The increase in both computational power and connectivity has had impact all over the place, but has also transformed science. Even the most analog disciplines now have computational modeling branches, are building datasets, and need best practices for presenting and publishing computational artifacts. From Digital Humanities, to Computational Biophysics.

Printed pages struggle to convey the depth of these results, as do (originally) flat data formats like PDF, which are oriented towards pixels, rather than datatypes.

But I have to disagree strongly about sniping LaTeX as (completely) outdated, because of the need to supplement the printed page with a "content browser". Yes, we most certainly need a computational toolkit for presenting scientific results and aiding peer-review. But no, typesetting is not going away. The human taste for aesthetically pleasing documents is here to stay, and beautifully laid out narratives are instrumental for getting your message across to your audience. Delighting the eye allows the reader to focus on content, rather than struggle with an ugly form.

So my take on my work at Authorea (yep, beware inside bias!) is to transfer our typesetting best practices to the web as the baseline, but then focus and innovate on the "depth" of web-first science articles. To improve academic writing, we need to expose and interact with data, do the well-known social collaboration gig, and embed guarantees for transparency and reproducibility. Machine-assisted quality control and authoring are the two large impact sweet-spots to hit in the coming decade on this front. Time will show if we're in the know or not, but LaTeX is certainly a point of departure that has to be supported, and learning it is a healthy thing to do in 2017. We have a lot of important work ahead of us!