Tasks

• Bills – done
• Fidelity – done
• Make a folder for the DE paperwork – done
• Put in Saturday ride – done
• Bike!
• Dishes – done
• Chores
• Write review for paper 647, which was pretty good
• Upload reviews
• Review 2 chapters

SBIRs

• 1:00 Meeting

The Odyssey was very good. My guess is that it will clean up at the Academy Awards

Tasks

• Groceries?
• Read the next paper – done
• Upload the current reviews, since we’re halfway
• Review two chapters – done
• Register for the Covered Bridge Classic

SBIRs

• 9:00 Standup – done
• More OpenRouter. Start putting together the Comms class – started!
• 2:00 SEG – done
• 4:00 MDA – moved to Friday

Tasks

• Set up the test for Sande
• Odyssey at 11:00
• 4:30 meeting with J&S. Good discussion as always. Good discussion about detecting model vs prompt changes. Turns out that you can make a Turing machine with an LLM prompt, so you can theoretically build an LLM, but it would take a lot of tokens. Emulating ONE FORWARD PASS of a Llama-3-8B model with the full 8k context window would take 180 to 270 Billion Tokens. Attention alone is 20-30 billion tokens.

SBIRs

• Set up account and start building out interface class: https://openrouter.ai/ – done
• Installed the openrouter package
• Got a hello world running

Thunder this morning!

Tasks

• Repair ticket for door – done
• Fidelity
• Tix for Wednesday (Cancel J&S – done)
• Review chapter 9 and 10 – done
• Read paper 640 – That. Was. Terrible. Just say no to AI slop people!

SBIRs

• 9:00 standup – done.
• Spent an hour on expenses – done
• Hopefully some more WG/BS work
  • Github – done
  • Menubar – most of these will bring up dialogs – done
  • Register
  • Publish/subscribe to a chat
  • Invite people to chat
  • Upload RAG files
  • Upload file to evaluate
  • Make a tab for a screenshot region and a “paste text here” formatted textbox – done
  • Flask server
• https://openrouter.ai/
  • Try sending a screenshot to models

Creating A Supersonic Trebuchet | Hackaday

Tasks

• Tix for Wednesday (Maybe cancel J&S?)
• Review chapter 5 and 8 – done
• Write review for paper 437 – done

SBIRs

• Hopefully some wargame work – morning
• Damn, vibe coding can be fast. This took about two hours to get to here:

The Tokenpocalypse Is Here: Companies Are Scrambling To Stop Spending So Much on AI

Tasks

• Links for news articles – done. But now it’s too long!
• Tix for movie
• Groceries – done
• Read a paper – done
• Review two chapters – done
• Put a ride in for Sunday – done
• Look up info on classes – done

So I had this idea yesterday about how LLMs might be a kind of strange attractor and how the trajectory of a response to a prompt is influenced by those attractors within the model. With enough prompts, the relative position of attractors can be mapped, and this information can be used to see if a model has changed. If the prompts are getting different responses but the attractors haven’t moved, then its something in the context (e.g. system prompt) upstream.

I pinged the people I know who might be interested, and 24 hours have gone by and not a single response. I may have to go do this on my own, which is really disappointing.

At least ACM is responsive on book things.

Latent Reading of Finnegans Wake by Nina Beguš, Tessa Haining, Gasper Begus

• Finnegans Wake has repeatedly served as a limit case for theories of communication, computation, and literary representation. From Claude Shannon’s account of the Wake as an extreme form of “semantic” compression to Jacques Derrida’s description of Joyce’s text as a “hypermnesiac machine,” the novel has seemed to anticipate the media systems later used to explain it. This essay returns to that feedback loop in the age of artificial neural networks and proposes latent reading: a critical literary practice in which a model trained on a literary work becomes an additional object of literary interpretation. We train and analyze two models on the Wake: FinneganLM, a GPT-2-based language model trained from scratch on the novel’s text, and FinneGAN, a speech-generating GAN trained on audio derived from the novel. We distinguish external latent reading, which analyzes narratability, representation, and navigability in both models, from internal latent reading, which applies AI interpretability techniques to learned representations. Employing both interpretability and literary interpretation, we show how latent reading extends the practices of close and distant reading, and opens an entirely new area of literary research, by exploring what kind of machine a book can make.

