diff --git a/examples/approx_space_time_learning.jl b/examples/approx_space_time_learning.jl
index eeb68f6..5052ad3 100644
--- a/examples/approx_space_time_learning.jl
+++ b/examples/approx_space_time_learning.jl
@@ -41,7 +41,7 @@ end
 # Also works with RectilinearGrids of inputs.
 # Times must be increasing, points in space can be anywhere.
 N = 50;
-T = 1000;
+T = 100;
 points_in_space = [randn(N) for _ in 1:T];
 points_in_time = RegularSpacing(0.0, 0.1, T);
 x = RegularInTime(points_in_time, points_in_space);
diff --git a/examples/exact_space_time_learning.jl b/examples/exact_space_time_learning.jl
index 7971037..58584aa 100644
--- a/examples/exact_space_time_learning.jl
+++ b/examples/exact_space_time_learning.jl
@@ -39,7 +39,7 @@ end
 # Exact inference only works for such grids.
 # Times must be increasing, points in space can be anywhere.
 N = 50;
-T = 1_000;
+T = 100;
 points_in_space = collect(range(-3.0, 3.0; length=N));
 points_in_time = RegularSpacing(0.0, 0.01, T);
 x = RectilinearGrid(points_in_space, points_in_time);
@@ -73,7 +73,7 @@ final_params = unpack(training_results.minimizer)
 f_post = posterior(build_gp(final_params)(x, final_params.var_noise), y);
 
 # Specify some locations at which to make predictions.
-T_pr = 1200;
+T_pr = 120;
 points_in_time_pr = RegularSpacing(0.0, 0.01, T_pr);
 x_pr = RectilinearGrid(points_in_space, points_in_time_pr);