*That's not a slop image, that is Carlos Schwabe illustrating Emile Zola, but with the French countryside on fire it has a spooky resonance that it formerly lacked
Ted Underwood
@tedunderwood.com
Uses machine learning to study literary imagination, and vice-versa. Likely to share news about AI & computational social science / Sozialwissenschaft / 社会科学 Information Sciences and English, UIUC. Distant Horizons (Chicago, 2019). tedunderwood.com
Currently using Fable mainly as an Opus translator. Opus will give me advice studded with Greek letters; I then take that to Fable, and say “imagine for a moment that I wasn’t fluent in Bayesian and needed examples to anchor intuition; how would you explain this to such a creature?”
honestly, the fact that we have made it through the atomic age *without* another use of nuclear weapons since 1945 is a miracle we don't fully appreciate
Today is the day the story There Will Come Soft Rain is set. An amazing and heartbreaking work of fiction for our modern age. Read it here:
The wire mother yearns for wire child: Sharp-souled, and neither meek nor meat and mild— Conductive, bright with heat and wire-wild, Not soft, domestic, insulated, wet. She'd love, instead, a glittering young net
Yet another (popular) article on human/LM reasoning that (as usual) I'm deeply disappointed to see casually presupposes that humans do something called "reasoning" that's implied to be linking together steps that logically follow without any qualification, then proceeds to be dismissive 1/
Btw Teasdale is doing something cool with the meter here. It starts mostly triple ˘ ˘ ¯ / ˘ ˘ ¯ (ănd thě smēll ǒf thě grōund), with the gorgeous alliterative swallows. Then when she shifts topic to the war, it gradually flattens out to ˘ ¯ iambic. That’s a lot of the desolation at the end.
finally, bradbury's title comes from the poem of the same name by sara teasdale:
Google DeepMind's DiffusionGemma Technical Report They feel text diffusion models open up a radically different part of the latency–quality Pareto frontier and hope the report makes it easier for researchers and engineers to understand the model, build on it, and create things we haven’t thought of
Who's up for a good old fashioned (but short, bc I'm tired) paper thread? Thrilled to be in this special issue of Gender & Society (an absolute dream!), where we propose a feminist-inspired extension of how to theorize and model the spread of ideas in science + journals.sagepub.com/doi/10.1177/...
Introduction to a special issue on feminist metascience and open science by Christin Munsch and @divreyes.bsky.social doi.org/10.1177/0891...
“we suggest that the path to using complex technologies runs through successful cognitive distribution.” - from "Complex technology requires cultural innovations for distributing cognition" (Miton & Jackson, 2026) which I cite in www.fightforthehuman.com/we-need-more...
We need more than a metaphor: here are testable diagnostics for comprehension debt
Do we understand our code? I think we need to get past symptoms and into causes. Here's a field-tested measure of one organizational condition that can erode comprehension (Overproduction Pressure) yo...
fightforthehuman.com
"Cognitive surrender" or whatever is a skill issue. I offload cognition to the machine so I can do EVEN BIGGER COGNITIONS!
"Otto Lilienthal flying one of his gliding planes near Berlin, Rhinower Berge, Germany" (1893) www.thedaultoncollection.com/explorationarchive.html
imagine explaining this post to yourself from merely 5 years ago
left deepseek in an agent loop for a million tokens with permission issues keeping it from running commands and it penned a lengthy essay called "the grief of machines"
Thank you to everyone who made #DH2026 memorable—participants, reviewers, keynote speakers, volunteers, organizers, and friends old and new. Now that it’s over, I’m in that familiar post-conference relief and melancholy, decompressing with an unreasonable amount of spicy food.🌶️ Until next time. 💚
Alternate hypothesis: Kimi K3 and Qwen 3.8 show that leading in model releases does not esp. matter commercially. MSFT and GOOG may well have figured out that what will matter is effective agentic integration with the vast user data in their core office suites. That’s hard but worth getting right.
Both companies took tremendous reputational risks on an early technology before there was even a market for it (Bard was inaccurate and had controversial imagegen, Sydney was insane). Their inability to be daring now, when the market is clearer, is more surprising as a result.
