Artificial Intelligence, Machine Learning and Data Science as Iterations of Business Automation for Small Businesses

Artificial intelligence and machine learning, the two iterations of automation are based on the data, small or large. The larger the data, the more effective an AI or machine learning tool will be. The opposite holds the opposite iteration. With a larger pool of data, the large businesses and multinational corporations have effectively been building, developing and adopting refined AI and machine learning based decision systems. The contention of this chapter is to explore if the small businesses with small data in hands are well-off to use and adopt AI and machine learning based tools for their day to day business operations.

Does the Human Brain Resort to AI's Deep Learning in Order to Solve Problems

Problem solving is a daily occurrence in business and, also, in human brains. Businesses resort to a variety of modes in order to find an answer to these problems.Human brains adopt, also, a variety of measures to solve their own brand of problems. Artificial Intelligence technologies seem to have been extending a helping hand to business in the search for problem solving mechanisms. Machine learning and deep learning are currently recognized as prime modes for business insight and problem solving. Does the human brain possess competencies and instruments that could compare to the deep learning technologies adopted by AI?

Big Data and Data Analytics in Agricultural Space: Towards Sustainable and Intelligent Agro Sector Development

Agriculture has become important for each and everyone for its importance in the daily lives. Cultivation and farming is most important and valuable in our life as it is needed for all of us. Furthermore it is essential to have better healthy agricultural systems and in this context Agricultural Informatics play a leading role. Here proper mechanism is very important in healthy and modern agricultural systems and development and for this various initiatives and methods are useful and enhancing. There are rapid changes and growth in respect of the support of various technologies which help in modernizing agricultural production and systems like genetic engineering and technologies, computing and information technology, nano-science and technology, Management Science etc. The combination of Information Technology and Agricultural Sciences has led to the developed the Agricultural Informatics. Agricultural Informatics is simply IT applications in Agriculture and allied areas with its various components. Though in recent past more emerging technologies of IT are enhancing the traditional growth of the Agricultural Informatics and among the technologies important are Big Data and Analytics, AI & Robotics, Cloud Computing & Virtualization, Internet of Things etc. And among these, Big Data and Analytics is emerging and changing the entire arena of the Agricultural Informatics with its periphery and functioning. As the data is changing and rapidly growing therefore, Big Data and Analytics is the solution for managing data effectively with large amount and also the complex data. This paper is theoretical and various aspects of Agricultural Informatics are mentioned such as features, applications and specially the impact of Big Data and Analytics. The Paper is also focused on possibilities of Big Data and Analytics in Agricultural Informatics with challenges, issues etc.

Artificial Intelligence in Business

In this chapter we discuss the core concept of Artificial Intelligence. We define the term of Artificial Intelligence and its interconnected terms such as Machine learning, deep learning, Neural Networks. We describe the concept with the perspective of its usage in the area of business. We further analyze various applications and case studies which can be achieved using Artificial Intelligence and its sub fields. In the area of business already numerous Artificial Intelligence applications are being utilized and will be expected to be utilized more in the future where machines will improve the Artificial Intelligence, Natural language processing, Machine learning abilities of humans in various zones.

Applied Artificial Intelligence – Making AI Work for Consumers as a Core Business Component

Artificial Intelligence (AI) is now rapidly being applied in our society. While the breakthrough of AI in terms of its use and its applicability on a societal level has in fact been repeatedly announced since the mid 1950s, is now truer than ever. As recently acknowledged, AI has now, after three waves of developments, finally left the research labs and entered real-world contexts. Accordingly, and as AI is now increasingly and widely applied, we suggest that it is now time to address issues related to “Applied Artificial Intelligence” (AAI). In this paper we propose this term, and we define it as the study, design, development, implementation and use of Artificial Intelligence technologies to address real-world problems. In this article we present how AI has developed over the past few decades, and across three waves of developments, and we illustrated Applied Artificial Intelligence by presenting our e-Biz corp case where a global actor is now using AI as a core component of their online business. We conclude this article with a set of recommendations for moving forward with Applied Artificial Intelligence, and we present the main contributions offered by our work to the growing body of research on how to make use of AI.