Artificial intelligence definition: Artificial intelligence, or artificial intelligence (AI for short), is a collective name for a collection of disciplines in the field of computer science that aim to simulate the human way of thinking and present abilities that have so far characterized only human intelligence. The field began as an experimental field back in the 1950s and since then has been the basis for countless studies and theories, the best known of which is the technological singularity theory that spawned many of the science fiction hits of recent decades.

 

The ultimate test for artificial intelligence software is called the “Turing test”: can a person who speaks in natural language with entities hidden from his eyes be able to distinguish which of them is a human and which is a machine? If he cannot confidently determine who is who, then the machine has successfully passed the test. However, in recent years, the focus of development in artificial intelligence has changed slightly and has moved from the ability to conduct free conversation towards data processing capabilities and conclusions – mainly due to the increasing use of big data databases.

 

The combination of the fields gave rise to, among other things, business intelligence (BI), which uses techniques such as data mining to improve business processes. Another field born out of artificial intelligence is machine learning (Machine Learning) – the computer’s ability to learn and draw conclusions based on a given sample pool, such as learning a spoken language that contains different voices, intonations, and dialects or building personal recommendation engines on shopping, music and video sites.

 

Strong artificial intelligence definition

Strong artificial intelligence is artificial intelligence that is equal to, or even surpasses, the intelligence of a human. From Wikipedia

 

Ethics of artificial intelligence definition

Artificial intelligence ethics deals with computers that can make moral judgments. This is a field of research in artificial intelligence. A person can give the computer the code of ethics directly by writing code or indirectly by reading it, or the computer can deduce this code from a list of existing laws from Wikipedia.

 

Nearby Wikipedia artificial intelligence definition

Computational intelligence, Landau intelligence, Landau intelligence, sometimes intelligence (history book), sometimes intelligence (historiosophy book), strong artificial intelligence, business intelligence 2.0, business intelligence 3.0, operational intelligence.

 

Aged artificial intelligence definition 

First used the term artificial intelligence in 1956 at the Dartmouth conference. At a basic level, it describes a computer miming human functions, such as learning or problem-solving.

In computer science, it is the study of intelligent agents: entities that observe their environment and take action to achieve their goals. Intelligent agents are designed to learn from human instructions and perform specific tasks without outside intervention.

As computer systems have been perfected, artificial intelligence has advanced, developing its capacity to learn to deal with increasingly complex tasks successfully. AI is a very fashionable scientific field in which we have several preconceived ideas, and sometimes, we need to understand what it is in concrete terms fully.

These artificial intelligence definitions will help you separate fact from science fiction. The most important terms are explained here to help you better understand the concept of AI.

 

Definitions related to artificial intelligence

• Abduction (or abductive reasoning)

Artificial intelligence ​​analyzes a claim or situation and finds the simplest and most plausible explanation.

Example: You notice that the road is wet. The most probable hypothesis is… that it rained. This is the logical explanation.

 

• smart agent

An autonomous entity can perceive its environment using sensors and acting on it. Intelligent agents can distinguish faces, as is the case today on most smartphones. It can also simply be a sensor that detects light in a room and reacts appropriately.

 

• Sentiment analysis

Association of different disciplines (automated natural language processing, computational linguistics, and textual analysis) applied simultaneously to identify and extract subjective information from content. Tone analysis aims to identify the intention of the subject.

 It determines the positive or negative tone of mentions of the brand made on social networks, news articles, and blogs. It can even pick up and interpret hard-to-understand expressions, such as sarcasm, with an overall accuracy of 90%.

 

• Predictive analysis (or predictive modeling)

Predictive analytics is on the rise. Mentions are up 20% since January 2022, with largely positive sentiment. In general terms, this artificial intelligence is talking about it. This method relies on analyzing past data to predict future outcomes by combining machine learning, statistics, and data mining. It can help brands anticipate problems or detect underlying trends in time.

In 2022, we launched the Forecasting tool, which allows brands to predict how a conversation will develop in the coming months using analytics from AI and historical data. By using Forecasts, brands can better position themselves as to the next big trend in their industry and which ones will fade over time.

 

“How often have marketers hoped for a crystal ball to predict the future and ensure their success? Well, that’s exactly what predictive analytics are starting to do. Marketing professionals have worked tirelessly to understand past performance to better plan for the future by gathering historical data, reviewing articles, and drawing conclusions manually. Predictive analytics uses the power of AI to automate this process, at scale, with the industry’s most reliable, real-time data. It might sound like a pipe dream, but predictions are already being used in many areas, from insurance to shipping services. VS 2023 is when marketing professionals can join in the fun.

 

• Algorithm

A set of predefined instructions for a sequence of simple or increasingly complex actions to perform. Several actions are possible: calculation, data processing, or automation of repetitive tasks.

Adaptive algorithms go further and can adapt to any change in information.

 

• Automatic learning (or machine learning )

It is the process by which artificial intelligence self-improves through experience – learning – without actually being programmed. Often, artificial intelligence has access to data and exploits it to learn.

In the case of Talkwalker’s custom models, the AI ​​learning process is human-initiated. Once educated, the AI ​​can isolate data sequences and make decisions based on examples provided by humans.

 

• Reinforcement learning

The process by which artificial intelligence improves from experience – learning – without using human programming. More often than not, artificial intelligence will have access to data and use it to learn. The artificial intelligence ​​learning process is human-initiated. Once educated, she can identify data sequences and make decisions from the examples provided by humans.

 

• Deep learning (or deep learning )

Deep learning is the most advanced evolution of artificial intelligence to date. This technology learns by example and uses multiple layers of nonlinear processing units to achieve impressive results.

It requires significant computer processing capacity and a large amount of labeled data to understand the task in question. This allows it to achieve the highest level of data accuracy possible.

 

• Supervised/unsupervised learning

Supervised and unsupervised learning refers to two methods of educating artificial intelligence. The first uses human-labeled datasets that allow artificial intelligence to learn from the labels and generalize its learnings to new cases.

Unsupervised learning does not require labels, and it is up to artificial intelligence ​​to assign a category to the results. While unsupervised learning can perform more complex tasks, it can also create unnecessary or capillary categories of data by going too far in clustering (the process of grouping heterogeneous items into homogeneous subgroups).

 

• Digital assistants (or virtual assistants)

Anyone who owns a smartphone knows them as Siri, Google Assistant, Cortana, or Alexa. Designed to react to user voice requests, they allow smartphone functions to be used hands-free.

Example: Siri, what’s the weather like? OK, Google, set the alarm clock. Alexa, play some music. More complicated or existential questions usually get sarcastic remarks in response.

 

• Big Data (or big data)

A term used to describe the exponential growth of data. Big Data requires computing power that generally exceeds the capabilities of common software and poses specific requirements for the circulation, collection, storage, and analysis of big data.

 

• A chatbot (or conversational agent)

A chatbot is an artificial intelligence program that mimics an interactive human conversation.

By automating business processes, the chatbot has gained ground in several applications, such as basic customer service, instant messaging, and intelligent virtual assistants.

 

What artificial intelligence means?

Artificial intelligence means no longer just science fiction. The future meets the present!

For communications and public relations professionals, technological advances have meant an exponential increase in the volume of data to manage. Big Data forces more time to be spent processing information, to the detriment of actions based on the insights thus generated.

In most industries, the question is no longer whether. Should use AI, but when. Should I use it?

In the information age, competition is fierce and leaves no room for laggards. If you can harness the potential of AI, you’ll get a valuable head start.

But before that, you have to know what artificial intelligence is.