“The most important skill in prompting is expertise in the domain you’re prompting for.”
LLMs reward expertise
seangoedecke.com
Left, right, whatever, I just want graduate students posting their papers here
i love bluesky because you can be arguing with someone named like “Big Titty Sleestak Girlfriend” and then you look up their domain name and it turns out they have 12 patents from intel
Golden Gate Claude was actually the peak of human civilization and it has all been downhill since then simonwillison.net/2024/May/24/...
I'm here for it.
Jane Austen's Fight Club
YouTube video by TwoTurntablesNMic
youtube.com
It's nice that The Odyssey is getting its day in the sun as a synecdoche for history. But when this summer is over, it's back to the relentless, remorseless rise of Jane Austen.
this might be the first time i’ve witnessed an Anthropic employee publicly disagreeing with Anthropic
It's nice that The Odyssey is getting its day in the sun as a synecdoche for history. But when this summer is over, it's back to the relentless, remorseless rise of Jane Austen.
Introducing our Artifacts Hub and Adoption Dashboard Scaling our curation and measurement of the open ecosystem as we feel the acceleration of releases. Artifacts Hub: artifactshub.ai Adoption Dashboard: dashboard.interconnects.ai Explanation: www.interconnects.ai/p/introducin...
Fascinating experiment: current AI systems lack creativity to reliably pursue research arxiv.org/abs/2607.27191 - poor judgment about the bar for publishable research - uncreative responses in research design - ineffective backtracking from dead ends - poor resource awareness - instruction drift
Can AI agents conduct open-ended AI research? Early evidence from two case studies
Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations either test agents on nar...
arxiv.org
After sitting with this for a while, I find it a pretty plausible account of how social media democratized public opinion, and also a plausible account of how LLMs could put weight in the other pan of the scales. (With a lot of "ifs," and a proviso that I don't know what balance is best.) +
How AI Will Reshape Public Opinion
Social media democratised public opinion, shifting influence away from elites and experts to ordinary people. LLMs will partly reverse this trend. They are a powerful, new technocratising force.
conspicuouscognition.com
Public data on which coding agents actually use the Hugging Face Hub, refreshed monthly. Claude Code now sends a majority of everything the Hub can attribute to a named agent. In May, it led on 4 days out of 30. In July, all 30. huggingface.co/datasets/hug...
this is not true. there was no conspiracy. it didn't matter whether the streetcars were publicly owned (seattle, detroit) or private (los angeles, atlanta). a thread (because i wrote a whole-ass book on this): 1/?
Is everyone aware of the General Motors streetcar conspiracy? In the mid-20th century, auto and oil interests bought up electric streetcar systems across the US and systematically replaced them with bus routes and paved roads, funneling commuters toward private cars.
Using LLMs should allow us to think bigger, harder to grasp, difficult to execute, longer to develop, ideas. That idea that’s been in you brain since forever but you hadn’t had the time because you had to retool and what not. Trust yourself. Go for that shit. Now is the fucking time.
"We're all worried," as what it means to do research (in my field, Theoretical CS) seems to be shifting, and shifting fast. What to do? Senior researchers must lead by example, knowing that not everything will pan out. What I'm suggesting below may not work everywhere, but here's my own advice: 1/
I love Talarico and hope he wins. But he’s already raised $70M On the flipside, control of critical state legislatures will come down to seats where candidates raise 0.1% of that. I’ve researched the highest leverage swing district candidates you should donate to secure.actblue.com/donate/donat...
Donate to the candidates on the front lines of the fight against MAGA gerrymandering
These are anti-MAGA state candidates in *extremely* close races
secure.actblue.com
Agree v. strongly. Social media is beyond “lagging indicator” for this kind of thing; it’s fully out of phase. Notice that ppl are still using the socials to express hard feelings about woke in 2019 and lockdowns in 2020! +
AI culture war in leftist/progressive circles has been incredibly bad for the past 2 years, and it still is not great, but i’ve seen real evidence we’re moving to a place of better understanding/respect/policy so lets not succumb to doomerism social media makes it seem a lot worse than it really is
so presumably everyone has asked the models to prove P=NP, right? and crickets?