On the other hand it reminds me of 2010ish robotic demo videos from academic researchers and willow garage.
Problem with robotics is usually that it's easy to produce a good-enough looking demo, but it's really hard to make somethin work in the general case. As exemplified by autonomous driving.
I work in robotics and with quaternions (mainly 6DoF SLAM and used to do robot arm kinematics), but I don't get the use case for this. Maybe provide some example use cases?
> most people know how to use their own money to further their own life if given capital and opportunity, thus capitalism is the solution
I didn't know that "giving capital and opportunity" to people is inherent to capitalism. My understanding of capitalism is, that if people have money, they can "use their own money to further their own life", but capitalists avoid giving money to other people unless the return on investment is greater than 1.
Freezing assets is simple. Seizing them is a huge pain. The EU has a hard time agreeing how to do it and who takes the liability for the Russian claims.
Can you elaborate on this? My guess would be, that because of their status as a government backed research institute, they invent a lot, but let others do the commercialisation. So patent fees seem like a natural choice for them, to recover their investments.
It does sound interesting and I signed up for the wait list. But I actually don't like pure chronological order. It feels like I have to look at everything to find the good stuff. Here I probably won't miss out too much if I check the front page once a day.
I have a Pixel 6a with GrapheneOS. Runs great for years, except for one or two apps that require an "official" Android.
Anyway, I now need to get the battery replaced, because apparently they are dangerous and Google pays for the replacement. Unfortunately, the replacement process requires the stock android to be installed. Meaning, I would need to backup the whole phone, reinstall stock android, then restore everything - and hope the whole ordeal works out.
Yes it is a Milchmädchenrechnung. I do not want to argue whether fusing states makes sense or not. This isn't even a moral condemnation of the original poster. All I say is that the equation `efficiency_gain == federal states before / federal states after` is completely made up.
Thinking the number of federal states is equivalent with an efficiency factor is utterly unsubstantiated. There may be a correlation (or not, I don't claim anything here), but `efficiency_gain == federal states before / federal states after` is pure fantasy.
I tried it to review some C++ code. It actually found minor bugs, but the signal to noise ratio is too high (maybe 10% of the found issues were real issues)
Figured I can save you a click and put the main point here, as few people will be interested in the rest:
The Kalman filter is adding the precision (inverse of covariance) of the measurement and the precision of the predicted state, to obtain the precision of the corrected state. To do so, the respective covariance matrices are first inverted, to obtain precision matrices. To have both in the same space, the measurement precision matrix is projected to the state space using matrix H. The resulting sum is converted back to a covariance matrix, by inverting it.
On the other hand it reminds me of 2010ish robotic demo videos from academic researchers and willow garage.
Problem with robotics is usually that it's easy to produce a good-enough looking demo, but it's really hard to make somethin work in the general case. As exemplified by autonomous driving.