In the ongoing fourth industrial revolution, organisations are trying to implement artificial intelligence for getting a competitive edge in the market. Nonetheless, the lack of information and AI experience leads to common mistakes. In this post, we talk about how to avoid the most common pitfalls by means of the 6 critical components of AI.
Machine Learning is a vast field involving a multitude of mathematical means to approach a problem. This allows an endless amount of approaches to tackle a problem. In this post, we explain how machine learning can be seen as a toolbox of algorithms.
Today, it is necessary to implement AI in the organisation to have a competitive edge in the market. But, organisations face difficulty when it comes to tackle the new technology. In this post, we talk about three steps which can be followed to successfully implement AI in your organisation.
Different types of software architectures must be considered when intending to develop an AI application. Functional and non-functional requirements as well as a set of architectural characteristics must be considered. In this post we describe each and every one of the considerations
Most AI experts believe that a use case identification workshop is a critical starting point for companies in their AI journey. After carrying out several of these workshops, I personally second that notion. Nonetheless, the different components of a workshop must be adequate for a valuable outcome.
The impact of Artificial Intelligence is not limited to business but to the entire society. While developing an AI system, organisations and institutions should prevent any wrongful implications on people’s everyday lives. In this post, we talk about three main ethical values for an AI framework which can aid in developing a responsible AI system.
Unquestionably, we are in an age of data. Modern technology generates an increasing amount of data, which can be processed to extract knowledge within it.