Popular Generative AI Terms You Should Know

Artificial intelligence is a topic of widespread discussion today, with everyone from professionals to the general public talking about its potential impact on our lives and jobs. With so much conversation, we frequently encounter many terms such as machine learning, NLP, generative AI, prompt, large language models, etc, and one may feel lost when these terms pop up.

If you are one of them, then this article is for you. We have curated a list of technical terms related to generative AI that frequently appear when we learn about generative AI.?

This article will list essential terms to help you understand AI terminology better. Whether you're a business owner or an enthusiast eager to learn about artificial intelligence, this article will improve your understanding.

AI has existed since the 1950s; however, it was not widespread until the launch of ChatGPT, which took the Internet by storm by reaching millions of users in just five days, a feat that took Instagram, Netflix, and Spotify months and years.

Now, several AI-powered tools are available for content marketers, designers, and business owners, taking humans' productivity and creativity to the next level. With the growing generative AI terms, netizens are getting confused.?

Generative AI Terms to Know in 2024?

With the emergence of popular tools such as ChatGPT, Bard, etc. This landscape could be exciting and confusing for beginners, as several terms are interchangeably used. Though the list is comprehensive and contains hundreds of words, we will be jotting down some of the most popular Gen AI terms here that every professional should know.??

1. Artificial intelligence

Artificial intelligence (AI) is a broad field focused on creating machines and programs to perform tasks that typically require human intelligence, although not as often depicted in fiction. An AI-powered machine and program can perform tasks such as learning, reasoning, problem-solving, understanding natural language, and perception. AI was conceptualized in the 1940s and 1950s with the aim of enabling machines to think and operate autonomously.

Over the decades, AI has developed into various subsets,?each focusing on different aspects of intelligent behavior. One subset is generative AI, which includes technologies that can create content autonomously. Generative AI includes models capable of generating text, images, music, and other forms of content by understanding and mimicking patterns found in the data they are trained on.?

2. Machine learning

Machine learning is a subfield of artificial intelligence that uses algorithms, mathematical models, and statistical assumptions to predict or make decisions. In other words, it is an approach that uses statistical techniques to enable machines to learn from data. It incorporates different techniques, such as deep learning, supervised and unsupervised learning, a framework, data processing and analysis tools, development environments, etc.

2. Neural networks

A Neural network consists of interconnected nodes (artificial neurons) that work together to process information and make decisions. It helps ML models to learn from complex, high-dimensional data. They are leveraged in AI/ML development when a ML model has to deal with unstructured and non-linear data

There are different types of artificial neural networks exist today:?

• Feedforward neural networks (FF), one of the oldest forms of neural networks.
• Recurrent neural networks (RNN), used for speech recognition, translation, and to caption images.
• Long/short-term memory (LSTM)
• Convolutional neural networks (CNN)
• Generative adversarial networks (GAN)

3. GPT

GPT stands for generative pre-trained transformer. It is developed by OpenAI, the company behind the popular ChatGPT tool. You may have noticed that ChatGPT contains GPT, so now you might be wondering exactly what a generative pre-trained transformer(GPT) is.?

GPT refers to a series of generative models developed by OpenAI that are pre-trained on vast amounts of text data using unsupervised learning techniques.

Transformers in generative AI refers to a special type of neural network architecture that is particularly used in generating content by several AI models. They are used in different tasks, such as language, audio, and video processing.

Apart from ChatGPT, millions of other generative AI models (or applications) surfacing across the Internet are built upon GPT. This means that GPT operates with some custom modifications behind the scenes. Major chatbots write in similar tones because they, in the end, have the same brain or program (or GPT model). The model can be considered the brain of your program.?

4. NLP

NLP stands for Natural Language Processing. It refers to processing natural languages like those we speak and write. Nowadays, machines are capable of understanding and processing our natural language. You can communicate with them using your everyday language, and they can grasp your intent.

NLP is a subset of artificial intelligence that enables interactions between machines and humans. When a system, machine, or program has NLP ability, you can interact with it using your own language. For example, AI Chatbots can understand sentiments like humans and respond appropriately. Have you ever wondered how they do it? The NLP technology behind them powers them to understand our sentiments.

5. LLM

LLM stands for large language models. In AI, a large language model refers to a computer program that is trained on massive amounts of text data from the Internet, books, articles, and more—thousands or millions of gigabytes' worth of text. Based on its learning, it can understand written language, write essays, answer questions, and even hold conversations.?

Famous examples of large language models (LLMs):

• GPT (Generative Pre-trained Transformer) series by OpenAI
• BERT (Bidirectional Encoder Representations from Transformers) by Google
• T5 (Text-To-Text Transfer Transformer) by Google
• XLNet by Google Brain?
• CTRL (Conditional Transformer Language Model) by Salesforce
• Megatron by Nvidia
• Turing-NLG by Microsoft

Curious to know more generative AI terms? Dive deeper into our latest insights on the blog. Read more: https://www.brilworks.com/blog/essential-terms-in-generative-ai/