Deep Learning? LLMs? An AI Glossary for Educators

Artificial Intelligence is the future, and it's transforming the education sector at an unprecedented rate. If you have read or talked to anyone about AI, you know that it has its own vocabulary; it can be challenging to keep up with the new terms that are popping up every day. So, today, we have created an AI glossary for educators to help you understand the most popular terms in AI, particularly “deep learning” and “large language models (LLMs).”

What Is Deep Learning?

Deep learning is a type of AI that mimics the workings of the human brain to solve complex problems. Deep learning algorithms use neural networks, which are a set of algorithms (a process or set of rules that a computer follows) that are designed to recognize patterns in data. Deep learning algorithms can learn from large volumes of data, and they can be trained to identify various things, such as objects within an image or speech patterns in audio files.

What Are LLMs?

A large language model (LLM), is a type of AI that is used to understand natural language. LLMs can understand the context and meaning of words, phrases, and even whole sentences. They're used to improve search engines, personal assistants, and chatbots. LLMs are trained on massive amounts of data and can respond to questions in natural language.

How Can Deep Learning and LLMs Be Used in Education?

Deep learning and LLMs are poised to revolutionize education in numerous ways. For example, deep learning algorithms can be used to develop personalized learning platforms that adjust their content and pace to the needs of individual students. LLMs are used to develop chatbots and virtual assistants that can deliver personalized learning experiences to students.

Examples of Deep Learning and LLMs in Education

There are a few great examples of deep learning and LLMs being used in education today. One of the biggest examples is Duolingo, the language learning app that uses AI and LLMs to deliver personalized learning plans to students. Another example is Knewton, an adaptive learning platform that uses deep learning algorithms to adjust the learning experience for each student.

Practical Tips on AI Usage in Education

As AI continues to transform the education sector, it's important to keep some things in mind. First, focus on meaningful purposes and ways AI can enhance your teaching and learning experiences. Second, understand the data you are inputting into the AI model, as this can significantly influence results. For example if you “train” a chatbot with only one student, it will not be able to understand the complexity of your entire student body. Third, recognize the limitations of AI; it’s important to use it as an aid rather than a replacement for teachers. Finally, prioritize ethical considerations when using AI to ensure that it's used responsibly.

In conclusion, deep learning and LLMs are two of the most popular terms in AI today; they are transforming the education sector at an unprecedented rate. As a teacher or school leader, understanding these terms is necessary to understand some of the latest developments in education. Implementing AI in the education sector is a complex process that requires an understanding of the technological capabilities and risks associated with it. We hope that this blog post has helped you gain an appreciation of AI's power and possible challenges, while giving you a brief glossary of many common terms.