Summary of A Reality Check Of the Benefits Of Llm in Business, by Ming Cheung
A Reality check of the benefits of LLM in business
by Ming Cheung
First submitted to arxiv on: 9 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Large language models (LLMs) have achieved remarkable performance in language understanding and generation tasks by leveraging vast amounts of online texts. By adapting to new domains through prompt engineering without retraining, they are suitable for various business functions such as strategic planning, project implementation, and data-driven decision-making. However, their limitations in terms of bias, contextual understanding, and sensitivity to prompts raise concerns about their readiness for real-world applications. This paper evaluates the usefulness and readiness of LLMs for business processes through experiments conducted on four accessible LLMs using real-world data. The findings have significant implications for organizations seeking to leverage generative AI and provide valuable insights into future research directions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary LLMs are big language models that can do many things with language, like understand and generate text. They’re good at learning from lots of online texts. This helps them be useful for businesses in things like planning, projects, and making decisions. But, they have some problems too, like being biased or not understanding the context right. That makes it hard to use them in real life. This paper looks at how well LLMs work for business stuff by testing four different ones on real-world data. The results are important for companies that want to use these models and help us know what we should do next. |
Keywords
» Artificial intelligence » Language understanding » Prompt
