Soft computing solves real world problems using similar tools. AI is an older term and soft computing a refinement that puts the focus on solving problems not on being intelligent or human like. AI tends to solve human like problems such as games, perception or conversation !
In my point of view, they have more similarities tan differences. Both relate approaches to process incomplete, uncertain and some times contradictory information
Machine Learning could be considered a part of AI, however I would classify Machine Learning as the study of creation of semantic models and adaptive behavior with AI being the overall science of systems that intelligent-seeming behavior.
Most of what goes as "AI" is rather simplistic, but highly effective, such as heuristics and the like.
Soft Computing doesn't fell like it has many ML and AI components as it is more about analysis of complex systems. I could be wrong though. As with most things in computer science, the deeper you dig, the more you discover that it's all related.
refer below this link getting some ideas related to AI ans SC
Both techniques are relevant.it differ from the various progress depends upon the situation. AI is an older term and soft computing a refinement that puts the focus on solving problems not on being intelligent or human like. Soft computing solves real world problems using similar tools. AI tends to solve human like problems such as games, perception or conversation. Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think.
In my opinion, both techniques are quite relevant while they aim to solve real world problems that have featured (tolerance for imprecision, uncertainty and partial truth to achieve tractability) using similar methodologies and tools.
Soft computing solves real world problems using similar tools. AI is an older term and soft computing a refinement that puts the focus on solving problems not on being intelligent or human like. AI tends to solve human like problems such as games, perception or conversation !
Machine learning and AI can be considered almost same. The basic purpose of AI is to provide intelligence to machines so that they can behave like human beings. One of the aspects of intelligence is learning. So, Machine learning is a topic under artificial intelligence.
AI may not be dealing with imprecision always.Where as soft computing has no special standing unless uncertainty is involved in the process.
AI is one of the technique of soft computing. In addition to AI soft computing includes fuzzy, genetic algorithm or may be combination of two or more techniques together.
AI is a study of computer science that attempt to model and apply the intelligence of human mind, it is also branch of computer system dealing with simulation of the intelligence behavior while soft computing is one the technique use in machine learning.
The Recommendation identifies five complementary values-based principles for the responsible stewardship of trustworthy AI:
- AI should benefit people and the planet by driving inclusive growth, sustainable development and well-being.
- AI systems should be designed in a way that respects the rule of law, human rights, democratic values and diversity, and they should include appropriate safeguards – for example, enabling human intervention where necessary – to ensure a fair and just society.
- There should be transparency and responsible disclosure around AI systems to ensure that people understand AI-based outcomes and can challenge them.
- AI systems must function in a robust, secure and safe way throughout their life cycles and potential risks should be continually assessed and managed. ”( OECD, 2019).
As mentioned by the OECD representatives, we believe that "Organizations and individuals who develop, implement, or operate intellectual intelligence systems should be held accountable for their proper functioning in accordance with the above principles."
soft computing is an emerging approach to computing, which parallels the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision.. It, in general, is a collection of computing tools and techniques, shared by closely related disciplines that include fuzzy logic, artificial neural nets, genetic algorithms, belief calculus, and some aspects of machine learning like inductive logic programming.
“AI” thus can be defined as the simulation of human intelligence on a machine, so as to make the machine efficient to identify and use the right piece of “Knowledge” at a given step of solving a problem.