What could these technologies mean for your business? We outline promising use cases here and highlight both the operational benefits, such as improved efficiency and cost optimisation, as well as the challenges, such as data protection.
In the Zühlke blog post ‘ChatGPT: generate revenue, not just text!’, we explained what large language models such as ChatGPT are and how the technology works. We also discussed its potential initial uses and showed that large language models (LLMs) of this kind could offer businesses a broad range of benefits, from improving customer service and automating routine tasks to generating content.
Generative AI can produce significant cost savings and boost your business’ efficiency, but it is not without its challenges. You need to ensure, for example, that the technology is used ethically and that the generated text is checked to ensure it is both accurate and appropriate.
With this as our basis, we will now take a deeper dive and outline various concrete use cases, examining the advantages, challenges and technological issues involved in the use of generative AI models and large language models in the industrial sector.
In broad terms, there are three main areas where large language models (LLMs) such as ChatGPT can be used:
Ask your document: Search large quantities of data in the form of documents and content, and receive a natural language response to even the most complex of questions.
Generate text: Generate content such as text or even programming code.
Dialogue: Deploy as a user interface in internal and external communication.