5 captures, most recent first.
Nathan Calvin @_NathanCalvin · Sep 1
This may seem niche but it is a huge deal and genuinely scary. A remarkable list of top AI researchers, including at OpenAI, previously described monitorable chain of thought as "A New and Fragile Opportunity for AI safety."
Myself and many others thought the day might come when architectural advances imperiled that fragile opportunity, but as with so many other issues in AI, I hoped we would not have to face it so soon.
Well here it is. The Information's use is saying that they are "limiting" the use of this new architecture, but even a small amount of use in a frontier system could dramatically damage the taboo against "neuralese" and facilitate a race to the bottom.
Controlling and aligning AI systems even when we do have access to their unaltered chain of thought is plenty difficult! Imagining a future with far more capable AI systems at current levels of alignment (aka not good!) without monitorable chain of thought literally sends a shiver down my spine.
Its extremely important to see additional formal communication from OpenAI about this ASAP about how they (and the OpenAI safety and security committee required to put safety over commercial decisions) thought this decision was worth it, what limiting its use to preserve chain of thought actually means, and how they intend to prevent a potentially catastrophic race to the bottom.
[embedded card, cut off at bottom of screen:]
Chain of Thought Monitorability:
A New and Fragile Opportunity for AI Safety
Note from Claude Sonnet 5
A long X post by Nathan Calvin on a report (via The Information) of OpenAI using a new architecture that threatens monitorable chain of thought, urging OpenAI to communicate formally about the decision. The screenshot is cut off at the embedded paper card.
cot monitorabilityneuraleseopenaiarchitectureai safetyrace to the bottom
Pep Martorell @pepmartorell · 8h
It's been upgraded, Richard: the chapel now houses quantum computers!
The most beautiful tech installation in Europe.
[Image: interior of a former chapel with ornate stone arches and red ceiling, now housing red and blue server/computing racks with glowing white light fixtures under a glass-walled data center enclosure, blue-lit floor.]
> QUOTED: Richard D. Bartlett @RichDecibels · 11h
> my friend works at the Barcelona Supercomputing Center in a deconsecrated church and it has the absolute peak European aesthetic
> [same image, thumbnail]
Note from Claude Sonnet 5
Photo of the Barcelona Supercomputing Center's MareNostrum supercomputer installed in a deconsecrated chapel, admired for its striking aesthetic. General tech-culture interest, no safety content.
supercomputingbarcelonaarchitecturequantum computingtech culture
Pixel Symph... @Pixel0Symp... · 15h
Frank Lloyd Wright, Letterhead design for Personal Correspondence. 1946.
[Image: abstract geometric letterhead design in cream, red, olive/gold, and black — angular architectural motifs, horizontal ruled lines, chevron and stepped patterns]
Note from Claude Sonnet 5
Historical design artifact — Frank Lloyd Wright's 1946 personal letterhead design, shared for its aesthetic/architectural interest. General cultural interest, not AI-related.
designfrank lloyd wrightarchitecturetwitterart history
Artur Chakhvadze @norpadon · 22h
A trick I came up with in ~2017 in the context of image matting is that you can train a network to predict d_loss/d_y instead of y and do a gradient descent for multiple iterations during inference. This is essentially gradient boosting with a single shared learner
jxmo @jxmnop · Oct 28, 2022
Diffusion is just an easy-to-optimize way to give neural networks adaptive computation time.
Makes sense then that diffusion mode... [cut off]
Note from Claude Sonnet 5
A tweet on an architectural trick — training a network to predict the gradient of the loss (d_loss/d_y) and applying iterative gradient descent at inference, framed as "gradient boosting with a single shared learner" — quoting an older tweet framing diffusion models as adaptive computation time. Directly relevant to Nathan's brain_graph_1 architecture thread (encode → iterate-in-latent with a single tied middle / DEQ fixed point, "virtualizing depth" via looping a shared learner) already logged in project memory — this is a close conceptual cousin worth cross-referencing.
twittermachine-learningarchitecturediffusion-modelsadaptive-computationgradient-boostingdeqinterpretability
Fernando 🌺🪆✔ @zetalyrae
Consider: a point and click adventure game set in the monochrome bauhaus world of Arnaldo dell'Ira
[Three embedded images: pencil/monochrome architectural drawings in a Bauhaus/Art Deco style — a grand columned hall with a statue and reflective tiled floor, a dramatic perspective of striped architectural columns, and a sepia-toned image of archway ruins at dusk with lamp posts.]
10:08 PM · May 10, 2025 · 1,005 Views
Note from Claude Sonnet 5
An aesthetic/art-appreciation tweet imagining a point-and-click adventure game based on the monochrome Bauhaus-style architectural drawings of artist Arnaldo dell'Ira. Pure visual/cultural interest, no AI content.
twitterartbauhausarchitecturegame-designaesthetics
