This is about a robot that moves around in a curved space by merely changing its shape. Very cool.

What a cliffhanger -- what did you end up doing? Not sweeping the streets presumably?

A nice example of overfitting!

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?

Thanks! You have the application correct, but there are many ways by which we use this. An example is if you have trying to build models that require sequentially annotated images(like action recognition). Another is creating many micro-models that each only detect one type of object even though your general model will have to detect multiple objects.

In general, the theory of what you are saying is correct that this method annotates data that is correlated with the original set, but practically it is still quite useful. Having more ground truth to work with gives a lot more practical flexibility with things like sampling, testing your model, randomization, and training more robust versions of your model.

TL;DR mutations happen.

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.

Both @makomk and @enkid seem to be right [0].

[0] https://www.cochrane.org/CD001269/ARI_vaccines-prevent-influ...

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.

[a] https://en.wikipedia.org/wiki/Great_Grain_Robbery [b] https://en.wikipedia.org/wiki/Voice_of_America#Cold_War

Sounds very interesting! Could you direct the interested to your favorite review article or another starting point?

An implementation or variation on this theme is surely the future of in-room audio:

https://en.m.wikipedia.org/wiki/Wave_field_synthesis

The math says, if implemented correctly, WFS is better than sitting in the sweetspot of any speakers. Also, there's no sweet spot with this technology.

Thanks for sharing! Is there a reason why borg is excluded from the comparison?

I will add it.

You will probably be surprised, but I wasn't aware of this one when starting my project! In a way, this is fortunate, because it was an interesting journey to code this :)

You might want to be aware that Yandex is a Russian company before moving all your photos there.

Not everyone who reads this site is a "reds under the bed" paranoid American.

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.