The distinction between the ability to follow in-
structions and the inherent ability to solve a prob-
lem is a subtle but important one. Simple following
of instructions without applying reasoning abilities
produces output that is consistent with the instruc-
tions, but might not make sense on a logical or
commonsense basis. This is reflected in the well-
known phenomenon of hallucination, in which an
LLM produces fluent, but factually incorrect output
(Bang et al., 2023; Shen et al., 2023; Thorp, 2023).
The ability to follow instructions does not imply
having reasoning abilities, and more importantly, it
does not imply the possibility of latent hazardous
abilities that could be dangerous (Hoffmann, 2022).
Attributing these capabilities to a combination
of memory and in-context learning and the more
general ability of these models to generate the most
statistically likely next token, can help explain the
abilities and the behaviour of LLMs. These ca-
AreEmergentAbilitiesinLarge Language Models just In-Context