Jeremiah Senkpiel

@Fishrock
213 Followers
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Staff Rust-lang developer. Backcountry powersports nerd. Adventure motorcyclist. Dirtbiker. Snowmobiler. Ski tourer. Trad rock climber. Former dungeon master.
GitHub / TwitterFishrock123
Websitehttps://www.jeremiah-senkpiel.com
LocationNorth Okanagan BC
#3254 - Detector

I am available (immediately) for Rust work! Whether it is finding nontrivial performance gains, reviewing code for correctness and soundness, or writing implementations from scratch, I am a knowledgeable engineer with experience at companies large and small from various industries.

If your company would like to discuss setting something up, contact me via the email on my GitHub profile (https://github.com/jhpratt).

#Rust #RustLang #programming #FediHire #GetFediHired

jhpratt - Overview

Contributor to Rust's compiler and standard library. Maintainer of Rust crates with over 3.0 billion downloads. Third degree black belt 🥋 - jhpratt

GitHub

@gsuberland

i am a

☐ man
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☒ disk drive

seeking

It occurs to me now that even JEPA based AI models are missing a key feature of human communication - the ability to separate ideas fully.

It feels as though a hierarchical system needs to have the ability to distinguish if there are multiple ideas in a given input and be able to put those into their own separate high dimensional representations at lower levels.

So if you tell Claude code to “not delete any files”, it is literally incapable of actually respecting that.
It seems unclear to some people, so let’s be clear: telling an LLM what to do does not “tell it what to do”. They cannot truely process instructions. All they can do is give you a median centered normal distribution of text that would follow from such text as provided. Yes, they can maintain context and focus, but they cannot plan by instruction.

RE: https://neuromatch.social/@jonny/116667022863059853

Excellent thread on what "LLM-assisted" testing actually does, with context from rsync replacing its test suite with a poorly vibe-ported Python version (as regressions roll in)

More generally, the primary product of LLMs is deception: the unfounded belief by the insufficiently-critical observer that the task has been performed. From vibe-coders to user communities, managers, and investors, there are many targets of the deception. Many are playing along for their own self-interested reasons (e.g, executives need investor confidence more than they need a product). And many feel hit when peers and communities see through it.

If you previously donated to the Wikimedia Foundation (e.g. via the beg notices on Wikipedia), it is still good to donate to the local chapters if there's one in your country. They're chronically underfunded (e.g. by the WMF) and generally are tax deductible charities too.

https://en.wikipedia.org/wiki/List_of_Wikimedia_chapters

List of Wikimedia chapters - Wikipedia

A massively multiplayer discussion game: Naïve Online
@chris Learning is forever but a Claude Code subscription bills monthly.