Some AI tools are designed to generate creative and coherent stories or narratives, often for entertainment or educational purposes.

TTS tools convert written text into spoken language, making it useful for accessibility, voiceovers, and automated phone systems.

Plagiarism detection tools compare a given text against a database of existing content to identify instances of plagiarism or content similarity.

Document classification tools categorize entire documents into predefined classes or labels. They are commonly used in document management and content organization.

Text annotation tools allow users to label and tag specific elements in a text, such as parts of speech, named entities, or sentiment.

These tools group similar texts together based on their content and identify the main topics within a collection of documents. Latent Dirichlet Allocation (LDA) is an example of a topic modeling technique.

Text generation models, like GPT-3, can generate coherent human-like text. They're used in content generation, creative writing, and chatbot responses.

These tools analyze text for grammar errors, spelling mistakes, and style inconsistencies. Grammarly is a popular example.

Question answering tools understand and respond to user queries with specific answers extracted from a corpus of text, such as a knowledge base or documents.

AI chatbots and virtual assistants engage in natural language conversations with users, providing information, answering questions, and assisting with tasks.

Text summarization tools condense long documents or articles into shorter, coherent summaries, which are helpful for quickly understanding the main points of lengthy texts.

These tools convert spoken language into written text, making it useful for transcription services, voice assistants, and accessibility applications.

Language translation tools automatically translate text from one language to another. Prominent examples include Google Translate and DeepL.

NER tools identify and classify entities such as names of people, places, organizations, and dates in text. They are used in information retrieval and data extraction applications.

These tools categorize text into predefined categories or determine the sentiment (positive, negative, neutral) expressed in a piece of text. They are commonly used for social media monitoring, customer reviews analysis, and content filtering.

AI tools can analyze legal documents and contracts, extracting key clauses and highlighting potential issues or risks