diff --git a/fancy_gym/examples/example_replanning_envs.py b/fancy_gym/examples/example_replanning_envs.py
index b06c970..47283a4 100644
--- a/fancy_gym/examples/example_replanning_envs.py
+++ b/fancy_gym/examples/example_replanning_envs.py
@@ -3,14 +3,14 @@ import fancy_gym
 
 
 def example_run_replanning_env(env_name="fancy_ProDMP/BoxPushingDenseReplan-v0", seed=1, iterations=1, render=False):
-    env = gym.make(env_name)
+    env = gym.make(env_name, render_mode='human' if render else None)
     env.reset(seed=seed)
     for i in range(iterations):
         while True:
             ac = env.action_space.sample()
             obs, reward, terminated, truncated, info = env.step(ac)
             if render:
-                env.render(mode="human")
+                env.render()
             if terminated or truncated:
                 env.reset()
                 break
@@ -38,13 +38,13 @@ def example_custom_replanning_envs(seed=0, iteration=100, render=True):
                         'replanning_schedule': lambda pos, vel, obs, action, t: t % 25 == 0,
                         'condition_on_desired': True}
 
-    base_env = gym.make(base_env_id)
+    base_env = gym.make(base_env_id, render_mode='human' if render else None)
     env = fancy_gym.make_bb(env=base_env, wrappers=wrappers, black_box_kwargs=black_box_kwargs,
                             traj_gen_kwargs=trajectory_generator_kwargs, controller_kwargs=controller_kwargs,
                             phase_kwargs=phase_generator_kwargs, basis_kwargs=basis_generator_kwargs,
                             seed=seed)
     if render:
-        env.render(mode="human")
+        env.render()
 
     obs = env.reset()
 
diff --git a/fancy_gym/examples/examples_dmc.py b/fancy_gym/examples/examples_dmc.py
index 2703e01..f02b7d9 100644
--- a/fancy_gym/examples/examples_dmc.py
+++ b/fancy_gym/examples/examples_dmc.py
@@ -17,7 +17,7 @@ def example_dmc(env_id="dm_control/fish-swim", seed=1, iterations=1000, render=T
     Returns:
 
     """
-    env = gym.make(env_id)
+    env = gym.make(env_id, render_mode='human' if render else None)
     rewards = 0
     obs = env.reset(seed=seed)
     print("observation shape:", env.observation_space.shape)
@@ -26,7 +26,7 @@ def example_dmc(env_id="dm_control/fish-swim", seed=1, iterations=1000, render=T
     for i in range(iterations):
         ac = env.action_space.sample()
         if render:
-            env.render(mode="human")
+            env.render()
         obs, reward, terminated, truncated, info = env.step(ac)
         rewards += reward
 
@@ -84,7 +84,7 @@ def example_custom_dmc_and_mp(seed=1, iterations=1, render=True):
     # basis_generator_kwargs = {'basis_generator_type': 'rbf',
     #                           'num_basis': 5
     #                           }
-    base_env = gym.make(base_env_id)
+    base_env = gym.make(base_env_id, render_mode='human' if render else None)
     env = fancy_gym.make_bb(env=base_env, wrappers=wrappers, black_box_kwargs={},
                             traj_gen_kwargs=trajectory_generator_kwargs, controller_kwargs=controller_kwargs,
                             phase_kwargs=phase_generator_kwargs, basis_kwargs=basis_generator_kwargs,
@@ -96,7 +96,7 @@ def example_custom_dmc_and_mp(seed=1, iterations=1, render=True):
     # It is also possible to change them mode multiple times when
     # e.g. only every nth trajectory should be displayed.
     if render:
-        env.render(mode="human")
+        env.render()
 
     rewards = 0
     obs = env.reset()
@@ -115,7 +115,7 @@ def example_custom_dmc_and_mp(seed=1, iterations=1, render=True):
     env.close()
     del env
 
-def main(render = True):
+def main(render = False):
     # # Standard DMC Suite tasks
     example_dmc("dm_control/fish-swim", seed=10, iterations=1000, render=render)
     #
diff --git a/fancy_gym/examples/examples_general.py b/fancy_gym/examples/examples_general.py
index 9def5b6..aff6b5c 100644
--- a/fancy_gym/examples/examples_general.py
+++ b/fancy_gym/examples/examples_general.py
@@ -21,7 +21,7 @@ def example_general(env_id="Pendulum-v1", seed=1, iterations=1000, render=True):
 
