Mark J. Nelson

@mm-jj-nn.bsky.social

Comp. sci. prof. @ American University, Washington DC. AI & games researcher with miscellaneous other interests. https://www.kmjn.org/

Since Aristotle, literary theory has studied texts and reception. We propose a new object of literary study: the latent spaces of an AI model trained on a single text. We call the method latent reading and apply it to the first case study: FinneganLM, trained on Joyce’s Finnegans Wake.

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Re: Last retweet, I will say I was impressed by the reviews from @aiide.bsky.social. And not even because they were positive (I think our paper probably won't get in). But they clearly read the paper carefully, were familiar with both our and other related prior work, and had very useful feedback.

VLADIMIR: Have they responded to our rebuttal? ESTRAGON: I haven't checked. VLADIMIR: You must. ESTRAGON: Why? VLADIMIR: To give us hope. ESTRAGON: Ok. We have a response. VLADIMIR: And? ESTRAGON: "I keep my score." VLADIMIR: (Stunned) He keeps his score? ESTRAGON: He keeps his score.

Melanie Mitchell@melaniemitchell.bsky.social · 2d ago

Edgy update of Waiting for Godot: Vladimir and Estragon are NeurIPS authors waiting for any reviewer to respond to their rebuttals.

I'm honestly happy to see some film-related Discourse on this site. I don't watch films myself, of course, because it's 2026. But I do think it's important that all the weird 20th-century retro media forms have communities striving to keep them alive.

This is kind of old news, but I pulled up 'macmon' on my Macbook, and still find it amazing that I can be running a full-featured laptop with a bunch of stuff open, and the total power draw is... 3 watts. Like 1/20 of what one single medium-brightness lightbulb used to use.

Not a strongly held opinion, but I'm a little skeptical of the recent LLM math results not really being compared against baseline search methods with similar compute budgets. Some of them are using pretty huge compute budgets!

I'm not normally a morning person, but I'm catsitting some cats who are used to having breakfast before their small human leaves for elementary school, so I guess I wake up around 8am now.

Recently discovered that the founder of our psychology department got fired after only a year due to a mail-fraud indictment. Later went on to a successful career in Hollywood, where he created Wonder Woman.

I see people are worried again about the increasing volume of papers in AI/ML. Just wanted to re-up my revolutionary O(1) solution*: browse the literature in time independent of paper count! * Assuming an idealized UI model where we can trigger timers & refresh content arbitrarily quickly

Mark J. Nelson@mm-jj-nn.bsky.social · 7mo ago

I uh, made this. It was supposed to be a joke / concept-art thing that scrolls through the torrent of new AI/ML arXiv uploads too fast to read. But I think I iterated too much and made it almost usable.

On the off chance you want to hear me talk about intersections between games and the history of AI, I'm giving at talk at the Arlington Public Library on August 4. Though it's intended more for a general public audience, and likely won't have too much new for people who follow me here.

AI and Games: A Recent History

Discover how AI changed gaming, and how gaming changed AI Find out how artificial intelligence has been considered in light of video games--and vice-versa. Go beyond simulated...

arlingtonva.libcal.com

A paper casting doubt on the foundations of a bunch of nice convergence bounds in multi-agent RL (found via @quokkka.bsky.social). The technical material here is a bit out of my depth, but relevant to some stuff I do in game AI. Attempt to briefly summarize based on an initial read below. 1/n

Paradoxes of Game Theoretic Equilibria and Price of Anarchy

For decades, static solution concepts (Nash, Correlated, and Coarse Correlated Equilibria) and the Price of Anarchy (PoA) have formed the bedrock of algorithmic game theory, with no-regret learning pr...

arxiv.org

Consider sponsoring the AAAI AIIDE conference in Belo Horizonte, Brazil! Your support will help motivate cutting-edge advancements in Game AI and creative technologies while giving you access to the best global talent in the field. Get involved: sites.google.com/view/aiide20...

AIIDE 2026 - Sponsors

Call for Sponsors We are excited to announce the Call for Sponsors for the The 22nd AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2026), taking place in Belo ...

sites.google.com

This criticism of early 2020s Netflix originals is fascinatingly similar to the complaints people have about genAI content. But all made by teams of paid human creatives following a formula.

In 2021 Netflix announced that it would start releasing a new original movie every week. A certain style soon began to take shape, a mind-numbing anticinema that anyone who has subscribed to Netflix in recent years knows by sight. I’ll call it the Typical Netflix Movie (TNM). From the outside, the TNM looks algorithmically constructed, as if designed to cater to each of Netflix’s two thousand “taste clusters,” the genre-like groupings Netflix uses to segment its audience, green-light programs, and recommend films and shows to subscribers. The TNM covers every niche interest and identity category in existence, such as a movie about a tall girl, Tall Girl, but also Horse Girl, Skater Girl, Sweet Girl, Lost Girls, and Nice......Girls. Seemingly optimized for search engines, the title of a TNM announces exactly what it is — hence a romantic comedy about a wine executive called A Perfect Pairing, or a murder mystery called Murder Mystery. The opening credit sequence looks thrown together, as if its designer were playing roulette with Adobe templates in After Effects. A typical shot frames two characters, waist up, in profile as the camera slowly dollies across them, a slow and constant whir meant to inject motion into an otherwise inert frame. There is a preponderance of drone shots. The characters’ dialogue is stilted, filled with overexplanation, clichés, and lingo no human would ever use, like two bots stuck in a loop. “Want to catch a beer?” a...