Systems are learning and doing things on their own. A machine when trained properly does specific tasks with best possible intended outcomes. Consider a chatbot where a system is trained to answers specific set of questions to humans when trained. A railway reservation enquiry system can deploy a chatbot with all common questions like train source destination stations, time of arrival and departure, delay time, refund status, ticket status and much more. It happens when the data available in system and collected in real time is properly managed and fed to the chatbot to be served through real time one on one conversations in a human like way. It not only performs in the best way but only those queries which goes unanswered by chatbot are passed to a human. One man can manage thousand enquiries with the help f an efficiently trained chatbot. It involves good amount of data, good AI algorithms and decent machine learning. Machine learning being class of learning for machines also has a subset as Deep learning which majorly solves complex problems. Machine learning deploys structures data and generally solves problems like building a chatbot. Deep learning deals with problems involving image processing and object recognition, Natural Language Processing, etc. Deep learning requires Convolutional neural networks or Artificial Neural networks to work with but are more accurate when a lot of data is available.
Learning approaches varies depending upon the problems to be solved. Consider a scenario where we simple need to recognize a speech, we can simply use Machine learning algorithms but if we need to recognize the speech from a specific user from 1000’s of different speech data, we need Deep learning approach. Deep learning is required for complex problem solving but machine learning generally used in automating tasks where a limited decision making is required.
Artificial Visual labs works majorly on solving complex problems and has solved industrial problems with a very high accuracy. Learning as merely a model of executing tasks and making systems intelligent but the foundation which we always look to is problem solving approach or better saying our logical brain. We consider ourselves as problem solvers and always look to add value than doing business.