Now, that we are in the middle of – or hopefully closer to the end of – a general hype that was caused by Open AI’s ChatGPT, it is time to reemphasize on what is possible and what is not, what should be done and what not. It is time to look at business use cases that are beyond the hype and that can be tied to actual business outcomes and business value. This, especially, in the light of the probably most expensive demo ever, after Google Bard gave a factually wrong answer in its release demo. A factual error wiped more than $100bn US off Google’s valuation. I say this without any gloating. Still, this incident shows how high the stakes are when it comes to large language models, LLM. It also shows that businesses need to have a good and hard look at what problems they can meaningfully solve with their help. This includes quick wins as well as strategic solutions. From a business perspective, there are at least two dimensions to look at when assessing the usefulness of solutions that...
- CRM (and other) Thoughts from Down Under