This is Subset Sum and is famously NP-complete so, no, an LP doesn't work. However, the problem is only weakly NP-hard and there is a pseudo-polynomial time algorithm running in time O(M • n) where M is the sum and n is the number of accounts.

The problem is, perhaps, most of all, that it takes the same amount of space.

Ps, it's not a permutations problem, but a subsets problem. While permutations is n! subsets are "only" 2^n.

I don't believe this to be the case.

The differential pressure from one end of a gas pipeline to the other is not 1800 psi - it is more like 20 psi. You don't repeatedly recompress along the pipeline length - you compress once at the start, and decompress once at the end.

The reason to use high pressures is because for a given pipe diameter (and therefore cost), you get far more gas transported at high pressures than you do at low pressures.

Meanwhile: https://cleantechnica.com/2024/05/03/fossil-fuel-companies-b...

Looks like another arms race. :-(

> If we are attributing these results to the the mass homeschooling experiment that was remote learning, what does that say about regular homeschooling that is still practiced?

Probably not much? It seems pretty reasonable to expect that people that self-select to homeschool their children are going to diverge from the general population (I.e., people en masse that had no desire nor means to do it).

The story’s probably much the same for people working from home. People that sought it out and had established routines before the pandemic probably handled it a heck of a lot better than the general population that was forced into it with little to no prep time and a lack of equipment and support.

If we are attributing these results to the the mass homeschooling experiment that was remote learning, what does that say about regular homeschooling that is still practiced?

Surely there's a more credible source you can find for this

From the intro:

> we've seen many companies and organizations hop on the vector search bandwagon, from NoSQL database providers such as MongoDB (via Atlas Vector Search) to traditional relational databases such as Postgres (via pgvector). The general messaging I hear around these vector search plugins is largely the same and goes something like this: developers should stick with us since you can store tables/JSON in addition to vectors, so there is no need to manage multiple pieces of infrastructure!

> This kind of statement always cracks me up, as it's clearly crafted by unsophisticated marketing teams

From the conclusion:

> Once your application starts requiring more complex workloads (such as joins or aggregations), that's when you'll want to contemplate using different data stores.

I don’t know, after reading through the post I’ve come away on the side of the “unsophisticated marketing teams”; if the vector DB doesn’t have transactions, joins, aggregations it sounds like I’d hit its limitations pretty quick and then I’d rather have an all-in-one industrial strength DB like Postgres instead of two systems.