Is there are standard probability space $(\Omega, \mathcal{A}, P)$ and a process $X_t : \Omega \to \{ -1, 1 \}$, $t \in [0,1]$ such that $X_t$ is uniformly distributed on $\{ -1, 1 \}$ and all the $X_t$ are independent (or uncorrelated)?
By Kolmogorov one can construct such a process but it is not clear to me whether $\Omega$ can be chosen to be standard.
I can show at least that such a process is not measurable (i.e. $X : \Omega \times [0,1] \to \{ -1, 1 \}$ is not measurable) but one can find a version with measurable sample paths $X(\omega) : [0,1] \to \{ -1, 1 \}$ for almost all $\omega$.
EDIT: The Kolmogorov construction gives $\Omega = \{ -1, 1 \}^{[0,1]}$ with the product $\sigma$-algebra and product measure (since all $X_t$ are independent). But $\Omega$ has cardinality $2^{c} > c$. Thus $\Omega$ is never standard Borel thus not a standard probability space (when a standard probability space is defined to be the completion of a standard Borel space equipped with some Borel probability measure). So we need to show that any other choice for $\Omega$ has cardinality $> c$.