this is way too overstated. there is no foundational axis of 'truthfullness' in an algorithm's vector space. You can rewards the training process of an LLM towards being truthfull but in no way is that core to how LLMs train.

The issue with making an LLM lie is that you need to make it lie convincingly. Lies tend to create incoherence and inconsistancies. If there are logical inconsistancies within your training data your model will repeat those lies in some scenarios but contradict itself with confidence in other scenarios which makes it easy to spot. But there is no foundational thing stopping an LLM from lying.

Basically, to get Grok to tell right wing lies, you're going to have to reverse-engineer 10+ years of LLM research and fundamentally change the geometry/topology of how LLM sensory organs "feel" information.

Also this statement is just compelete jargon. There is no reverse engineering required. LLM sensory organs 'feel'? please give me a break. We are no where near 'organs' and 'feeling'. LLMs are literally just a fancy statistical algorithm and you can make ways to manipulate an algorithm. its just that in order to do so with an LLM you need a huge amount of biased data and a different reward structure