, AI- a machine which mimics the human mind, is still a pipe dream. In the middle we have the meat of the pipeline, the model, which is the machine learning algorithm that learns to predict given input data.

Machine Learning is hottest subject of today's time, DataScientist is the sexiest job of today but implementing these buzz words in real life business is most important need. Machine Learning is the hottest subject of today's time, DataScientist is the sexiest job of today but implementing these buzz words in real life business is most important need. The real need for today's time and business is to clarify, demonstrate and extract real values to benefit every one from this golden key word "Machine Learning". As on date sadly most of the machine learning methods are based on supervised learning. Which means we still have long long way to go.

In a cybersecurity context, AI is a software that perceives its environment well enough to identify events and take action against predefined purpose. It can also learn and build the rules on the go as well; actually thats the real AI. Biggest fear of today's time is the concern that hackers are getting much more smarter. These hackers will use artificial intelligence in cyberattacks that are more sophisticated and harder to detect. We do have Artificial Intelligence in our systems and business strategies.

African Business Review: Tell me a little about your role with Econet Wireless Zimbabwe. I have extensive experience in IT networks, telecom services, and the financial technology space, now exploring artificial intelligence to add value to myself and add to my skills, as machine learning is the future of every business and technology of today. I sit in a very key position to oversee the entire changing landscape of the financial IT i.e. fintech services sector. In our previous issue of African Business Review, you discussed the challenge that banking and financial organisations face in trying to keep costs low while ensuring the same high quality of services - is this still the case? Keeping costs low is the prime idea, as this is a low margin business for low value transactions, if the cost at any time starts looking north, customers immediately start running south.