     """
 
-    env = gym.make(env_id)
+    env = gym.make(env_id, render_mode='human' if render else None)
     rewards = 0
     obs = env.reset(seed=seed)
     print("Observation shape: ", env.observation_space.shape)
@@ -85,7 +85,7 @@ def example_async(env_id="fancy/HoleReacher-v0", n_cpu=4, seed=int('533D', 16),
     # do not return values above threshold
     return *map(lambda v: np.stack(v)[:n_samples], buffer.values()),
 
-def main(render = True):
+def main(render = False):
     # Basic gym task
     example_general("Pendulum-v1", seed=10, iterations=200, render=render)
 
diff --git a/fancy_gym/examples/examples_metaworld.py b/fancy_gym/examples/examples_metaworld.py
index bd87c2b..f8b59cd 100644
--- a/fancy_gym/examples/examples_metaworld.py
+++ b/fancy_gym/examples/examples_metaworld.py
@@ -2,7 +2,7 @@ import gymnasium as gym
 import fancy_gym
 
 
-def example_meta(env_id="fish-swim", seed=1, iterations=1000, render=True):
+def example_meta(env_id="metaworld/button-press-v2", seed=1, iterations=1000, render=True):
     """
     Example for running a MetaWorld based env in the step based setting.
     The env_id has to be specified as `task_name-v2`. V1 versions are not supported and we always
@@ -18,7 +18,7 @@ def example_meta(env_id="fish-swim", seed=1, iterations=1000, render=True):
     Returns:
 
     """
-    env = gym.make(env_id)
+    env = gym.make(env_id, render_mode='human' if render else None)
     rewards = 0
     obs = env.reset(seed=seed)
     print("observation shape:", env.observation_space.shape)
@@ -27,9 +27,7 @@ def example_meta(env_id="fish-swim", seed=1, iterations=1000, render=True):
     for i in range(iterations):
         ac = env.action_space.sample()
         if render:
-            # THIS NEEDS TO BE SET TO FALSE FOR NOW, BECAUSE THE INTERFACE FOR RENDERING IS DIFFERENT TO BASIC GYM
-            # TODO: Remove this, when Metaworld fixes its interface.
-            env.render(False)
+            env.render()
         obs, reward, terminated, truncated, info = env.step(ac)
         rewards += reward
         if terminated or truncated:
@@ -81,7 +79,7 @@ def example_custom_meta_and_mp(seed=1, iterations=1, render=True):
     basis_generator_kwargs = {'basis_generator_type': 'rbf',
                               'num_basis': 5
                               }
-    base_env = gym.make(base_env_id)
+    base_env = gym.make(base_env_id, render_mode='human' if render else None)
     env = fancy_gym.make_bb(env=base_env, wrappers=wrappers, black_box_kwargs={},
                             traj_gen_kwargs=trajectory_generator_kwargs, controller_kwargs=controller_kwargs,
                             phase_kwargs=phase_generator_kwargs, basis_kwargs=basis_generator_kwargs,
@@ -93,7 +91,7 @@ def example_custom_meta_and_mp(seed=1, iterations=1, render=True):
     # It is also possible to change them mode multiple times when
     # e.g. only every nth trajectory should be displayed.
     if render:
-        env.render(mode="human")
+        env.render()
 
     rewards = 0
     obs = env.reset(seed=seed)
diff --git a/fancy_gym/examples/examples_open_ai.py b/fancy_gym/examples/examples_open_ai.py
index f1688ef..5dbd10e 100644
--- a/fancy_gym/examples/examples_open_ai.py
+++ b/fancy_gym/examples/examples_open_ai.py
@@ -13,15 +13,13 @@ def example_mp(env_name, seed=1, render=True):
     Returns:
 
     """
-    env = gym.make(env_name)
+    env = gym.make(env_name, render_mode='human' if render else None)
 
     returns = 0
     obs = env.reset(seed=seed)
     # number of samples/full trajectories (multiple environment steps)
     for i in range(10):
         if render and i % 2 == 0:
-            env.render(mode="human")
-        else:
             env.render()
         ac = env.action_space.sample()
         obs, reward, terminated, truncated, info = env.step(ac)