Every leap forward in technology can be a leap forward in human benefit, if managed properly. Innovation, technology and digital advancements have brought us to some of the most exciting times in civilisation. We have gone from tellers to ATMs, cheque books to electronic cards, rotary to mobile phones, from paying bills over the counter and balancing cheque books to online payments. Today, at the click of a mouse or the touch of a button, big business is yielding returns we never thought possible.

The evolution of artificial intelligence (AI) and machine learning (ML) in particular has proven most beneficial. We are now capable of processing big data into meaningful information at lightning speeds. For example cassava farmers in Tanzania are able to protect their crops through the use of an app that uses artificial intelligence and machine learning to diagnose diseases.

By waving the phone over blighted cassava leaves the app scans through large datasets of images that depict multiple diseases cassava plants may have; and within seconds identifies precisely what the problem is as well as profer solutions. This incredible processing power is available and is being utilised by individuals and corporations around the world to unleash valuable solutions.

Another practical example that people come across every day is the use of Google Maps. For the past 10 years, our approach to mapmaking in most of the world combined data from users, third parties, operators, and algorithms to build useful maps. However, in places evolving as quickly as Nigeria, a new approach is required. We have trained a machine learning system to recognize address information from StreetView, satellite imagery, and even handwritten addresses on buildings; and then use that information to automatically add buildings onto the map.

In the past year, we’ve added over 10M buildings to our Nigerian map, making it more accurate. So the next time you get directions from Google Maps that is a real life use case of AI and ML. Every leap forward in technology can be a leap forward in benefit, if managed properly. Technology solutions require data and the more advanced solutions that involve the use of AI and ML require access to big data – millions of bits of information.







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