text: In this paper authors are summarizing their work on building a framework for automated neural network (NN) construction across multiple tasks simultaneously. They present initial results on the performance of their framework called Multitask Neural Model Search (MNMS) controller. The idea behind building such a framework is motivated by the successes of recently proposed reinforcement based approaches for finding the best NN architecture across the space of all possible architectures. Authors cite the Neural Architecture Search (NAS) framework as an example of such a framework that yields better results compared to NN architectures configured by humans. Overall I think that the idea is interesting and the work presented in this paper is very promising. Given the depth of the empirical analysis presented the work still feels that it’s in its early stages. In its current state and format the major issue with this work is the lack of more in-depth performance analysis which would help the reader draw more solid conclusions about the generalization of the approach. Authors use two text classification tasks from the NLP domain to showcase the benefits of their proposed architecture. It would be good if they could expand and analyze how well does their framework generalizes across other non-binary tasks, tasks in other domains and different NNs. This is especially the case for the transfer learning task. In the NAS overview section, readers would benefit more if authors spend more time in outlining the RL detail used in the original NAS framework instead of Figure 1 which looks like a space filler. Across the two NLP tasks authors show that MNMS models trained simultaneously give better performance than hand tuned architectures. In addition, on the transfer learning evaluation approach they showcase the benefit of using the proposed framework in terms of the initially retrieved architecture and the number of iterations required to obtain the best performing one. For better clarity figures 3 and 5 should be made bigger. What is LSS in figure 4?