This article provides a short introduction to Large Language Models, their uses, and some limitations associated with LLMs
According to Wikipedia, a Large Language Model(LLM) is a computational model capable of language generation or other natural language processing tasks. In simpler words, it is a type of AI that allows computers to understand and generate human language by running through large amounts of data. Examples of popular LLMs are:
- Google's Gemini
- Chat GPT's GPT-3.5
- Meta AI's Llama
How Do They Do It?
A LLM is a neural network(it processes data like that of the human brain). An example of a neural network is the self-driving car. They learn patterns from a solid amount of data. The input given to a LLM is called a prompt and Prompt design is the process of determining what input to feed a LLM to get the desired result.
What Can They Be Used For?
LLMs provide many advantages like:
- Creating documentation
- Multilingual Support
- Translation
- Simple Math
- Conversations
- Code generation
- Decision Making
- Poems
- Inspiration
Note: Not all LLM answers are right.
Limitations
As efficient and interesting LLMS can be, there are some restraints on this piece of technology which include:
- Accuracy
- Cost
- Data Privacy and Information
- Limited Knowledge
- Environmental Impact.
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