However, it is hard to imagine an actual application of the process. If I understand it correctly, the author suggests using a set of micro-models for annotating a dataset which is then used to train another model. The latter model can actually detect Batman in a general environment, ie, can generalize. However, enriching a training dataset by adding adjacent frames depicting Batman from the same movie will likely have limited usefulness when training an actual Batman detection (non-micro!) model. Or do I get the final application wrong?
The key paragraph is the following:
"We are seeing some mutation coming up in some samples that could possibly evade immune responses," said Shahid Jameel, chair of the scientific advisory group of INSACOG and a top Indian virologist. He did not say if the mutations have been seen in the Indian variant or any other strain.
Your point [1] argues that the USSR collapsed due to internal reasons only. I believe that it is an oversimplification.
Cooperation with totalitarian states often prolong their existence. An example that comes to mind is the US subsidizing grain being sold to the USSR and thus preventing starvation, which would have arguably led to a collapse of the communist regime [a].
However, it is also possible to encourage the "feedback loop" that you mention by merely demonstrating the alternatives that are out there. Radio from the other side of the Iron Curtain [b] gave hope to many people in the USSR.
To sum up, thoughtful action from the outside can help bring down totalitarian regimes faster.
This discovery is definitively cool, but not close to the phosphine-on-Venus cool. The present paper is similar to the former finding in the sense that what looked like a natural explanation (a p-wave order parameter) seems to have been ruled out (just like chemical origin of phosphine seems to have been ruled out). Hence, more exotic findings might lurk in this material.
Wiki says that "Hydroxychloroquine is being studied to prevent and treat coronavirus disease 2019 (COVID‑19), but all clinical trials conducted during 2020 found it is ineffective and may cause dangerous side effects."