CommanderPhoenix

@docvivileandra.bsky.social I remember you saying something about wanting movable arms. Looks like a non-3D option is becoming a thing.

So, you are asking to be taught a lesson...

Ya'll use actual razors for shaving? I've just been using these bad boys. Sharp as hell and works great if you know what you're doing.

Currently running a Lancer game with people from @docvivileandra.bsky.social 's discord server. So far, my players have committed three counts of police brutality, but it's ok, they deleted their bodycam footage.

Growing up a city kid, I never had the opportunity to see the Milky Way and its hundreds of billions of stars splattered across the night sky with my own two eyes. But every time, I see even just a picture, I'm memorized by what all could be up there. Wish we could one day explore it all.

The forth panel of a comic by Shen Comix @shenanigansen on twitter/x or u/shenanigansen on reddit. This frame depicts the author replying to an alarming piece of information with what seems like a very calm exclamation of "Jesus Christ."

"over 3/4ths"

Refs cont.

Jumper, John et al. “Highly accurate protein structure prediction with AlphaFold.” Nature vol. 596,7873 (2021): 583-589. doi:10.1038/s41586-021-03819-2

DeepMind’s protein-folding AI has solved a 50-year-old grand challenge of biology AlphaFold can predict the shape of proteins to within the width of an atom. The breakthrough will help scientists design drugs and understand disease.

Refs

Heaven, Will Douglas. “DeepMind’s Protein-Folding AI Has Solved a 50-Year-Old Grand Challenge of Biology.” MIT Technology Review, Massachusetts Institute of Technology, 20 Oct. 2021, www.technologyreview.com/2020/11/30/1012712/deepmind-protein-folding-ai-solved-biology-science-drugs-disease/.

Then again, I study industrial design, not comp-sci. Someone more informed on the details of the technologies I mentioned could probably work out the details of such a concept and its viability much better than I could.

If a similar architecture is used to create a translator software, and trained only to translating two languages in one direction (instead of dressing up ChatGPT with some directions in the initial prompt), a reliable and context/culture aware translation software might just be possible.

By using the two processing paths to correct each other within the evoformer blocks and recycling the result to the start multiple times to further refine the results, AlphaFold is able to filter out a lot of of errors and achieve the impressive results it demonstrated in CASP14 (Jumper et al.).

In my limited and somewhat uneducated reading of Alphafold 2 paper, the architecture that enabled the impressive degree of accuracy in its predictive performance works by running two processing paths in parallel, one using MSA representation, the other using Pair representation.

To oversimplify, and also to draw a possibly bad analogy, to a breakthrough in a tangentially related field: AlphaFold 2, developed by DeepMind, scored over 90 in CASP's Global Distance Test for about 2/3 of the proteins (Heaven), an impressive figure.

That said, I don't doubt that could possible to create a program that can reliably provide workable context aware machine translation using technologies developed in the process of creating LLMs.

Particularly I'm thinking that the Transformer Deep Learning Architecture could be helpful here.

This is genuinely horrifying. I had assumed that LLMs have an advantage in translation over older technologies because they are uniquely designed to process natural language.

In hindsight, however, given that general LLMs are effectively supercharged autocomplete, this really isn't surprising.

I get that the human brain has really great storage capacity and all but you gotta remember that it's only because of the extremely lossy compression, which basically works by throwing away most of the data and reconstructing it from context at recall.

In other words, *corrupts your data*

That said, whether or not any cybernetics could meaningfully accelerate this process is a different matter entirely.

A scenario where conscious experience dictates long-term (more than the next few seconds) planning, while parts of your nervous system that you're not normally aware of take care of the fine details in the moment, in such a way that makes everything feel like conscious decisions.

While your conscious experience feels objectively slow, the discrepancy between reaction times and perception to experience latency implies that your body already does exactly what you described as how a realistic "Sandevistan" might work:

The median human reaction time is 273ms, according to humanbenchmark.com (My attempt was 224ms, removing latency from computer hardware, it's closer to 210ms). This implies that a person, without needing cybernetics, is already able to react faster than they can consciously decide their next move.

According to Herzog et al. in their paper, "All in Good Time: Long-Lasting Postdictive Effects Reveal Discrete Perception," published in Trends in Cognitive Sciences, it can take between 300ms and 500ms for a stimulus to become a conscious experience.

If you think about it, a skin-tight mechanical pressure suit and flak armor panels are very hot. Possibly slutty

#vtuber #envtuber

Then they came for the Jews
And I did not speak out
Because I was not a Jew
Then they came for me
And there was no one left
To speak out for me

- First they came, by Pastor Martin Niemöller

First they came for the Communists
And I did not speak out
Because I was not a Communist
Then they came for the Socialists
And I did not speak out
Because I was not a Socialist
Then they came for the trade unionists
And I did not speak out
Because I was not a trade unionist

👀

afaik, the definition of "peer" here refers to the 2nd noun definition from the Oxford Dictionary which reads: "a person of the same age, status, or ability as another specified person."

For people who's entire job that is to write things, they sure don't pay attention to definition of words

📒🐧✏️
"Noted"

fr tho, I can't find any reliable source of if the "wood of your own hunger" was actually generated by Deep Seek R1, but if my computer wrote that out for no good fucking reason I will be watering it with the garden hose.

In any case, in their blind crusade to sate their inferiority complex through the use of artificial agents, not tools anymore, they will find that what they have unleashed is "what happens when you try to carve God from the wood of your own hunger." to quote, very ironically, Deep Seek R1

As far as I am personally concerned, you could probably give me just about any task (except coming up with names or cool acronyms) and I can reliably do it better than any AI models in existence. And I am at least the second least professional person I personally know.