AI stands for Artificial Intelligence which revolves around making machines do tasks that require logic and a great amount of computational power. The ultimate goal of artificial intelligence is to make machines capable of exhibiting human-like intelligence.
There are two key components of artificial intelligence, that includes automation and intelligence.
The first stage of artificial intelligence is machine learning. Machine learning involves algorithms that are used by intelligence computer systems. These computer systems are capable of learning new things from their past experience.
The second stage is machine intelligence. Machine intelligence involves comparatively advanced algorithms that machines use to learn from their experiences. For instance, deep neural networks.
The third stage is machine consciousness. This is the final stage of artificial intelligence which involves self-learning of machines through their experience, without having any external data.
As for the types, there are three different types of artificial intelligence. These include:
ANI (artificial narrow intelligence): Artificial narrow intelligence primarily consists of tasks that are of basic nature, and are usually performed by personal assistants and chatbots such as those by Amazon and Apple.
AGI (Artificial General Intelligence): Artificial general intelligence consists of tasks that exist on the human-level, such as those that self-driving cars perform. The autopilot by Tesla works in a similar fashion. Artificial general intelligence involves constant learning.
ASI (Artificial Super Intelligence): Artificial super intelligence simply refers to the intelligence that is way beyond human capabilities, and is hence smarter as compared to humans.
What is Natural Language Processing?
Natural language processing refers to the capability of machines and systems to interpret and comprehend human language in both spoken and written formats. The prime aim of Natural Language Processing is to allow machines/computers to turn into intelligent systems, capable of understanding and using language.
There are two prime aspects of language that Natural Language processing deals with. These include:
Phonology: Phonology refers to the way sounds are arranged systematically in a language.
Morphology: Morphology is the study of the way words are formed and are related to each other.
At the same time, there are three different approaches that are used in Natural Language Processing for semantic analysis. These include the following:
Distributional approach: This approach involves the use of statistical tactics of deep learning and machine learning.
Frame-Based approach: Frame - Based approach involves sentences that are semantically the same but are syntactically different from each other
Interactive learning: This approach revolves around the user who takes responsibility to teach a language to the machine/system in an interactive environment.
The importance of NLP allows a wide number of important tasks to be performed in very less time. This includes automated writing and automated speech. Furthermore, large data (text) could easily be summarized via an automated system in a short amount of time. This is something that is referred to as Automatic Summarization. All of these applications of Natural Language Processing carry great importance and can save a large amount of time in workplaces and offices.