We also appreciate that the reviewers, especially Reviewer 2, had some concerns with aspects of the papers as well. To each of these points, we'd like to make the following comments: We're happy to include the traditional (e.g., Tanh or LSTM) RNN for comparison, and will add this to the We didn't include Embed2Control-style comparisons, We can include a discussion and illustration of this in the revision. The "simple" model always refers to a simple feedforward network (with the same structure as We'll fully describe the video texture setup in the text (e.g., the source videos are actual videos of physical fire from Thanks for pointing out the confusion here, we'll clarify all of these. However, we'll certainly discuss this point more. We'll include all these details for the experiments (lack of space to desribe them all here).

In the first section, some characteristic features of AI research in France are presented, including difficulties with the current means and the current organization of AI research. In the second section, the state-of-the-art in different areas of AI is described. This allows us to conclude that AI research in France may play an important part at the international level, if the necessary means for its development in the middle and the long term are given. It is no easy matter to review all AI research in an entire country. First, AI is not a very well defined area.

In the first section, some characteristic features of AI research in France are presented, including difficulties with the current means and the current organization of AI research. In the second section, the state-of-the-art in different areas of AI is described. Besides some weakness, and in spite of the general difficulties mentioned in the first section, strong points and great potentialities are exhibited. This allows us to conclude that AI research in France may play an important part at the international level, if the necessary means for its development in the middle and long term are given.