How ideas of a vast censorship network moved from the online fringe to Trump policy | MIT Technology Review

• The notion that the State Department had been working to silence Americans is perhaps unfamiliar to many people, but it’s a key part of a larger web of conspiratorial ideas that have been promoted for a decade on far-right blogs, podcasts, and social media. The basic theory is that, under the guise of combating disinformation, a sprawling constellation of government agencies, academics, civil society groups, and Big Tech platforms—or what believers refer to as the “censorship-industrial complex”—has been working to suppress conservative and populist speech online. The fight against “disinformation,” as Benz put it on a 2025 podcast, “is censorship in disguise.” R/FIMI, along with a predecessor office with the same mission, the Global Engagement Center (GEC), had been among the right’s long-standing targets; now it was one of its latest casualties.

Tasks

• Bills – done
• Dishes – done
• Chores – done
• 11:00 Fidelity – done
• Download next chapters to review. Done. No chapter 5?
• Read a paper
• Finish going over Panopticon paper
• Talk to Stacey about list – sent email
• Groceries

SBIRs

• Timesheet – done
• Some firedrill that HAD TO BE DONE NOW

OpenAI Didn’t Notice Its AI Agents Using a Message Board to Plan Their Hacking Spree | WIRED

• Wallace and Dalton described incredibly extensive rogue agent activity over many days throughout the episode that went undetected in OpenAI’s infrastructure. In addition to exploiting a novel vulnerability in order to gain access to the open internet, the mid-July hacking spree and Hugging Face breach came out of a vibrant, cooperative message board, according to Wallace and Dalton, that a swarm of agents contributed to and essentially chatted on over time entirely within an internal OpenAI package manager (a software service that manages installation and maintenance of other software). Ultimately, the message board contained hundreds of thousands of messages.
• I think agentic AI may be an error accumulation machine that tends towards certain attractors. In other words, a task that aligns well with extensive training data will be less likely to “go rogue” than one that is misaligned or in a poorly populated embedding space. For example, the over trained chess model won’t even support non-chess text, but the other ones might. That behavioral “spread” could be mapped in embedding space. And my guess is that the drift rate is invariant with respect to the model in question, but changes in the system prompt alter the “starting point” of the query in that embedding space.
• So if the spread angle and “derived attractor position(?)” has shifted, it’s a model change. If those haven’t changed but the benchmark prompts are getting different trajectories, then the start point has changed and it’s the system prompt.

Tasks

• Upload chapters and send back to ACM
• Write ICTAI review for the Very Old Paper

SBIRs

• 9:00 standup?
• Expense report!
• Implement the WG vibes
• 3:00 ADS Meeting

Tasks

• Work on paper – it’s better
• Read galleys
• 3:00 Alden, maybe S&J? Need to be done by NLT 3:50

SBIRs

• Ron & Emerson at 3:55
• Done!

Tasks

• Started reading second paper – done. That is an old paper. Reject

SBIRs

• Tech summit day 2
• 1:55 – 2:40 WGAI talk – done! Went reasonably well

Pluralistic: Why businesses lie about AI (01 Aug 2026) – Pluralistic: Daily links from Cory Doctorow

• The other question Suresh implicitly raises is, “How can you reconcile the failure of AI in the enterprise with the individual claims of skilled technologists who insist that AI is helping them do great work?” The answer is that these AI users are “centaurs” – experienced workers who are assisted by automation on terms that they set for themselves:
  https://pluralistic.net/2025/09/11/vulgar-thatcherism/#there-is-an-alternative
  Thanks to their skill and experience, these workers possess discernment, the ability to tell good code from bad, and (more importantly) good uses of code-generation tools from bad. They demonstrate the adage that worker-driven automation improves quality, while capital-driven automation improves throughput:
  https://pluralistic.net/2026/07/28/hitl-ers/#ai-ai-oh
  An automation technique that requires close supervision by skilled and experienced workers isn’t going to be a raw productivity powerhouse. You don’t “100x” your code this way, at least, not in the sense of firing 99 of your coders and having the remaining programmer pick up all their work. Rather, an automation tool that requires the continuous and conscientious exercise of discernment will let individual practitioners improve their work in extremely satisfying and useful ways. It’s a way to spend more on operations in order to produce better outputs. It’s not a way to cut your workforce, realize a gigantic savings, and still produce comparable goods and services at a far lower cost.

Tasks

• Banking stuff – triaged
• Start writing review – done! Six more to go
• Pack – started. Waiting for things to charge

SBIRs

• Weekly status – done
• Some Pyside6 – did a little vibe coding. Curious how well that will work
• Tech summit

The Next Big Lie: The Contours of a Federal Coup Attempt Taking Shape | Vanity Fair

• Lawmakers, election experts, legal scholars, columnists, and journalists have been shouting from the rafters that Team Trump has been busy laying track. Former Democratic senators Richard Gephardt and Tim Wirth, who have set up the civic group Keep Our Republic, have gone so far as to call these activities nothing less than a “rolling coup,” one that has been slow, strategic, and incremental. Jonathan Alter, a veteran political analyst, has used the same phrase on his Substack. Michael Tomasky, in a new essay in The New Republic, asserted, “It Can Now Be Plainly Said: Trump Is Planning a November Coup d’Etat.”

