In the first article of our series dedicated to AutoML, we explored what AutoML is all about and how it works; however, the way AutoML lets businesses upscale the AI is another important aspect to discover for AutoML learners, deployers, experts and professionals. In this article, we will highlight what is meant by democratizing AI with AutoML and how SMEs (Subject Matter Experts) can take the utmost advantage of the same.
We live in a world that is saturated with data, yet only a small portion of it is used in a productive way. Access to machine learning software is a simple solution that may effectively close the data gap that exists between SMEs and the data they need. It is time to open up access to the data needed to make informed choices by people, many of whom may not necessarily have the level of technical expertise required. If we can successfully democratize artificial intelligence, it can be more readily accessible to the businesses.
According to Research and Markets study, democratizing AI with AutoML is rising as one of the most important aspects today’s businesses are paying attention to. This is evident from that fact that thee global AutoML market generated $270 million revenue in 2019 and is expected to touch $15 billion by end of 2030.
What exactly does “democratization” mean?
The term “democratization” refers to a process of making something available to each and everyone without difficulty. At the moment, AI is fairly specialized; but, if we can make it available to all the enterprises across all sectors, there is no doubt that the prospects would be unlimited in number.
Imagine being able to make use of the particular expertise and mental capacity of a data engineer, in conjunction with the incorporation of AI and machine learning, to further extend their research while simultaneously saving time in the process. One approach to achieve this goal is to make it possible for data professionals and small- and medium-sized enterprises (SMEs) to include Automated Machine Learning (AutoML) in their line of work.
How can Auto ML be beneficial here?
Traditional machine learning (ML) requires a greater amount of human work, such as the formulation of data, the analysis of algorithms, and other activities, all of which are necessary before the point at which the real ML can be employed. Subject matter experts can make better use of their time and make more effective use of their time by automating these procedures using AutoML technology. The time and effort that data technicians, engineers, and other SMEs would spend on using conventional machine learning and dependent on AI-specialized data scientists may now be utilized in other areas.
Auto ML Platforms for SMEs -The Future of AI
There have been recent developments that bring us one step closer to formally acknowledging the democratization of AI. The development of AutoML-enabled systems that enable SMEs, such as data engineers, to conduct reviews, analyses, and decision-making as if they were the specialized data scientists themselves is a significant step toward achieving this goal.
Data users may utilize AutoML without a need of having any specialist training or education, and they will still be provided with resources and learning material that will offer them a basic foundation and more information about AI and the applications it has.
The fact that we have seen all of these developments in such a short time demonstrates that the democratization of AI has already arrived. AutoML systems make it possible for businesses to get access to all of the data they want on a greater scale
