Flutterby™! (short)

Claudio Nastruzzi in The Register: Why AI writing is so generic, boring, and dangerous: Semantic ablation

When an author uses AI for "polishing" a draft, they are not seeing improvement; they are witnessing semantic ablation. The AI identifies high-entropy clusters – the precise points where unique insights and "blood" reside – and systematically replaces them with the most probable, generic token sequences. What began as a jagged, precise Romanesque structure of stone is eroded into a polished, Baroque plastic shell: it looks "clean" to the casual eye, but its structural integrity – its "ciccia" – has been ablated to favor a hollow, frictionless aesthetic.

Abraham Lincoln's letter to Henry L. Pierce declining an invitation to speak in Boston at a birthday celebration honoring Thomas Jefferson (that may have been intended to be read at the event):

This is a world of compensations; and he who would be no slave, must consent to have no slave. Those who deny freedom to others, deserve it not for themselves; and, under a just God, can not long retain it.

Via.

Think Academy Education Briefs: Sweden Education Shift: From Digital Learning to Pen and Paper.

I'm taken back to those conversations in the '90s where school board members, and administrators, were talking about "we need tech in the classroom!", and teachers, and sane people, were saying "what's the curriculum need?"

Especially as we've learned how students process pencil and paper note taking differently from typed note taking. And, heck, I'm still learning how I react differently to ebooks (on a multi-purpose device) vs paper books.

via Bruce Sterling

bob @bob@feed.hella.cheap

if the LLM-generated content is adding value then distributions of users/viewers/readers should be getting heavier tailed. are they? so far I've only seen people talking about number of books/apps/etc published which is unrelated to value

I suspect there's not a lot of value for the LLM wielder who's trying to push their material out to the wider world. If you want LLM generated content, you chat with the chatbot yourself and get a personalized experience. No real value to someone else talking with the chatbot.

Kevin Beaumont @GossiTheDog@cyberplace.social

Today in InfoSec Job Security News:

I was looking into an obvious ../.. vulnerability introduced into a major web framework today, and it was committed by username Claude on GitHub. Vibe coded, basically.

So I started looking through Claude commits on GitHub, there’s over 2m of them and it’s about 5% of all open source code this month.

https://github.com/search?q=au...ype=commits&s=author-date&o=desc

As I looked through the code I saw the same class of vulns being introduced over, and over, again - several a minute.

Interesting video about using a nibbler for cutting sheet metal, including building a nibbler table (like a router table), and using templates to get accurate repeatable cuts with the technique. No Laser Cutter? No Plasma Cutter? No Problem! Accurately cut sheet metal with low cost tools! By Rebecca Valentine.

I have lost a couple of the disks for the bottoms of some tart tins, and have been trying to figure out how to cut replacements. Need to get a nibbler and find some stainless steel sheet.

So Ars Technica wrote a thing on the Scott Shambaugh: An AI Agent Published a Hit Piece on Me (linked earlier), except that they used an LLM and it synthesized quotes that didn't actually get said or written. @mttaggart@infosec.exchange has a thread on this with receipts and archive links.

From this thread it appears that the slop publication was inadvertent from the editor's perspective.

Edit: Ars Technica: Editor’s Note: Retraction of article containing fabricated quotations

That this happened at Ars is especially distressing. We have covered the risks of overreliance on AI tools for years, and our written policy reflects those concerns. In this case, fabricated quotations were published in a manner inconsistent with that policy. We have reviewed recent work and have not identified additional issues. At this time, this appears to be an isolated incident.

And a mea culpa from the author, summarized by Michael Taggart:

First, this happened while sick with COVID. Second, Edwards claims this was a new experiment using Claude Code to extract source material. Claude refused to process the blog post (because Shambaugh mentions harassment). Edwards then took the blog post text and pasted it into ChatGPT, which evidently is the source of the fictitious quotes. Edwards takes full responsibility and apologizes, recognizing the irony of an AI reporter falling prey to this kind of mistake.

datarama @datarama@hachyderm.io

2010s: There is no cloud, it's just someone else's computer.

2020s: There is no Claude, it's just someone else's code.

datarama @datarama@hachyderm.io

2010s: Old Man Yells At Cloud

2020s: Old Man Yells At Claude

A programmer's loss of identity. I guess I'm lucky in that my association between mean and the Internet's notion of "programmer" kinda diverged when /. got funding, but this is an interesting meditation on how the general adoption of slop prompting as "programming" is changing the identity of those of us who think that reasoning about systems is important.

Via Baldur Bjarnason @baldur@toot.cafe

Meanwhile, Chris Dickinson @isntitvacant@hachyderm.io linked to Peter Naur, Programming as Theory Building (PDF) (You may remember Naur as the "N" in BNF notation) in response to Simon Willison's acknowledgement that LLMs separate him from the model building:

I no longer have a firm mental model of what they can do and how they work, which means each additional feature becomes harder to reason about, eventually leading me to lose the ability to make confident decisions about where to go next.

In linking to Margaret Storey's How Generative and Agentic AI Shift Concern from Technical Debt to Cognitive Debt (which also links to the Naur piece).

In response to Simon's note, Jed Brown @jedbrown@hachyderm.io wrote:

I believe the effect you describe becomes more insidious in larger projects, with distributed developer communities and bespoke domain knowledge. Such conditions are typical in research software/infrastructure (my domain), and the cost of recovering from such debt will often be intractable under public funding models (very lean; deliverables only for basic research, not maintenance and onboarding). Offloading to LLMs interferes not just with the cognitive processes of the "author", but also that of maintainers and other community members.

Unlike reports from ChatGPT, Google's "AI" seems smart enough to know that I'd have to drive my car to the car wash. Unless, of course, I was going to use a self-service bay.

Inspired by this thread.

First of all, what did Oregon do to the person who named the "Oregon Grape" after it. Second, I now have Opinions about the landscape designer who recommended it.

It finally sprawled enough that Charlene said she wanted it out, and I suspect I'll be following runners all summer...