I'm working through an SVM tutorial (from Andrew Ng Stanford course notes). In the brief coverage of Lagrange duality. The primal optimization problem is stated $$ \min_{w} \theta_{\mathcal{P}}(w) = \min_{w} \max_{\alpha, \beta \::\: \alpha_{i} \ge 0} \mathcal{L}(w,\alpha,\beta) $$
The dual optimization problem is stated
$$ \max_{\alpha, \beta \::\: \alpha_{i} \ge 0} \theta_{\mathcal{D}}(\alpha,\beta) = \max_{\alpha, \beta \::\: \alpha_{i} \ge 0} \min_{w} \mathcal{L}(w,\alpha,\beta) $$
Under the appropriate conditions (convex objective, convex inequalities, affine equalities), it's noted that $w^{*}, \alpha^{*}, \beta^{*}$ can be found such that $w^{*}$ is the primal solution and $\alpha^{*}, \beta^{*}$ are the solution to the dual problem and that they satisfy the KKT conditions. One KKT condition in particular is that
$$ \alpha_{i}^{*} \ge 0. $$
Why is this condition notable considering that a constraint was $\alpha_{i} \ge 0$?