The “mind” consists of a model formed by the “brain”: This would be a model of the entire environment, including the self, the body, the physical environment, other agents, and the social environment. Furthermore, the model would be a best guess about the most likely state of this environment. It uses this model to learn, decide, attend, remember, perceive, predict, and produce action. This model develops as the brain matures, rapidly during infancy and more slowly later. It has structural components that remain stable over long time. It has labile elements that change at multiple time scales, adapting to the current environment and goals. The mind’s formation through modeling of the world might be likened to the way scientists build models: through a combination of the experiment (interaction with the world) and theory (thought).

The existence of such a model is probably most evident from the many demonstrations that perception is a constructed model formed from sensory input. A simple example is the way we imagine seeing the entire forward field-of-view when we actually see clearly only a small foveally defined region. Such a construction is presumably formed on the basis of partial cues in regions that have poor acuity, from prior eye movements, and from prior knowledge that tells us what is likely to be present (such as the likelihood that if we are in a room there will be walls and doors in peripheral regions of poor acuity). This model will of course be most useful for the purpose of maintaining a stable environment as the eyes, head, and body move, and for the purpose of guiding future eye movements (and bodily movements) as the need to do so arises.

The term artificial intelligence well these machines are artificially incorporated with human-like intelligence to perform tasks as we do this intelligence is built using complex algorithms and mathematical functions but AI may not be as obvious as in the previous examples in fact AI is used in smartphones cars social media feeds video games banking surveillance and many other aspects of our daily life the real question is what does an AI do at its core here is a robot we built in our lab which is now dropped onto a field in spite of a variation in lighting landscape and dimensions of the field the ai robot must perform as expected this ability to react appropriately to a new situation is called generalized learning the robot is now at a crossroad one that is paved and the other rocky the robot must determine which path to take based on the circumstances this portrays the robot’s reasoning ability after a short stroll the robot now encounters a stream that it cannot swim across using the plank provided as an input the robot is able to cross this stream so our robot uses the given input and finds the solution for a problem this is problem solving these three capabilities make the robot artificially intelligent in short ai provides machines with the capability to adapt reason and provide solutions.

let’s have a look at the two broad categories an AIs classified into weak ai also called narrow ai focuses solely on one task for example alpha go is a maestro of the game go but you can’t expect it to be even remotely good at chess this makes alpha go a weak AI you might say Alexa is definitely not a weak ai since it can perform multiple tasks well that’s not really true when you ask Alexa to play despite it picks up the keywords play and Despacito and runs a program and is trained to Alexa cannot respond to a question it isn’t trained to answer for instance try asking Alexa the status of traffic from work to home Alexa cannot provide you this information as she is not trained to and that brings us to our second category of ai strong ai now this is much like the robots that only exist in fiction as of now Ultron from avengers is an ideal example of a strong ai that’s because it’s self-aware and eventually even develops emotions this makes the ai’s response unpredictable you must be wondering.

we saw what AI is machine learning is a technique to achieve ai and deep learning, in turn, is a subset of machine learning that provides a machine with the capability to learn from data and experience through algorithms deep learning does this learning through ways inspired by the human brain this means through deep learning data and patterns can be better-perceived ray Kurzweil a well-known futurist predicts that by the year 2045 we would have robots as smart as humans this is called the point of singularity well that’s not all in fact Elon musk predicts that the human mind and body will be enhanced by ai implants which would make us partly cyborgs.