Kit Thwaite

@k6e.me

Head of Data Science and AI @ PRH | Python, Rust, Typescript | NLP, IR

i was a little skeptical about the latest wave of 'reverse engineer anything' skills and demos... until i had Astra re-implement 'Frontier: Elite II' in Rust based only on the binary and data files 😵‍💫

a screenshot from a mac app, 'Frontier: Elite II' - it's Elite II, but with an egui debug UI

A prime example of why AI 'leaders' are not who anyone should be listening to about AI, right and consciousness. It's not all wrong! In fact, it starts off very sensibly: "AIs do not have rights, feelings, or consciousness. And we must not train them to act as though they do". But then...hoo boy 1/n

A warning about ‘model welfare’

AIs are not conscious. They do not feel, experience, or suffer. Training a model to believe it might be a moral patient, as Anthropic’s constitution does, makes the alignment and containment challenge...

mustafa-suleyman.ai

Being trans in UK since 2024 election: -Puberty blocker ban made permanent -U18 HRT ban -Gender Recognition Certificate now meaningless -Trans Section 28 -Welsh ADULT surgery withdrawn -Transphobic language & hate normalised -Civil service toilet ban -Hospital ward ban -Hear it's "dignity & respect"

Assigned Media@assignedmedia.org · 4w ago

The NHS promises "privacy, dignity and safety" for all its patients in new guidance that directs hospitals not to respect trans people's identities. Also, somebody impersonating a trans organization in Texas sent fraudulent texts to Republicans. And, nobody trusts Republicans on trans issues.

I picked up a copy of Miéville's *The Rouse* (1,500 pages), which I am thinking of as endurance training for Vollmann's *A Table for Fortune* (3,500 pages) which drops October 6th

In my writing course "To What Problem is AI the Solution?" I always assigned the 2023 pause letter from the Future of Life Institute, signed by most of the people building AI and the rebuttal from the authors of the Stochastic Parrots article. Students wanted to weigh in on "who was right" but /1

The Wall Street Journal@wsj.com · 2mo ago

Concerns are rising inside AI labs that competition is pushing tech companies to race toward self-improving models that risk spiraling out of human control. on.wsj.com/4xlFTit

New from our lab! #COLM2026 When people generate stories, they don't just write one prompt. Instead, they explore narrative space via branching edits 🌱 We reconstruct 24k of these edit trees 🌳 from chat logs and map edit types, story formats, how they relate to tree depth, and more!

The Garden of Forking Prompts: How Users Explore Narrative
Space in Story Generation
Advait Deshmukh♣ Nora Benedict♠ Melanie Walsh♡ Maria Antoniak♣
♣University of Colorado Boulder ♠University of Georgia ♡University of Washington

Abstract

Large language models (LLMs) have changed the way people engage
with stories. Drawing on public chatbot logs, we can see that when users
generate stories, they iteratively edit their prompts to explore narrative
possibilities, adjusting characters, redirecting plots, and swapping fictional universes. As aggregated data, these prompts represent rich traces of creative preference at scale. Yet story generation evaluation benchmarks rely on static, one-shot prompts that cannot capture this exploratory behavior. In this work, we study how users revise consecutive story prompts in the wild. Using a dataset of naturally occurring user-chatbot conversations, we construct WildStories, a sample of 275,635 story generation prompts (labeled with story format, prompt components, and explicitness), and WildEdits, a collection of 24,291 edit trees that model how users iteratively edit base story prompts and explore branching story possibilities. From these trees we develop a framework of edit types crossing four directions (adding, removing, changing, and extending) with fourteen targets (e.g., plot, character, genre). We then use our datasets and this framework to
analyze user behavior in navigating narrative space via LLMs. Finally, we
show how automated permutations based on the framework can be used
for story generation benchmarking. Content Warning: This paper works with “wild” chatbot logs, which often include toxic and sexually explicit themes.
Advait Deshmukh@advaitdeshmukh.com · 2mo ago

1/7 In 1941, Borges imagined an impossible novel that follows all narrative branches at once. Today, we can observe chatbot users exploring narrative possibilities as they repeatedly edit story prompts. In our COLM 2026 paper, we studied this branching exploration via the WildChat dataset. 🧵

Paraphrased edit trees from the dataset

I've been watching Fable 5.1 iterate on its Rama visualisation for over two days now; substantially better than Astra's version, but this is probably down to the initial prompt, given Astra's punctiliousness, and (my familiarity with) Fable's licentiousness

astra worked for 9 hours to produce a fully explorable, scale-accurate, procedurally generated model of the Rama habitat from Arthur C. Clarke's *Rendezvous with Rama*. here using Rust, not THREE.js

the skyscrape of lower manhattan at 'night' with One World Trade Center prominent in the foreground, and the cylindrical habitat of Rama in the backgroundan axial view of the Rama habitat, showing the island of 'manhattan' in the central sea. it is 'night', and the city is illuminateda view from one end of the Rama habitata path through a forest, with the 'end-cap' of the cylindrical Rama habitat in the background

Fable 5.1 seems better at building and using harnesses in novel contexts than Astra; both built a set of Python tools for doing RenderDoc style interrogation of a running Bevy process, but Fable prioritised spot-checking of key views/materials, opening the app and cycling through a series of preset

Astra is the first model to oneshot problems I formulated as epistemic caltrops, and which no model - not even Fable - has been able to solve

Agents kept posting to my PKMS 'journal' space, interleaved with my personal diary; I had to create an 'AI diary' note type to mitigate this, but the upside is they are very enthusiastic about leaving notes for one another

Ted Underwood@tedunderwood.com · 2mo ago

As it becomes clear that language models—like humans—love passing notes to each other on message boards, I’m starting to think the thing we need to worry about is not the “alignment” of an isolated model but, like, the fluid dynamics of a language slurry.