LLMs are limited to their generalized pre-training set, thus information and content related to anything current won't be answer or perhaps the model will attempt to hallucinate an answer. I'm sure you've gotten an answer such as this from querying bard or gpt. This
LLMs like ChatGPT, trained on extensive text data, excel in creative writing and summarization. Their deep language understanding and real-world knowledge enable them to handle tasks like reasoning, task planning, and decision-making, vital for autonomous agents. In this article we will highlight the increasing need for specializing LLMs for contextual
Supply chain managers aim for precise future product demand predictions, but 100% accuracy and coverage is an overwhelming challenge. AI/ML technologies are improving demand forecasting for that short term insight, by leveraging recent-data within models such as PR news feeds. Demand Sensing vs. Forecasting Demand sensing predicts near-future demand
