7 Basic AI Terms You Need to Know in 2024

Artificial intelligence (AI) is one of the most exciting and rapidly evolving fields of technology today.

But with so many new terms and concepts being introduced every day, it can be hard to keep up with the latest developments and trends.

That’s why I’ve compiled this list of 10 advanced AI terms that you need to know in 2024, along with simple definitions and examples for each of them as promised.

7. Generative AI

Creates new content, such as images, text, music, or videos, based on some input or data.

Example:

• Image Creation by DALL.E
• Audio generation by Synthesys

6. Large Language Model

Understands and generate natural language, such as English, by learning from a huge amount of text data.

Example:

• GPT by Open AI
• LaMDA by Google
• LLaMA by Meta

! GPT stands for Generative Pretrained Transformer

5. Reinforcement Learning

AI that can learn from its own actions and feedback, rather than from data or instructions.

Example:

AWS DeepRacer

AWS Racer is an autonomous racing car that has been designed to test out RL in a physical track. It uses cameras to visualize the runway and a reinforcement learning model to control the throttle and direction.

PS: You can build your own ML models and test them and participates in DeepRacer Leagues.

4. Adversarial Machine Learning

Adversarial machine learning is a type of AI that can fool or attack other AI models by generating fake or malicious data or inputs.

Example:

Adversarial Robustness Toolbox (ART) is a Python library that provides tools and techniques for creating, detecting, and defending against adversarial attacks on machine learning models.

Do you know an application that uses Adversarial ML? Comment below and let me know. I could not find one.

3. Narrow AI

AI that can perform specific tasks or solve specific problems, but cannot generalize to other domains or situations.

Example:

Self Driving Cars

2. Multimodal AI

Process and integrate information from different modalities, such as text, images, audio, or video.

Example:

ChatGPT ver. 4.0

ImageBind by Meta

1. Retrieval Augmented Generation:

This is a type of AI that can enhance its generation ability by retrieving relevant information from specific sources like internal company documents and database.

Example:

Microsoft Copilot for Microsoft 365,

Atlassian AI options in Jira to summarize entered text.

I hope you enjoyed this post and learned something new about AI. If you did, please share it with your network and let me know what you think in the comments.

Thank you for reading.