You don’t need that assumption. Your assumption can just be “the person and vessel (or a point in the vessel, like its center of mass) don’t diverge significantly over time”.

Then, if you treat velocity as a vector and compute the person’s average velocity vector over time, you’ll have a pretty close estimation to the vessel’s velocity vector.

After all, if those two average vectors (vessel’s and person’s) were to differ much, they would end up in different locations.

The average basically zeroes the vector for each lap the person does, so the remainder must be the vessel’s.

yeah, I think the whole “water” argument really dilutes the case against data centers.

On a serious note, the argument works for areas that already struggle to supply enough water for consumers. Otherwise, we should be focusing more on the power stress to the grid, and the domino effect on supply chain of hardware cost increases that it’s happening across many industries. It started with GPUs, now it’s CPU, storage, networking equipment, and other components.

If these prices are too high for a couple of years, we’ll start seeing generalized price increases as companies need to pass along the costs to consumers.

It’s not, I read the code. It’s not merely asking the LLM for recommendations, it’s using embeddings to compute scores based on similarities.

It’s a lot closer to a more traditional natural language processing than to how my dad would use GPT to discuss philosophy.

Ok, I’m not suggesting replacing humans with AI and I despise companies trying to do this unsustainable practice.

With that out of the way, I’ll restate that LLMs follow some rules more reliably than humans today. It’s also easier to give feedback when you don’t have to worry about coming across as a pedantic prick for pointing out the smaller things.

On your point that LLMs are not improving; well, agents and tooling are definitely improving. 6 months ago I would need to babysit an agent to implement a moderately complex feature that touches a handful of files. Nowadays, not as much. It might get some things wrong, but usually because it lacks context rather than ability. They can write tests, run them, and iterate until it passes, then I can just look at the diff to make sure the tests and solution makes sense. Again, something that would fail to yield decent results just in the last year.

No, it also doesn’t do that. It gets embeddings from an LLM and uses that to rank candidates.

can’t be worse than that screen

It’s true, I was the bowling pin

that’s how it looks when you walk/run in circles in a vessel that’s moving

some people get sick looking at screens?

lol macs have the glossiest screens out there, almost like they make it a mirror on purpose

no one is saying everyone has to ask an LLM for movie recommendations

wow, this dystopic update is reality not disappointing

yet another reason to not use Google

chill, this is extracting text embeddings from a local model, not generating feature-length films

that’s like saying “no jet use is benign” meant for comparing a private jet to a jet-ski

the generative aspect is not even used here

There’s no training, the LLM embeddings are used to compare the plots via a cosine similarity, then a simple weighted score with other data sources is used to rank the candidates. There’s no training, evaluation, or ground-truth, it’s just a simple tool to start using.

that’s pretty cool, this is just the wrong crowd, don’t worry about the downvotes

This is not a recommendation or a preference, it is a mandate,

ODF’s mandate is the document-layer expression of that principle, as you cannot claim digital sovereignty while allowing your documents to be locked in proprietary formats controlled by a single vendor.

incredibly based

tmpfs is a memory filesystem, they all do

https://man7.org/linux/man-pages/man5/tmpfs.5.html

one-liner to get the total used size

/usr/bin/df --type=tmpfs | awk 'NR>1 {sum+=$3} END {print "tmpfs used (MiB): " sum / 1024}'

for a more readable output

df -ht tmpfs

it can use up to that number, but it won’t allocate that much when not needed, which is the case here. tmpfs can also use swap, so the maximum space available is system RAM + swap