Studies show that Artificial intelligence (AI)
great value to your business, some of the benefits of implementing AI are increased sales, lower
operating costs, improved efficiency, and it can improve the overall user experience both on the
front and back end.
The result of allowing AI into business processes would increase productivity by automating manual process, increase efficiency by predictive analysis and thereby decrease operational costs.
Our experienced team of AI Agile developers can identify key areas where Artificial Intelligence can improve your business, and develop software and implement the solution to help you reach your targets.
Artificial Intelligence has wide range of uses that spread across
multiple industries, including - Sales & Marketing, Security, Financial, Healthcare, Customer
Service & more.
AI strength is its ability to take BIG DATA, crunch them and arrive at new answers that can be investigated to effect change. Large corporations like Google use this to refine your searches, and Netflix for your recommendations as examples.
AI can change how a business operates from its core, implementing actions such as Deep Learning, Machine Learning, Language Processing or Conversational AI and Predictive Analysis or Smart Searching.
Artificial Intelligence is divided into four main categories, below is a breakdown of each
Deep Learning is the new grand daddy of AI and subset of ML, where neural networks with their various “deep” layers allow learning to occur. It builds on the results of Machine Learning.
The ability for the ML to learn from its designed task and to teach itself the task. It improves through experience. The process starts when ML uses data through examples or instructions. It then interprets the results (data) and starts to create data patterns that it uses to make future decisions (instructions) without human involvement.
Natural Language Processing refers to AI method of communicating with
an intelligent system using a natural language like English. This would be written or orally.
This process uses data along with analysis, statistics, and machine learning techniques to create a predictive model for forecasting future events
Predictive Analysis is forecasting of future outcomes using current and historical data.
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