LLM (Page 2)

Archival data in research institutions and national laboratories represents a vast repository of historical knowledge, yet much of it remains inaccessible due to factors like limited metadata and inconsistent labeling. Traditional keyword-based search mechanisms are often insufficient for locating relevant documents efficiently, requiring extensive manual review to extract meaningful insights.Continue Reading

Yuewen Group is a global leader in online literature and IP operations. Through its overseas platform WebNovel, it has attracted about 260 million users in over 200 countries and regions, promoting Chinese web literature globally. The company also adapts quality web novels into films, animations for international markets, expanding theContinue Reading

Since Amazon Q Business became generally available in 2024, customers have used this fully managed, generative AI-powered assistant to enhance their productivity and efficiency. The assistant enables users to answer questions, generate summaries, create content, and complete tasks using enterprise data. Today’s workforce faces significant application overload. According to Gartner,Continue Reading

Large language models (LLMs) excel at generating human-like text but face a critical challenge: hallucination—producing responses that sound convincing but are factually incorrect. While these models are trained on vast amounts of generic data, they often lack the organization-specific context and up-to-date information needed for accurate responses in business settings.Continue Reading

Fine-tuning a pre-trained large language model (LLM) allows users to customize the model to perform better on domain-specific tasks or align more closely with human preferences. It is a continuous process to keep the fine-tuned model accurate and effective in changing environments, to adapt to the data distribution shift (conceptContinue Reading

As large language models (LLMs) become increasingly integrated into customer-facing applications, organizations are exploring ways to leverage their natural language processing capabilities. Many businesses are investigating how AI can enhance customer engagement and service delivery, and facing challenges in making sure LLMs driven engagements are on topic and follow theContinue Reading

Evaluating large language models (LLMs) is crucial as LLM-based systems become increasingly powerful and relevant in our society. Rigorous testing allows us to understand an LLM’s capabilities, limitations, and potential biases, and provide actionable feedback to identify and mitigate risk. Furthermore, evaluation processes are important not only for LLMs, butContinue Reading