DecisionBrain, a leading provider of advanced decision support software powered by machine learning and optimization, unveiled its new interactive infographic, showcasing a wide range of AI use cases across 16 different industries. This comprehensive resource highlights the breadth of application for five of the most widely used AI approaches within the broad field of decision science.
They are:
- Machine Learning: This is a broad term that encompasses a variety of techniques for teaching machines (computers) to learn from data. It's usually used to make accurate predictions or decisions without being explicitly programmed.
- Natural Language Processing: NLP techniques are used to process and understand human language. Common applications are chatbots and virtual assistants. Since the launch of ChatGPT and its rivals and offshoots, its use for natural language generation is rapidly growing.
- Computer Vision: Computer vision methods are widely used to identify objects, track motion, and monitor quality. While image generation is an emerging use case, it is not yet as widely deployed in the industry as the other use cases.
- Business Rules: Formerly called expert systems, rules-based systems follow explicit sets of instructions that define how a business should operate or decisions are to be made. Business rules are often used for pricing and insurance underwriting applications or to automate tasks and ensure that businesses comply with regulations.
- Mathematical Optimization: This is a field of mathematics that deals with finding the best solution to a problem, given a set of goals and constraints. Mathematical optimization techniques are used in a variety of applications, such as planning, scheduling, routing, resource allocation and much more.
This infographic does a great job in talking about specific technologies for different use cases. It also is a great reminder that optimization should be a significant part of your AI strategy."
Mike Watson, Northwestern University
Mathematical optimization plays a pivotal role in many industries. For example, you might use computer vision and/or machine learning to predict when your assets are likely to break down or require service. Optimization approaches can take those predictions and create smart detailed daily or weekly service plans that allow you to operate efficiently and meet service level or uptime expectations while respecting workforce capacity limitations alongside many other factors, like parts availability. We hope you will feel inspired by the applications listed in our infographic."
Filippo Focacci, CEO of DecisionBrain
DecisionBrain's new interactive infographic serves as a valuable resource for business leaders, innovators, students, and anyone interested in gaining a broader perspective of the current AI landscape.