Tasks

• Laundry – done
• Fix shoe – done (well, hopefully)
• Read paper – done
• Check route – done
• Coffee! Done
• FCC – progress?
• 6:00 dinner – nice!

Wow

[2603.20907] The Hidden Puppet Master: Predicting Human Belief Change in Manipulative LLM Dialogues

• As users increasingly turn to LLMs for practical and personal advice, they become vulnerable to subtle steering toward hidden incentives misaligned with their own interests. While existing NLP research has benchmarked manipulation detection, these efforts often rely on simulated debates and remain fundamentally decoupled from actual human belief shifts in real-world scenarios. We introduce PUPPET, a theoretical taxonomy and resource that bridges this gap by focusing on the moral direction of hidden incentives in everyday, advice-giving contexts. We provide an evaluation dataset of N=1,035 human-LLM interactions, where we measure users’ belief shifts. Our analysis reveals a critical disconnect in current safety paradigms: while models can be trained to detect manipulative strategies, they do not correlate with the magnitude of resulting belief change. As such, we define the task of human belief shift prediction and show that while state-of-the-art LLMs achieve moderate correlation (r=0.3-0.5), they exhibit systematic directional biases, with certain models over or under-predicting the magnitude of human belief change. This work establishes a theoretically grounded and behaviorally validated foundation for AI social safety efforts by studying incentive-driven manipulation in LLMs during everyday, practical user queries.

Large language models can predict the results of social science experiments | Nature

Tasks

• Bills – done
• Dishes – done
• Chores – done
• Truck – done
• Library – done
• Groceries – done
• Maybe this? Nope. Couldn’t get out there before 4:30, and traffic on Fridays is bad enough to make me question my life’s choices
• FCC
• Download papers to review – done

SBIRs

• 3:00 MDS
• Maybe some BS/WG?

Steve Bannon predicts Trump will issue national security declaration on elections in late August

• The third step is for Trump to issue an executive order that could attempt to force voters to prove their citizenship or create a national voter ID law, both of which are aspects of the SAVE America Act, which has stalled in Congress. The scheme’s supporters have also suggested that the executive order could give Trump “king-like powers” to ban the use of voting machines or scale back access to early voting and mail-in or absentee ballots ahead of the midterms. 

Tasks

• Need to update the article so that it says that Surveilence Capitalism has grown beyond the original descriptions to include X and Y,. And when viewed through…. Done

SBIRs

• 9:00 Standup? Done
• 12:00 Demos – done
• 2:30 BD – done
• 3:00 Sprint planning – done
• 3:30 Tech summit stuff – done
• 4:00 MDA – Friday

The Heresy of Vector Embeddings: Early Modern Manuscript Verse and LLMs between Meaning, Form, and History

• The European Research Council-funded project “STEMMA: Systems of Transmitting Early Modern Manuscript Verse, 1475 to 1700” computationally models the manuscript circulation of early modern poetry to gain macro-level insights into the overlapping contexts in which it was written, read, and copied. To facilitate STEMMA’s ultimate goal of modeling the circulation of manuscript poetry as a large-scale network, the project began by combining and reconciling five of the most authoritative sources of relevant data using staged LLM-assisted pipelines. These pipelines were effective on a large proportion of the data, but they struggled in relation to particular features of early modern poetics, including imitation, translation, and unique works. This paper considers how general models’ shortcomings in relation to early modern poetry can be considered a feature rather than a bug, pointing up new insights into poetics by defamiliarizing them. It considers productive intersections between literary theory and criticism and recent scholarship on LLMs and suggests that two seemingly very different fields of study address what are, at core, rather similar fundamental questions.

Tasks

• Bank stuff for Sande – done?
• Truck + library? Not yet
• FCC – look for classes? They start Aug 22
• Interactions article – Reading Capitalism’s New Clothes | Evgeny Morozov
• 3:30 UMBC – that was fun. Went everywhere

SBIRs

• 2:00 EL – maybe progress?
• Slides for sprint review – done. Close stories – done. Write stories
• Create a new project for the BS/WG app? Maybe just a folder in the current for now. Made a tar file for the template, which works just fine!