What’s the difference between strong AI and weak AI?
Strong AI can successfully imitate human intelligence and is at the core of advanced robotics. Weak AI can only predict specific characteristics that resemble human intelligence. Alexa and Siri are excellent examples of weak AI. What do you think? Any examples that you can bring in?
Model-based reflex agent
The Model-based agent can work in a partially observable environment, and track the situation. Lets discuss more here.
Simple Reflex agent
The Simple reflex agents are the simplest agents. These agents take decisions on the basis of the current precepts and ignore the rest of the precept history.
Goal-based agents
Goal based agent is one which choose its actions in order to achieve goals. It is a problem solving agent and is more flexible than model reflex agent.Goal based agent consider the future actions. Lets discuss more here
Belief-desire-intention agents
Its an AI agent in which decision making depends upon the manipulation of data structures representing the beliefs, desires, and intentions of the agent
Expert System
An expert system is an AI software that uses knowledge stored in a knowledge base to solve problems that would usually require a human expert. Any other thoughts?
Fuzzy Systems
Fuzzy Logic Systems (FLS) produce acceptable but definite output in response to incomplete, ambiguous, distorted. Can somebody give little more clarity on the same. Any thoughts?
Soft Computing
Soft computing, as opposed to traditional computing, deals with approximate models and gives solutions to complex real-life problems. Soft Computing techniques are Fuzzy Logic, Neural Network, Support Vector Machines, Evolutionary Computation and Machine Learning and Probabilistic Reasoning.
vertical AI is the New Black
vertical AI cannot be “built” in a vacuum without deep industry expertise. Further, vertical AI must be built in direct collaboration with its ultimate consumers and not in a hermetic box, no matter how well-funded that box might be. This is responsibility of service providers and developers to build AI frameworks and “fill in the blanks” in active and dynamic collaboration with customers.
facial recognition
The AI enabled facial recognition application once a darling of Silicon Valley as software for authenticating identities, policing and spying, is suddenly under great controversy. What is the need of stopping the use of such technology for protecting civil rights and privacy?