Стоит только отвернуться и сказать а тебе!
IBM:
Large Language Models (LLMs) were explicitly trained on large amounts of text data for NLP tasks and contained a significant number of parameters, usually exceeding 100 million. They facilitate the processing and generation of natural language text for diverse tasks. Each model has its strengths and weaknesses and the choice of which one to use depends on the specific NLP task and the characteristics of the data being analyzed
https://www.ibm.com/blog/what-is-generative-ai-what-are-foundation-models-and-why-do-they-matter/Trustworthiness is one of our main areas of focus. If companies can’t have confidence in the predictions and content these models generate, few of the other benefits matter
To reduce the chance of an AI insulting a customer or hallucinating facts, we are curating domain-specific datasets to train our models.
By making it easier for companies to securely process and store data on servers they own or lease, we hope to lower the barriers to AI adoption.
https://research.ibm.com/blog/generative-ai-for-enterprise