The Java SDK is currently a Tier 2 SDK.. As a Tier 2 SDK they have up to 6 months to implement it. I know they are actively working towards support for the specification.
Best to join our community discord [1] and ask the maintainers !
The concept has not always had this name, that is more recent branding. ~25 years ago it was formalized by a proof that optimal generalized learning is a universal sequence prediction problem. An unfortunate property of universal sequence prediction problems is that they are profoundly intractable and we really don't have a good idea of how to reduce these problems to a tractable approximation on real hardware.
Many basic concepts in computer science are in this class: data compression (see: the Hutter Prize), indexing (see: "learned indexing"), cache replacement algorithms (see: Bélády optimality theorem), etc. We narrowly specialize these algorithms such that they look very different to be computationally feasible but at the limit they are the same algorithm problem.
I find it interesting that database engines are essentially a giant bucket of algorithms all in this class.
> The Riksdag voted in favour of the Government’s proposal which includes the abolition of permanent residence permits for people in need of protection and people who have been long-term residents in Sweden, as well as their relatives.
>The proposal is one component of the efforts to adapt Sweden’s regulatory framework for the granting of international protection and asylum procedures to the minimum guarantees set out in EU law. The purpose of the adaptation is to create better conditions for integration and to reduce social exclusion by reducing asylum-related immigration.
Not all route for permanent residence. Only for asylum seekers. Employment or academic based route are still there it seems.
Employment and academic status are not permanent, nor are visum based on those without conditions.
Permanent residence was more akin to citizenship in that they were permanent and mostly unconditional. The discussion in Sweden around them often came into a discussion around what the difference between citizenships and permanent residence, and if that difference was meaningful.
The practical difference between Permanent residence and citizenship was that:
Swedish citizenship allows a person to be elected into parliament, employed by the police or work in the military.
Swedish citizenship are treated by other countries as Swedish citizens according to international relationships.
Swedish citizens that live aboard can vote in Swedish elections
That was it. Without permanent residence people need to become citizens to get the same rights as citizenship, as all other form of visums has conditions and limits.
Citizens are mostly unconditional, so yes, Swedish citizenship are more permanent. There is discussion around revoking membership from people with double memberships, but it is in legal limbo since it may not be consistent with the constitution.
Permanent Residency were not removed if you moved away. It was also not removed if a person did criminal activity. There was a bit weird middle ground where people retained their permanent residency status, but was expelled from the country due to serious crime.
If clinics and hospitals do not bill 1k dollars each visit, 100k+ for a simple surgery, and pharmacy does not sell medicine 10x the price, US gov't do not need that much allocation for healthcare.
They only bill that much because they need the average amount of money collected for a procedure to pencil.
They get that cash price amount from a tiny amount of people, 70% of that price from private insurers, 30-60% from Medicare, less from Medicaid. Even then, they have to basically litigate the bills through private insurance appeals.
If they had one payer which had a single reimbursement rate, they wouldn't have to do these shenanigans.
The Machine-Learning world, especially "Google Brain" research team figured out that NumPy was an awesome piece of software for dealing with large arrays of numbers and matrix multiplication. They built "TensorFlow" on top of it around 2015 which became very popular. Facebook followed suit and released PyTorch in 2016.
IPython/Jupiter notebooks (for Julia, Python and R) from 2015 were another factor, also adopted by the AI/ML community.
The alternative data-science languages at the time were Mathematica, MATLAB, SAS, Fortran, Julia, R, etc, but Python probably won because it was general purpose and open source.
I suspect Python would not have survived the 2/3 split very well if it wasn't for AI/ML adopting Python as its main language.
> when the tooling was so inferior
Since 2012, Conda/Anaconda has been the go-to installer in the SciPy/NumPy world which also solves a lot of problems that uv solves.
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