"Reward modelling" is the term used to describe a process that guides a Large Language Model toward human preferences in generative artificial intelligence. The Deep Seek development team and others at Tsinghua University in Beijing, China are preparing to release version 2 of their economical GAI in the near future.
Human preferences? Human preferences are dependent on the combination of particular cultural factors and individual idiosyncrasies, the number of which could easily be infinite. Like every aspect of GAI in whatever form, its development is structured by those doing the developing. No large language model will be able to incorporate something as yet undiscovered.
An authoritarian regime could easily use directed GAI to explain and justify its policies to its population, just as genuine humans have in the past. It's unlikely that if the human preference is found to be greater personal freedom policies will reflect that.
The Deep Seek phenomenon is already having repercussions in the US data center growth picture. If smaller scale or more efficient GAI installations become part of the US data center complex, electrical demand will be a fraction of what is currently projected. More Deep Seek publicity will put the brakes on funding needed for what could be called "conventional" data center development. It will also be necessary for reliable customers to buy in to the concept and make GAI profitable. Nobody knows yet if that will be the case but some are willing to accept the risk rather than being left on the sidelines.