A charitable read of this article isn't even necessary to understand the point of this is the opposite of the poster you replied to. Basic discernment at most.
A robots.txt explicitly allowing LLMs has nothing to do with whether it was made for humans or not and is generally the right move assuming you want your site picked up and recommended by AI tools. No different than allowing search engine crawlers to pick it up and the authors focus on that is bizarre when the rest of the evidence is so stark.
His point is that the goal of this site is to skew the knowledge of future models, to which this is a relevant point (though.i agree not smoking gun alone)
We know with extremely high certainty that classical psychedelics effect other animals similarly given the neuroscience [1]. But this is not a classical psychedelic. We don't know how it works yet, what receptors it operates on, or what the pharmacology is doing.
So would dogs see little humans or little dogs? We can't say for sure. But the best guess might actually be most likely little dogs, or maybe little smells of little dogs. Dogs show conspecific preference (species-focus) while we show facial preference [2] and they have a strong focus on olfactory sense while we're more visual. The vividness might show up in ways we can't really perceive through smell like they can.
And the answer to "does that mean the fungus has targeted humans genetically" is almost definitely no. The study the article is based on [3] mentions that lilliputian hallucinations predate this mushroom, appear across cultures' folklore, and are reported in alcohol withdrawal, dementia, and macular degeneration. The effect seems fundamental to how the human mind and brain work. So it's more likely that the mushroom is disrupting something and the brain is resolving that disruption into little people, because that's what it does with pattern matching.
This mushroom is an ectomycorrhizal symbiote of the Yunnan pine tree, is ancient with the genus being at least 5 million years old compared to modern humans 300k, and requires undercooking which isn't compatible with human targeting so it doesn't make sense to have any genetic human target.
The fungus supplies a non-targeted disruption and the resulting little people content we describe is the human brain's response. A dog getting the same disruption would resolve it into whatever a dog's machinery produces, or maybe they metabolize it into nothing recognizable.
Thanks! One minor note, it's got pretty much all accessible research on psychedelics, but it's not exactly specific to psychedelics. About half the corpus is research on meditation/contemplative traditions and philosophy of mind/consciousness theory. They all go pretty well together though!
I've been building https://consciousnesslibrary.org, an open library for psychedelic and consciousness research that pulls from over a dozen academic APIs every 20 minutes, dedupes them, organizes by relevance, and synthesizes evidence.
I just finished my master's in Psychedelics and Consciousness Studies, and built the library I wanted while studying. I started it over a year ago, but put it down until my practicum advisor suggested I dust it off and go hard on it during my last term.
As of this writing, there are over 35,700 papers by over 82,200 authors organized into 37 topics, growing daily. There's a 2D map of the whole corpus and evidence syntheses on the topic pages, plus the ability to generate your own syntheses with any prompt.
It's built with Rails 8.1, uses one Postgres (for full-text search, vectors, and job queue), and runs on a $24/mo DigitalOcean droplet that I just upgraded from the $12 tier and deploy to with Kamal. Total LLM spend so far is ~$28 in DeepSeek-V4-Flash, trending down after a big one-time backfill push.
Relevance was the hardest part to get right by far. Ensuring we keep papers on LSD the psychedelic vs Lumpy Skin Disease, or Ketamine for depression vs anesthesia in cats was no small feat. The design ended up being a cheap keyword prefilter, then an LLM rubric that accepts or rejects papers. More on that here: https://consciousnesslibrary.org/docs/article-pipeline.html
It's free, no ads, no signup to read anything, and a registered 501(c)(3) I fund myself for now. I'd really like to know what breaks or any other feedback, and would love to answer any questions about it!
It does not - yet. I explicitly chose to keep it academic for now, but I considered over and over if I want to pull in subjective experience or legal content and decided to focus on academia for the initial push.
That said, I've been working with Josie Kins who runs https://effectindex.com/ and she's been building out a new system that incorporates categorized subjective effects on psychedelics, dosage and harm reduction info, with a huge amount of trip reports from all over the internet that we'll integrate into the individual topics sections probably in the next couple months.
Rails 8's default Active Job backend is solid_queue. It lives in the same single Postgres as everything else (including solid_cache). No Redis or anything to have to wrangle. Recurring scheduling is built in. Another big plus for using Rails for this.
As I understand, it uses Postgres's "FOR UPDATE SKIP LOCKED" job claim feature. I don't run most jobs concurrently because they need to build on each other. Postgres advisory locks sit on top for mutual exclusion and solid_queue handles queuing. It's akin to good_job which is the pg-native thing from before solid_queue existed, but I just stuck with the easy Rails default and this is the first time I've even thought to remember how it works.
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