Rule-based AI Technology and Machine Learning — What’s the Difference?
Rule-based AI technology and machine learning models are widely used to make conclusions from data. Both these approaches have merits and demerits. Several organizations are exploring and implementing tasks that are related to artificial intelligence in order to automate business processes, improve product upgrades and enhance market experiences.
This article provides some critical points that should be taken into account before investing in any of the techniques. It is important to rely on the correct AI technology for the development of any business requirement — be it mobile app development or custom software development. Emerging technologies like AI and machine learning have the potential to contribute a lot to development and productiveness. That is why there has been constant debate and discussions over the usage of these technologies.
What is rule-based Artificial Intelligence?
A system that accomplishes AI technology through a rule-based model is known as a rule-based AI system. It is an established fact that the demand for AI developers is increasing every day. A rule-based AI produces pre-defined outcomes that are based on a set of specific rules that are coded by humans. These systems are simple AI models that use the rule of if-then coding statements.
The two main components of rule-based AI technology models are ‘a set of facts’ and ‘a set of rules’. You can create a basic AI model with the help of these two components.
What is Machine learning?
A system that executes artificial intelligence through machine deep learning is called a learning model. The machine learning system follows its own set of rules that depend on data outputs. It is an alternative method to address some of the challenges of AI technology rule-based systems. Machine Learning systems only take into account the outputs from the experts or data. These systems are based on a probabilistic approach.
Difference between rule-based AI and machine learning
Here are some of the main differences between rule-based AI and machine learning systems:
1. Rule-based custom software development in AI models is deterministic and machine learning systems are probabilistic. ML systems frequently evolve, develop and adapt their production according to the training information streams. Also, they use statistical rules than a deterministic approach.
2. Another major difference between rule-based AI and machine learning is the project scale. Rule-based artificial intelligence development models are not scalable. Whereas, machine learning systems can be easily scaled to suit the development needs.
3. ML systems need more data when compared to rule-based models. Rule-based AI technology models can function with simple basic data and information. On the other hand, ML systems need full demographic data details.
4. Another key difference between rule-based AI and machine learning is that rule-based AI systems are immutable objects. However, machine learning models are mutable objects that let enterprises transform the value or data by using mutable coding languages like java.
When to use machine learning models
· When there is a change of pace
· When pure coding processing is available
· When simple guidelines don’t apply
When to use rule-based AI technology models
· When there is a risk of error
· When you require speedy outputs
· When you are not planning for machine learning
Conclusion
Rule-based AI and machine learning models have their own merits and demerits. It entirely depends on the context of the usage to decide which approach is appropriate for the development of a business. Most business projects begin with a rule or excerpt-based model to fully comprehend and explore the business. Meanwhile, machine learning systems are recommended for the long term since they are more manageable for regular improvement and enhancement through data preparation and algorithm.
As the world of huge datasets increases, it is important to look beyond binary outputs by using a probabilistic rule rather than a deterministic approach of AI technology. A reliable and competent software development company can guide you towards an appropriate methodology for your unique business requirements.