AI trends
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
There are four types of artificial intelligence;
- Reactive machines. …
- Limited memory. …
- Theory of mind. …
- Self-awareness
Evolution of artificial intelligence
Researchers have created software that borrows concepts from Darwinian evolution, including “survival of the fittest,” to build AI programs that improve generation after generation without human input
There are three stages of AI:
- Artificial Narrow Intelligence (ANI)
- Artificial General Intelligence (AGI)
- Artificial Super Intelligence (ASI)
Algorithms of AI
AI often revolves around the use of algorithms. An algorithm is a set of unambiguous instructions that a mechanical computer can execute. A complex algorithm is often built on top of other, simpler, algorithms.
Many AI algorithms are capable of learning from data; they can enhance themselves by learning new heuristics or can themselves write other algorithms. Some of the “learners” described below, could theoretically, learn to approximate any function , including which combination of mathematical functions would best describe the world
- a) Naive Bayes.
- b) Decision Tree. …
- c) Random Forest. …
- d) Support Vector Machines. …
- e) K Nearest Neighbours. …
- a) Linear regression. …
- b) Lasso Regression. …
- c) Logistic Regression.
Challenges to humans
The cognitive capabilities of current architectures are very limited, using only a simplified version of what intelligence is really capable of. For instance, the human mind has come up with ways to reason beyond measure and logical explanations to different occurrences in life. What would have been otherwise straightforward, an equivalently difficult problem may be challenging to solve computationally as opposed to using the human mind. This gives rise to two classes of models: structuralist and functionalist. The structural models aim to loosely mimic the basic intelligence operations of the mind such as reasoning and logic. The functional model refers to the correlating data to its computed counterpart
Applications of AI
AI is relevant to any intellectual task. Modern artificial intelligence techniques are pervasive and are too numerous to list here. Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the Ai effect . High-profile examples of AI include autonomous vehicles (such as drones and self-driving cars), medical diagnosis, creating art (such as poetry), proving mathematical theorems, playing games (such as Chess or Go), search engines (such as google search), online assistants (such as Siri), image recognition in photographs, spam filtering, predicting flight delays, prediction of judicial decisions, targeting online advertisements, and energy storage.
conclusion: Is AI good or bad?
There is no implicit good or bad to AI it will simply respond with results that are derived completely by its learning. … Even in cases where AI has no safety impact it may still create an ethical and moral dilemma by perpetuating unsustainable behaviours and points of view