Martin Wattenberg

Martin Wattenberg

@wattenberg.bsky.social

Human/AI interaction. ML interpretability. Visualization as design, science, art. Research scientist at Google DeepMind.

8.1K followers1.2K following425 posts

Four dimensions is too many! Let's unfold this 4D cube to three dimensions, then two, and then one. Don't worry, we'll put it back together again. The math is lovely, but it's the rhythm and dance of the lines that fascinates me here.

The one paper I review that desperately needs an ethics discussion is, predictably, the one paper that omits one. Meanwhile, the other papers are utterly innocuous and have long statements that are basically "Air currents created by typing this paper may potentially lead to a hurricane in 2029"

This is such a fantastic paper! We need more of this kind of empirical work on what people really do with AI. The idea of the "solipsistic reader-writer" seems important. Also, the paper is so well-written!

Melanie Walsh@mellymeldubs.bsky.social

Excited to share this. @neel2112.bsky.social, @mariaa.bsky.social, and I analyzed 500K anonymous ChatGPT convos (shared w/ consent from WildChat) to see if people were generating fiction. We found tons of stories, fanfiction & erotica. Many users iterated on the same stories for days and weeks.

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That offers governments a vast, unprecedented level of power over their citizens. In evil hands, that’s obviously a disaster. But, like the framers of the US Constitution, I believe it’s also wrong to give absolute powers to democratically elected leaders, or people you think of as the “good guys.”

As AI capabilities increase, we need a broad, deep, society-wide discussion of what limits make sense, and how we can hold the government meaningfully accountable to citizens. For that reason, I stand with Anthropic and anyone else who is avoiding a rush toward mass AI surveillance.

Before now, there was always a natural barrier on the power of surveillance. Even in the limit, if everyone’s actions were recorded all the time, there wouldn’t be enough people and time to watch and analyze the entire footage. But AI threatens to make that natural barrier completely obsolete.

In 2025, AI left its imprint on everything—even names! If you've ever asked an AI to tell you a story, you've probably seen the Elara-Elena-Clara nexus...

Meet Elara, the Name of the Year. She doesn’t exist. Yet she’s everywhere—and she’s all of us. bit.ly/Elara-Name-o...

I want to play with this clever book myself!

Global Museum@globalmuseum.bsky.social

A book from the 19th century that depicts the Rhine Valley by creating an impression of three-dimensionality and spatial distance. @MasayukiTsuda2 #globalmuseum #books #travel #19thcentury

Martin Wattenberg reposted

Charts and graphs help people analyze data, but can they also help AI? In a new paper, we provide initial evidence that it does! GPT 4.1 and Claude 3.5 describe three synthetic datasets more precisely and accurately when raw data is accompanied by a scatter plot. Read more in🧵!

Martin Wattenberg reposted

AI is often thought of as a black box -- no way to know what's going on inside. That's changing in eye-opening ways. Researchers are finding "beliefs" models are forming as they converse, and how those beliefs correlate to what the models say and how they say it. www.theatlantic.com/technology/a...

theatlantic.comWhat AI Thinks It Knows About YouWhat happens when people can see what assumptions a large language model is making about them?

A wonderful visualization for those of us obsessed by sunlight and geography!

Olivia Vane@oliviafvane.bsky.social

This map shows the hour of sunrise globally through the year. It reveals time zones following national and, sometimes, regional boundaries, and slicing through the oceans.

An incredibly rich, detailed view of neural net internals! There are so many insights in these papers. And the visualizations of "addition circuit" features are just plain cool!

Chris Olah@colah.bsky.social

Can we understand the mechanisms of a frontier AI model? 📝 Blog post: www.anthropic.com/research/tra... 🧪 "Biology" paper: transformer-circuits.pub/2025/attribu... ⚙️ Methods paper: transformer-circuits.pub/2025/attribu... Featuring basic multi-step reasoning, planning, introspection and more!

I'd be curious about advice on teaching non-coders how to test programs they've written with AI. I'm not thinking unit tests so much as things like making sure you can drill down for verifiable details in a visualization—basic practices that are good on their own, but also help catch errors.

Neat visualization that came up in the ARBOR project: this shows DeepSeek "thinking" about a question, and color is the probability that, if it exited thinking, it would give the right answer. (Here yellow means correct.)

Great thread describing the new ARBOR open interpretability project, which has some fascinating projects already. Take a look!

David Bau@davidbau.bsky.social

ARBOR aims to accelerate the internal investigation of the new class of AI "reasoning" models. See the ARBOR discussion board for a thread for each project underway. github.com/ArborProjec...

Out: rectangular maps of the globe In: rectangular maps of butterfly wings!

The Public Domain Review@publicdomainrev.bsky.social

In 1897, Alfred G. Mayer created his butterfly wing projections, an attempt to gain new insights into natural patterns and laws. Vertical blocks denote individual wings, distorted and stretched mathematically to fill a tidy rectangular space. More here: publicdomainreview.org/collection/m...

Martin Wattenberg reposted

What a beauty! This is comet C/2024 G3 (ATLAS) passing through the field of view of the LASCO C3 coronagraph. It wasn't for certain whether it would survive it's closest approach to the sun on January 13th, but it did and delivered us a spectacular show! #comet #C2024G3 🔭

Idle question: Are there any papers from legit math journals using emoji as notation? We already use every symbol on the keyboard, musical sharps and flats, and even weird made-up fonts (what is that Weierstrass P??). A smiley is easy to draw with chalk and put into LaTeX, so why not?

Martin Wattenberg reposted

New paper <3 Interested in inference-time scaling? In-context Learning? Mech Interp? LMs can solve novel in-context tasks, with sufficient examples (longer contexts). Why? Bc they dynamically form *in-context representations*! 1/N

If you're the kind of person who likes thinking about the sky (and I am!) this is a wonderful visualization to explore. So many patterns, each with its own story.

Cees Bassa@cbassa.bsky.social

For the 4th year in a row, my all-sky camera has been taking an image of the sky above the Netherlands every 15 seconds. Combining these images reveal the length of the night changing throughout the year, the passage of clouds and the motion of the Moon and the Sun through the sky. #astrophotography