AI terms you need to know

Listen to this article

In this article, you will learn about glossary of important terms about Artificial Intelligence (AI). You'll learn about almost 100 words that are often misunderstood in this complex field. From concepts such as AGI e AI Automation until Deep Learning e NLPThese definitions are essential to a better understanding of how AI works. With accessible explanations, you'll be better prepared to use AI effectively and consciously. Let's start exploring!

• AI is a field that creates intelligent machines.

• AGI is an AI with human-like intelligence.

• AI Chatbots allow text and speech interactions.

• Bias can distort the way AI perceives information.

• Supervised learning uses labeled data to train models.

AI Glossary: Terms You Should Know

In this article, you'll find a comprehensive glossary of artificial intelligence (AI) terms. AI is a vast and ever-changing field, and understanding its language can be the first step towards making the most of its capabilities. Let's explore the main terms you should know.

What is AI?

Artificial Intelligence is the field that seeks to create machines and software that perform functions normally associated with human intelligence, such as pattern recognition, language comprehension, planning and decision-making.

Common AI terms

Here are some of the most important terms you should know:

Term	Definition
AGI (Artificial General Intelligence)	A type of AI with human-like understanding and skills in any intellectual task. It's still a hypothetical concept.
ANI (Artificial Narrow Intelligence)	AI that excels at a specific task but lacks general reasoning. Most of today's AIs are ANI.
AI model	A trained function that maps inputs to outputs based on patterns learned from data.
AI agent	AI system designed to perceive its environment, make decisions and act towards specific goals.
AI chatbot	A conversational system that uses language models to interact with users via text or speech.
Deep Learning	Subfield of machine learning that uses complex neural networks to process information in an advanced way.
Processors	Hardware units that perform calculations necessary for AI, such as GPUs and TPUs.
Data Training	Information that a model learns during training. The quality and diversity of the data directly influences the model's performance.

Advanced AI terms

Below you'll find terms that are a little more complex, but just as important.

Term	Definition
Fine-tuning	Fitting a pre-trained model using a smaller, task-specific data set.
Multimodal models	Models that process and generate different types of data, such as text, images and audio.
Supervised Learning	Method that trains a model using input-output pairs.
Unsupervised Learning	Finds patterns in unlabeled data.
Embeddings	Numerical representations that capture semantic information about the data.
Inference	Phase in which a trained model receives new inputs to produce outputs.
Hallucination	When a model generates a confident but false statement.
Red Teaming	The practice of testing an AI system for flaws or unsafe behavior.

Examples of AI applications

AI can be applied in various areas, such as:

• ChatbotsUsed in customer service to answer common questions.

• Image recognitionUsed in health and safety to identify patterns in images.

• Recommendations: Streaming platforms use AI to suggest movies and music based on your tastes.

How does AI work?

AI uses algorithms that analyze large amounts of data, learning patterns and making predictions. For example, an AI model can analyze sales data to predict which products will be most in demand next month.

AI tools and platforms

There are various tools and platforms that facilitate the use of AI, such as:

• Zapier: Integrates different applications and automates tasks without the need for programming.

• OpenAI: Provides advanced language models, such as ChatGPT, which can be used in various applications.

Conclusion

In short, you now have a glossary essential terms about Artificial Intelligence (AI) that will facilitate your understanding of this fascinating field. Understand concepts such as AGI, Deep Learning e NLP is fundamental to navigating the world of modern technology. By familiarizing yourself with these terms, you will become better able to use AI and make informed decisions about its use. Remember artificial intelligence is a powerful tool, and the more you know about it, the better you can use it.

Now that you're more equipped with this knowledge, why not delve even deeper? Visit Blox News and continue your journey of learning about technology and innovation!

Frequently Asked Questions

What does A2A mean in AI?

A2A is a protocol that allows AI agents to communicate and collaborate in an open way.

What is Agentic AI?

Agentic AI are AI systems that can define their own goals and take actions in the real world.

What is AGI?

AGI is a hypothetical artificial intelligence that understands and learns like a human.

What is AI?

AI, or Artificial Intelligence, is the field that creates machines that perform functions such as pattern recognition.

What is an AI Agent?

An AI Agent is a system that perceives its environment and makes decisions to achieve goals.

What is AI Automation?

AI Automation combines automation with artificial intelligence to perform intelligent tasks.

What is an AI Chatbot?

AI Chatbot is a system that talks to users using AI, via text or voice.

What is AI Integration?

AI Integration is the inclusion of AI capabilities in existing products or processes.

What is an AI Model?

An AI Model maps inputs to outputs, learning from patterns in data.

What is AI Orchestration?

AI Orchestration manages different tasks, integrating them into an efficient system.

What is Alignment in AI?

Alignment is the effort to make AI follow human values.

What is ANI?

ANI is an AI that is great at a single task, but doesn't think in general.

What is the Attention mechanism?

Attention is a part of neural networks that decides which inputs are most important for the output.