Radko Diev explores the rise of specialised and general-purpose GPTs in corporate environments, highlighting their distinct roles and implications for organisations.
Good point and good post, Dominique. If companies use only external datasets and GPTs then the potential for error is obvious; but if they only use internal data then the weight of historical data can hold back new thinking, as you suggest. How we get the right blend of internal and external agents is an important challenge.
In my opinion, companies are jumping towards Corporate GPTs without thinking at strategic dimensions such as: who should know what?, how much our internal knowledge should be favored vs external knowledge? what is the value and liability of past knowledge for innovation. I wrote a short article about it https://www.wware.ai/p/the-hidden-risks-of-corporate-gpts , would love your feedback.
Good point and good post, Dominique. If companies use only external datasets and GPTs then the potential for error is obvious; but if they only use internal data then the weight of historical data can hold back new thinking, as you suggest. How we get the right blend of internal and external agents is an important challenge.
In my opinion, companies are jumping towards Corporate GPTs without thinking at strategic dimensions such as: who should know what?, how much our internal knowledge should be favored vs external knowledge? what is the value and liability of past knowledge for innovation. I wrote a short article about it https://www.wware.ai/p/the-hidden-risks-of-corporate-gpts , would love your feedback.