6 words you need to know to better understand AI

DALL-E, ChatGPT, Midjourney… We hear about Artificial Intelligence (AI) everywhere! Around 35% of the companies now use it to grow their business. But even after the emergence of these revolutionary tools, is it still difficult to understand the notion of AI and the many concepts surrounding it?

What is Artificial Intelligence?

Let’s start with the premise: artificial intelligence (AI). The expression was first spoken in the summer of 1956 during a scientific meeting, the Dartmouth Conference, to refer to tasks that are simple for humans, but complex for machines.

Indeed, even though machines were adept at performing a variety of logical tasks since their creation, other tasks such as identifying the type of animal in a photo, recognizing voices, or simply carrying on a conversation were difficult for them. .

As a result, the scientists present at the meeting agreed to find ways to allow the machines “using language, forming abstractions and concepts, and learning and performing tasks intended for humans,

artificial intelligence

machine learning

Machine learning (ML) is one of the key learning principles in AI. It is the process that allows machines to improve through learning: specifically, it allows computers to learn without the need for special programming. Machine learning uses algorithms to sift through data streams.

In 2023, 48% of companies will use machine learning to make product recommendations, target marketing, or even assimilate large amounts of information, among other things. Examples include Netflix or Amazon.

reading or learning

Deep learning, a subcategory of AI, is an integral part of machine learning. To learn from the data or make predictions, it relies on artificial neural networks. Its concept was largely inspired by the human brain. Deep learning makes it possible to assimilate large amounts of data and then classify it.

Deep learning in particular is at the core of common day-to-day services such as facial recognition, voice assistance and even fraud detection systems. It is also important to note that the popular ChatGPT bot is based on Deep Learning.

neural network

A neural network, also known as a neural network, is an algorithm inspired by the behavior of biological neurons. A neural network is simply a network of mathematical equations made up of dozens, if not hundreds, of “layers” of neurons that perform a variety of sorting and classification operations.

The depth of a network is measured by the number of layers it contains. Neural networks are often used in prediction or classification problems to process data in a complex manner. For example, these systems operate object recognition in images or in self-driving cars to detect pedestrians or obstacles on the road.

Large Language Model (LLM)

Large language models, also known as large language models (LLMs), are AI models for generating content from input or “prompt” text. They are part of NLP which is used to study large amounts of text to infer structures and relationships between words or sentences. LLM is widely used in various fields: machine translation, text generation and even speech recognition. The famous ChatGPT is based on GPT-3, a powerful LLM developed by OpenAI.

data mining

Data mining, literally data exploration, is the process of analyzing large amounts of data in order to discover relationships between them and extract useful information. It is closely linked to key concepts of AI such as Big Data or even predictive intelligence. This process gives companies a real advantage compared to their competitors: it allows, in particular, to better understand customer needs, improve marketing strategy, and optimize turnover.

natural language processing

Natural Language Processing or Natural Language Processing (NLP) is an integral part of Artificial Intelligence. He guides understanding and speech generation like a human. Well-known virtual assistance technologies such as Apple’s Siri, Windows’ Cortana or Amazon’s Alexa are all based on NLP.

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