Genentech has several ML groups that do mostly applied work, but some do fairly deep research into the model design itself, rather than just applying off-the-sh

Genentech has several ML groups that do mostly applied work, but some do fairly deep research into the model design itself, rather than just applying off-the-shelf systems. For example, they acquired Prescient Design which builds fairly sophisticated protein models (https://nips.cc/Conferences/2022/ScheduleMultitrack?event=59064 https://nips.cc/Conferences/2022/ScheduleMultitrack?event=59...) and one of the coauthors is the head of Genentech Research (which itself is very similar to Google Research/Brain/DeepMind), and came from the Broad Institute having done ML for decades ('before it was cool'). They have a few other groups as well (https://nips.cc/Conferences/2022/ScheduleMultitrack?event=60268 https://nips.cc/Conferences/2022/ScheduleMultitrack?event=60... and https://neurips.cc/Conferences/2022/ScheduleMultitrack?event=60041 https://neurips.cc/Conferences/2022/ScheduleMultitrack?event... and https://neurips.cc/Conferences/2022/ScheduleMultitrack?event=57996 https://neurips.cc/Conferences/2022/ScheduleMultitrack?event...). I can't say I know anybody there who is doing what I would describe as truly pure research into ML; it's not in the DNA of the company (so to speak) to do that.