On Google and Oxford's cases, I don't think it is common to broadcast among your colleagues in different groups your proposed ideas before you actually go into

On Google and Oxford's cases, I don't think it is common to broadcast among your colleagues in different groups your proposed ideas before you actually go into it. So I think it may happen even in the same company/university. For the meta-learning papers, you may have interests to read the related work part of the RL^2 paper https://arxiv.org/pdf/1611.02779.pdf https://arxiv.org/pdf/1611.02779.pdf. Quoted as follows, "Our work draws inspiration from a particular line of work (Younger et al., 2001; Santoro et al., 2016; Vinyals et al., 2016), which formulates meta-learning as an optimization problem, and can thus be optimized end-to-end via gradient descent." "Another line of work (Hochreiter et al., 2001; Younger et al., 2001; Andrychowicz et al., 2016; Li & Malik, 2016) studies meta-learning over the optimization process. There, the meta-learner makes explicit updates to a parametrized model." Inspired by the same works, apply the meta learning idea into RL problems, meet the ICLR deadline together. Still make sense right?