The prolific connection of everyday things with the internet to create and store data is driving large tech companies and scientists to create better artificial intelligence (AI). The exponential amount of data stored requires an error-free processing with little downtime. Hence, different algorithms are created to process the accumulated data and recover a meaningful pattern to help businesses and organizations to grow. Neural networking and machine learning are parts of the AI umbrella that uses human-level intelligence to process data through algorithms and learn from the basis of the work processing.
Internet of Things (IoT) is one of the major reasons for the importance of AI integration. IoT devices from nanorobots for surgical purposes to satellites to be sent to distant galaxies are being developed to connect humans with the vast realms of possibilities. With that in mind, we have to remember that it is not possible for a single or even a group of human being to process all the terabytes of data that is constantly being created manually.
Artificial intelligence on the other hand with the help of supercomputers has the processing ability of humans and can swiftly analyze the data created by IoT devices such as smartphones, social media, smart television, Amazon’s Alexa, wearable devices and other intelligent personal assistants. As over 8 billion ‘things’ are being predicted to be connected to the internet by the end of 2020, the amount of unstructured data is about to increase by many folds. Therefore, neural networking is the best solution for energy conservation, storage space conservation, and creates a safer environment all around us through prior analysis and predictive technology.