$l(\theta)=\sum_{i=1}^{m} \log p(x, \theta)$

Step 1 ：First, we need to understand the problem. The function \(l(\theta)\) is given as the sum of the logarithms of the function \(p(x, \theta)\) for \(i = 1\) to \(m\). This is a common form in statistics, often seen in maximum likelihood estimation.

Step 2 ：However, without further information about the function \(p(x, \theta)\), we cannot proceed with specific calculations. The function \(p(x, \theta)\) could be any function of \(x\) and \(\theta\), and without knowing its form, we cannot compute its logarithm or the sum from \(i = 1\) to \(m\).

Step 3 ：Therefore, while we understand the form and meaning of the function \(l(\theta)\), we cannot compute it without additional information.