Abstract: Julia has established itself as the programming language that sits in the intersection between very fast languages, like C and Fortran, and high abstraction programming languages, like Python and Matlab. It has been argued that this solves the 2 language problem where a prototype is programmed in a high abstraction language and later needs to be re-implemented in a fast language. In this talk, we will argue that, while Julia does solve the 2 language problem, it also creates the 1.5 language problem where there is a huge difference between working Julia code and very efficient Julia code. We will showcase a medium-sized problem to highlight this discrepancy. Finally, we want to start a discussion in the community on how to solve this problem by targeting the education of Julia novices towards performance at scale. Contents 00:00 Welcome! 00:10 There are two ways of using Julia 00:34 Existence of these two ways is not a problem. My expectations were a problem. 00:55 Formal self introduction of the speaker and his collaborator 01:55 Bosch traditionally was dominated by MATLAB and Python for machine learning 02:20 When our opportunity to use Julia rose 03:24 Producing naive port from MATLAB to Julia was very slow 04:36 This port was slow and take much longer time that we expected 05:37 Experience Julia programmers probably want to point to me how memory management in our project should work 06:13 How two Julia languages looks in practice 08:18 I'm still not sure what `@unpack` macro does 08:46 If read SciML documentation from start to finish, we would find this 09:54 What I think about 1.5 language problem? 10:38 Is Julia failing at its main promise? 12:12 When Julia will run on washing machines? 12:57 Thank you! 13:10 Q&A: alock check (question hard to hear)? 13:25 Q&A: do you saw shift of emphasis in promotion of Julia? 14:45 Q&A: what algorithms you want run on washing machine? 15:09 Q&A: which hardware is running on washing machines? 16:11 Outro Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/JuliaCommunity/YouTubeVideoTimestamps Interested in improving the auto generated captions? Get involved here: https://github.com/JuliaCommunity/YouTubeVideoSubtitles