  We study hypergraph discrepancy in two closely related random models of
hypergraphs on $n$ vertices and $m$ hyperedges. The first model,
$\mathcal{H}_1$, is when every vertex is present in exactly $t$ randomly chosen
hyperedges. The premise of this is closely tied to, and motivated by the
Beck-Fiala conjecture. The second, perhaps more natural model, $\mathcal{H}_2$,
is when the entries of the $m \times n$ incidence matrix is sampled in an
i.i.d. fashion, each with probability $p$. We prove the following:
  1. In $\mathcal{H}_1$, when $\log^{10}n \ll t \ll \sqrt{n}$, and $m = n$, we
show that the discrepancy of the hypergraph is almost surely at most
$O(\sqrt{t})$. This improves upon a result of Ezra and Lovett for this range of
parameters.
  2. In $\mathcal{H}_2$, when $p= \frac{1}{2}$, and $n = \Omega(m \log m)$, we
show that the discrepancy is almost surely at most $1$. This answers an open
problem of Hoberg and Rothvoss.
