Large Language Models (LLMs), Defining the Next Wave of Interactive Artificial Intelligence

The language model of artificial intelligence is created based on natural language processing technology and algorithms. For example, halfway through a sentence, the model will infer the words behind the sentence based on previously recorded examples. In general, it is about summarizing text information or even creating visual diagrams from plain text.

Large Language Models (LLMs) are trained on massive datasets that contain huge amounts of data. Examples of Google's BERT and OpenAI's GPT-2 and GPT-3 are good examples of LLMs. It is understood that there are about 3 billion parameters in GPT-1750, trained on 570 gigabytes of text. The things these models generate can range from simple articles to complex financial models. AI startups including OpenAI, Hugging Face, Cohere, AI21 Labs, and AI12 are driving LLMs by training models with billions of parameters.

A South Korean company called Naver announced that it has built one of the most comprehensive AI-based language models, HyperCLOVA, a Korean model similar to GPT-3. Unlike the above models, Huawei's PanGu-Alpha and Baidu's Ernie 3.0 Titan are trained on massive Chinese datasets of e-books, encyclopedias and social media.

In 2022, we will see large language models become the basis for the next generation of interactive AI tools.