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The Banco de España (BDE) published a paper that proposes the use of different Natural Language Processing (NLP) techniques to better understand central banks' stance towards central bank digital currency (CBDC), analyzing a set of central bank discourses from 2016 to 2022. It uses dictionary-based methods, and two large language models (LLMs) (Bert and ChatGPT), concluding that LLMs better reflect the stance identified by human experts. ChatGPT appears to exhibit a higher degree of alignment because it can capture subtler information than BERT. The study suggests that LLMs are an effective tool to improve sentiment measurements for policy-specific texts, though they are not infallible and may be subject to new risks.

"BloombergGPT represents a significant leap forward for the financial and AI communities. Currently, the model is not available publicly and there is no API, much less a chat interface, to access it. It is unclear when or if public access will be available or even the current incarnation of BloombergGPT will still see further revisions. The BloombergGPT team concludes in their paper that "we err on the side of caution and follow the practice of other LLM developers in not releasing our model" and will not make the model available to the public."

As Shannon taught us, effective communication is not just about capacity-it's about encoding information to suit the channel. By leveraging multimodal interaction, predictive AI, and hybrid approaches to interface design, we can create intelligent systems that amplify human capabilities. As such, it's likely that the next era of human-computer interaction will not be about replacing GUIs with conversational interfaces, but harmonising the two into systems that are greater than the sum of their parts.