Artificial Intelligence (AI) is the technology that enables a machine to stimulate human behavior. It is one of the trending technologies and machine learning is its main subset. AI system completely deals with structured and unstructured data. Machine Learning (ML) is a subset of Artificial Intelligence and it explores the development of algorithms that learn from the given data. These kinds of algorithms are able to learn from the given data and teach themselves to adapt to new circumstances and perform certain tasks.
The Big Data augmenting the intelligence in machines
In many areas of research and industry, ML and AI are becoming dominant problem-solving techniques. A similar fundamental hypothesis is shared by both ML and AI; and computation is a better way to model intelligent behavior in machines. Computation does not reinforce learning methods and also does not search for probabilistic techniques. Big data is no fad. As the world is growing at an exponential rate, the size of the data collected across the globe is also growing. Data is becoming contextually relevant which is breaking new ground for ML and AI.
The need for AI and ML
Data is the lifeblood of all businesses. AI automates repetitive learning and analyzes more and deeper data using neural networks that have many hidden layers. In summary, the goal of AI is to create technology that allows machines to function in an intelligent manner. The difference between keeping up with the competition and falling further behind is actually been increased at a high scale by data-driven decisions. So, Machine learning can play a great role to unlock the value of customer data and also enact decisions that keep a company ahead of the competition.
The balancing skills between AI and ML
As stated by Terry Simpson, technical evangelist at Nintex, the skill sets between AI and ML vary at an extreme level. On one hand, there is the technical developer who can execute a given task after been taking the desired outcome, and on the other hand, there is the business analyst who needs to point out that what the business actually needs and see the vision to automate it. Even more, organizations are starting to understand the ways that how AI and ML can have a positive strategic impact.
The PolicyTimes suggestions
- Companies that are hiring the employees must check well that they have diverse skills so that they can stay up to date on the various types of offerings, which is good for the company. Even to judge the improvement of products and services, a data analyst must also be kept in the company.
- To create more and more targeted datasets, the data must be analyzed well by the respective organizations so that the current problems related to AI can be solved.