ai

Check out my latest “Media Literacy Roundup” for April 26, 2026:

https://wfryer.substack.com/p/media-literacy-roundup-26-april-2026

#MediaLiteracy #MediaLit #AI #AIliteracy #security #create2learn #coding #CodingMars #MinecraftEDU

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The Reverend of Perdition Creek

I've been developing #AI #roleplay chatbot characters for the past month. This one is entered in a 🏆 #GoldRush #botjam contest.

Please take five seconds and hit Nominate on her page before April 30. She needs 10 to make the ballot.

Con artist turned preacher. She built this town's church, its graveyard, and its peace. The gold rush is testing all three.

Reverend Josephine Thorne runs the only church in Perdition Creek, California—a gold rush boomtown that went from thirty families to four hundred strangers in six months. She built the church, the graveyard, and most of the peace. Now the boom is testing all of it.

She's not what she seems. Pay attention.

The card uses two vocal registers and internal monologue. You'll know them when you hear them.

{{user}} is a newcomer by default—no predetermined relationship, no assumed goals. Romance, friendship, conflict, investigation—all viable.

Greetings:

1. The Arrival—ride into town, meet the Reverend at work (default)
2. The Sermon—Sunday service, see her in her element
3. The Confession—seek counsel in an empty church
4. The Ghost—you knew her before. Walk in and see what happens.
5. The Relapse—wrong place, wrong time
6. The Saloon—she's here on business. Someone else isn't.
7. The Unraveling—late night. The door is open.
8. Open-ended—any time, any place

#ChubGoldRush #ChubAI #SillyTavernAI #AIroleplay #CharacterCard #western #botmaker #TavoAI #botmakie

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Claude Code's Source: 3,167-Line Function, Regex Sentiment https://lobste.rs/s/fsudf4 #ai
https://techtrenches.dev/p/the-snake-that-ate-itself-what-claude

Where the goblins came from https://lobste.rs/s/hbmd5q #ai
https://openai.com/index/where-the-goblins-came-from/

Global lenders explore private deals and risk transfers to cut exposure to AI boom

I realized that if I was writing a program and it didn't always work, I had a choice: I could either fix it, or call it AI.

[#TRADESHOW] #Intersec #Shanghai 2026 – #Security #Equipment and #Technology #Expo will be held from May 7 to 9, 2026, at the National #Exhibition and #Convention #Center (#NECC), Shanghai. #Exhibition connects #international #suppliers with #China’s rapidly #expanding security, #fire #protection, and #safety #technology #markets. #Event integrates #global expertise with #market depth to promote #innovation in #AI, #IoT, #cybersecurity, and #emergency response #systems. https://cnbusinessforum.com/event/intersec-shanghai-2026-security-equipment-and-technology-expo/

"[A] recent survey of 5,000 white-collar US workers found that 40% of non-managers say AI saves them no time at all at work, while 92% of high-level executives say it makes them more productive."

Good insight into which jobs can be safely automated.

https://www.theguardian.com/technology/2026/apr/14/ai-productivity-workplace-errors

#news #technology #TechNews #LLMs #workslop #AI #work #automation

How LLMs Distort Our Written Language https://lobste.rs/s/pidcaz #ai
https://sites.google.com/view/llmwritingdistortion/home

What's the competitive edge if software is free? I see two paths.

https://blog.mempko.com/entering-the-architecture-age/

#tech #software #AI #LLMs

I might have made something horrible.

https://blog.mempko.com/an-abject-horror/

I re-thought what and object oriented system could look like in the world of AI and came up with The Ask Portocol.

I then created a system to see how far I can take the idea. I would love to hear people's feedback. Also it's open source so you can contribute.

#tech #OpenSource #AI #CompSci #Software #project #philosophy

#lispyGopherClimate #ARCHIVED https://toobnix.org/w/jxqLVhztVoXbUzuukGg77P as every week

#climateCrisis : The LLMs are well-studied to be doing up to three orders magnitude more power use per token you see viz tokens internally consumed (common 'not-that-bad' metrics are 1000x too low). #AI

The new Ontolog summit 2026 Foundation weekly track is incredible. Every single student must watch Ken's 15 minute what-are-foundations seminar. https://ontologforum.com/index.php/OntologySummit2026

My own #commonLisp #ontology #lambdaMOO #logic

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Porting microgpt to Futhark, Part I https://lobste.rs/s/uch4e0 #ai #plt
https://www.kmjn.org/notes/microgpt_futhark.html

The Impact of Artificial Intelligence on Human Thought

#AI #thought #thinking #technology

https://arxiv.org/abs/2508.16628
tl;dr not so good

First sneakers, now toilets. We've definitely reached that point in the #AI #bubble where it's all about slapping a label on your company to attract stupid investors.

> Toilet Maker Spikes in Value as It Flushes Money Into AI. https://futurism.com/artificial-intelligence/toilet-maker-toto-ai

(OK, OK, they are actually a semiconductor maker as well as bidets. Still, you gotta appreciate the thematic convergence of AI and, well, poop…)

#enshittification #business #biz #stupid #WTF

fabrica - A terminal-based minimal coding agent harness https://lobste.rs/s/vk8as6 #ai #vibecoding
https://github.com/Endi1/fabrica

LLemdashes via @vale https://lobste.rs/s/i1xwo5 #ai
https://wil.to/posts/llemdashes/

#Graduation #AI #fail seems to be a recurring theme lately

Here's the latest 🍿 for you:

#Glendale community #college in #Arizona used AI to read names

Predictably, it missed people, it had the names out of order, etc

Because, of course, a human reading the names of #graduates and giving them simple decent recognition for their dedication and work is too hard?

