These Are 7 AI Terms You Need to Know

Artificial Intelligence (AI) is one of the most revolutionary technological innovations in the digital era. This technology allows machines to imitate human abilities to think, learn, and solve problems. Its use is also very broad, ranging from the automotive sector, health services, to daily interactions.

The presence of AI technology not only increases efficiency, but also changes the way we work and interact with the world around us, making automation and intelligent data analysis an important part of modern life.

Commonly Used AI Terms

1. Artificial intelligence (AI)

Artificial intelligence (AI) is a field of computer science that develops systems or machines that can perform tasks that usually require human intelligence, such as reasoning, decision making, and learning.

AI encompasses a variety of techniques, including machine learning, natural language processing, and robotics. Through this technology, machines can interact with humans, solve complex problems, and even understand emotions.

2. Machine Learning (ML)

Machine Learning (ML) is a branch of artificial intelligence (AI) that focuses on developing algorithms that allow computers to learn from data. This technology helps systems recognize patterns and make predictions or decisions without having to be explicitly programmed.

This process involves training a model using historical data, then applying it to analyze new data. ML is used in a variety of applications, such as image recognition, predictive analysis, and anomaly detection.

3. Generative AI

Generative AI is a type of AI that can generate new content, such as text, images, videos, or music, based on data that has been learned. This algorithm uses models such as artificial neural networks or GANs (Generative Adversarial Networks) to create creations that are close to human work.

For example, Generative AI can create realistic images from text descriptions or write articles based on certain instructions. This technology is widely used in the creative industry, design, and chatbots applications that generate automated responses.

4. Large Language Model (LLM)

A Large Language Model (LLM) is a type of artificial intelligence model that is trained with large text datasets to understand, generate, and process natural language.

Similar to GPT (Generative Pre-trained Transformer), LLMs are trained to recognize patterns in text, allowing them to understand context and provide relevant responses. Through this capability, LLMs can be used for a variety of tasks, from automatic writing, language translation, to answering complex questions.

5. Prompts

Prompts in the context of AI refer to instructions or questions given to LLMs to generate a response or complete a task. Prompts can be text, keywords, or sentences that define the required context.

The quality and clarity of the prompt greatly impact the results produced by AI. This is because clear and well-structured prompts can help the model understand the goal and provide more accurate answers.

6. Copilots

Copilot is a term often used in the context of AI to describe an AI tool or system that acts as an intelligent assistant, helping users complete tasks more quickly and efficiently.

Copilots are often integrated into work environments such as coding, writing, or design to provide suggestions, predictions, or complete tasks automatically based on the context provided by the user.

7. Plugins

Plugins in the AI ​​world are additional components that can be integrated into an AI platform to extend its functionality. By adding plugins, users can enrich AI capabilities with new features, such as connecting to external databases, processing specific types of data, or performing specific tasks in specific applications.

Plugins allow users to customize AI tools to their specific needs. Typically, these elements are used to simplify the process of integrating AI with existing systems, thereby expanding its potential use in

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