AI language learning models are computer programs that can generate natural language texts based on some input, such as a prompt, a question, or a keyword. Some examples of AI language learning models are ChatGPT, BERT, and GPT-3. These models are trained on large amounts of text data from various sources, such as books, articles, websites, and social media posts. They use deep neural networks to learn the patterns and rules of natural language, and then use them to produce new texts that are coherent, relevant, and sometimes creative.
Text-based Generative AI tools can use artificial intelligence to summarize data and provide answers quickly and efficiently; it has and can be used for creating content for websites or social media, generating reports or articles, and even writing creative works such as stories or poems. These tools can be useful when you are brainstorming topic ideas or trying to come up with keywords to use to search on a specific topic. Remember that these tools are NOT sources of knowledge -- they are fluency-based text-language generators ("large language models"), which means that they literally guess what word comes next. To understand when these tools are most (and least) useful, please scroll to the bottom of the page.
The information, sentences, or questions that you enter into a Gen AI tool (prompts) have a huge influence on the output and the results you receive. After you enter a prompt, the AI model analyzes your input and generates a response based on the patterns it has learned through its training. More descriptive prompts can improve the quality of the outputs.
If you're unhappy with the results from your search, try rewording, explaining further, or thinking about circumstances and audience.