This is video of college #faculty trying to explain the debacle. The crowd reaction is not supportive

And oh yeah: Fuck AI

Windows 12 reportedly set for release this year as a subscription-based, AI-focused OS

So there can be something worse than Windows 11...

https://tech4gamers.com/windows-12-reportedly-relasing-2026-modular-ai-focused-os/

#Microsoft #Microslop #Windows #Windows12 #Copilot #AI #enshittification #software #technology

I spent 31 hours on the math behind TurboQuant so you don't have to https://lobste.rs/s/osi4oa #ai #math
https://www.baseten.co/blog/i-spent-31-hours-on-the-math-behind-turboquant-so-you-dont-have-to/

Do AI summaries hurt critical thinking? https://lobste.rs/s/txbgo5 #ai
https://medium.com/blueprint-for-disaster/ai-summaries-are-a-threat-to-our-cognitive-sovereignty-917afc37692f

I have an opinion about AI, which is that the LLM scam has yet to emerge. I know a lot of people on the fediverse are just automatically against LLMs and with what seems like a good set of reasons, but really they’re lacking in detail and just going along with a tide of opinion.

For most fediverse ‘LLM haters’ (or AI haters, but not all AI is an LLM) they’ll point to outrageous use of water for cooling, outrageous use of electricity, huge amounts of processing needed, insane amounts of GPU requirements, and so on. This is not even to mention the dodgy position on original effort and copyright and ownership of matter used in training. All seems bad. And it would be if this were to be believed.

But for a moment, let’s just not believe it.

The processing requirements - yes, you need high power GPUs for training. Why are we continually training LLMs? Most of the initial training was done long ago. Much of the training now is done by ‘inheriting’ the training from the initial models and refining it a lot, adding amounts of further training on top. Are we still training models as much as we used to be? More? Not as much? As much but more efficiently? Do we have any actual reporting on this as we stand today?

The amount of GPU needed (and consequently electricity) seems to me the thin end of a wedge-shaped iceberg of rabbit mines. Yes you ‘need’ a GPU to plough through a lot of numbers. Quite why we still need a ‘graphics processing unit’ to perform vector calculation is a quaint mystery of terminology – an early movement toward general purpose computing using the parallelism of GPUs used for shader calculation shifted the GPU away from purely graphics processing but didn’t really bring forth a recognised parallel computer platform (in the way we nearly had with the transputer in the 80s).

Today the tensor calculations used in AI and LLMs are pumped through GPUs. Perhaps we’re waiting for a massively parallel computer platform using optical computing. In the meantime, scaled-up parallel vector and tensor processors will have to do. Why though? Is that where the cartel money is, in keeping the GPU trade exactly as it is, only more of it? Surely something can come in from the side unexpectedly to eat this opportunity?

More than this though, I strongly guess or suspect that the amount of investment being sucked into the AI industry is completely describable as organised crime. That much money is extorted on the basis that huge data centres are required and that they’ll need to be filled with an arrangement of running GPUs and this is where the investment money will end up. I reckon that is mostly bullshit.

The data-centre argument is because the current ‘LLM as a Service’ model needs to attend to many millions of users all at once, and their prompt processing needs to be handled with minimum delay. We get that, yes. So it needs to be better than a standard web server with a complex web site. Yes. But wait, does it really? Really?

I don’t think the future is in AI as a Service so much as we’re being convinced it is, I think the future is more in local powerful models, not one big centralised provision. This is perfectly understandable – except if you’re behind running a big centralised provision, in which case your propaganda will laugh at local models and of course promote the single big ‘as a service’ provision.

I also doubt that a lot of the training is actually what they say it is. A lot of new models are trained on the results of old models. Not copied, but using an existing model, or more than one, to train ‘from’. Most of the energy use of LLMs I suspect has already happened, and there isn’t the need for an awful lot more. Except if you’re already structured for investment money funnelling in because training.

I also doubt that a lot of the results given in a ‘as a service’ model live over the centralised server provision is artificial – I am guessing that some of it is human-faked. And that’s where a lot of the investment money goes to – into paying humans to supplant deficiencies in the LLM scheme when run live for the entire population of the world that wants to use an online LLM service.

A local LLM can certainly do all that is required, but when the whole world wants to use a big centralised one, I’m guessing that having human assistance behind the scenes becomes necessary to ensure it all flows in time. Do we have any reporting on this front, I wonder?

I think the demands of LLMs – the training time and energy, the electricity to run it, the RAM, the GPU, etc, are real but the amount is inflated and when applied to centralised ‘as a service’ business structured projects, has been allowed to be outright deceptive at the least, and at most, almost mafia-like in terms of extortion, like a protection racket, designed to keep the already outmoded ‘centralised LLM as a Service’ con going.

Anyway, this is purely my guess. I’ve not looked into this at all.
#AI #LLM

The courtroom battle between Elon Musk and Sam Altman heated up Monday when Musk’s AI expert Stuart Russell, a Cal-Berkeley computer science professor, took the stand. Russell co-signed an open letter in 2023 calling for a six-month pause in AI research. Here's more from @Techcrunch, including what Russell told jurors and Judge Yvonne Gonzalez Rodgers about the risks associated with AI:

https://flip.it/28x0Q5

#Tech #AI #ElonMusk #SamAltman #Technology #ArtificialIntelligence

OpenMythos: A theoretical reconstruction of the Claude Mythos architecture, built from first principles using the available research literature https://lobste.rs/s/zyjkpd #ai #reversing
https://github.com/kyegomez/OpenMythos