It’s focused on how to strategize implementation for incorporating one of the above mentioned categories of Artificial Intelligence (AI).

Currently applications of AI are falling into 4 main categories:
  • Chatbots – Virtual Assistants to respond to users inquiries in real-time augmenting the real user behavior/response – uses Natural Language Processing (NLP), Machine Learning (ML) and Predictive Analysis (PA)
  • Computer Vision – mainly implemented to traffic controlling systems and sports especially professional auto racing sports, to identify vehicles at high speed, threats/mechanical fault prior to typical timings nowadays – uses Optical Character Recognition (OCR)
  • Automated content deliver – leveraging AI-driven automation of content delivery to expand coverage, engage users and increase revenue (as per service industry priorities like Journalish, Netflix etc) – uses Machine Learning (ML) and Deep Learning (DL) and Predictive Analysis (PA)
  • Wearable Tech – AI in conjunction with IoT devices to improve over miscellaneous day to day requirements like parking vehicle, training and performance of athletes/people health and fitness – uses Machine Learning (ML), Deep Learning (DL), and Predictive Analysis (PA)
Advanced, automated and super-detailed Analytical Resources to take Businesses Intelligence (BI) to next level. Wondering, what can be achieved by having it? Watch a Hollywood movie Limitless (consider the pill as incorporating ML, DL and PA and main character as a Super Computer CPU which just needs that BIG DATA to manipulate to bring up best results/solution suitable to any field of subject topic).