Understanding AI & AI Tools

by Dhanashree Ambure

Posted on May 24, 2018 at 05:00 PM

Understanding AI Tools

Artificial intelligence (AI) has come into its own within the last decade fueled by unprecedented computing power and massive data analytics capabilities.

Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals.

Intelligent Machines

In computer science AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. In general, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".

This definition seems a bit technical, to generalize it in a broader sense, AI is something by which machines can think intelligently and make our life easier by performing tasks intelligently, for example, Apple's personal assistant: Siri. She's the friendly voice-activated computer that we interact with on a daily basis. She helps us find information, gives us directions, add events to our calendars, helps us send messages and much more. Another example is Netflix. It provides highly accurate predictive technology based on customer's reactions to films. It analyzes billions of records to suggest films that you might like based on your previous reactions and choices of films.

Machine Learning Tools

Now a days, there are many robust AI/machine learning tools available. Some of them are: Apache PredictionIO (open source), Eclipse Deeplearning4j (open source), Torch (open source) and IBM Watson.

As per one of the recent news article by Javier Jimenez(president of Magic Software Enterprises, Americas) published at industryweek.com, the AI market is expected to grow at a compound annual growth rate (CAGR) of 52% till 2025. As per Javier Jimenez, these are the 5 ways by which Artificial Intelligence can boost productivity:

  1. More accurate demand forecasting
  2. Predictive maintenance
  3. Hyper-personalized manufacturing
  4. Optimizing manufacturing processes
  5. Automated material procurement

In coming future, AI is going to impact our life very deeply. It can be automated transport systems, robot as a friend, predicting climate, improving healthcare and disease diagnostics and much more. AI is taking us into an era where human beings will start getting dependent on machines for a variety of tasks specially which requires accuracy and precision.