World Models represent an approach where machine learns from data representing real world scenarios, for example videos or gaming, in an attempt to simulate human interaction with his environment. The aim of such an approach is for the machine to think and act like humans.

However, for AI to get closer to reality, machine should directly respond to real world data not through models which predict responses to prompts, as in the case of LLMs, nor through learning from a simulated environment, as in the case of gaming in World Models. The only case where such a reality concept is applicable is through following simple instructions by human.

To achieve this, instead of building a machine which shows high reasoning capabilities, the main focus should be on simplifying algorithms to enhance machine performance in response to human queries. Do you agree with this approach?

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