The discussion revolves around finding the cumulative distribution function (CDF) for a random variable defined as the sum of independent and identically distributed (i.i.d.) exponential random variables. The initial approach using the moment generating function (MGF) was abandoned due to undefined means, leading to the use of the characteristic function (CF) instead. The user encountered issues while attempting to evaluate integrals related to the CF, resulting in non-finite numerical outputs that contradict the expected properties of a CDF. There is confusion regarding the application of the Gil-Pelaez theorem for inverting the CF, with participants suggesting possible errors in the derivations and numerical evaluations. The conversation highlights the complexities of deriving distributions from CFs and the potential pitfalls in numerical integration methods.