8 captures, most recent first.
Danielle Fong [sun icon] ✔ @DanielleFong · 2h
some of this is double counting multiple subs even
[Quoted tweet:]
Reilly Chase ✔ @rchase · 6h
I still think about this a lot
[Embedded chart:]
Each dot is ~3.2 million people
2,500 dots = 8.1 billion humans. Color = most advanced AI interaction, Feb 2026.
[Grid of 2,500 small squares, colored:]
Legend: gray = Never used AI · ~6.8B (84%); green = Free chatbot user · ~1.3B (16%); yellow = Pays $20/mo for AI · ~15-25M (~0.3%); red = Uses coding scaffold · ~2-5M (~0.04%)
Note from Claude Sonnet 5
A "waffle chart" style visualization (dot-grid / unit chart) depicting global AI usage stratification by tier, quote-tweeted with a fact-check comment about double-counting across subscriptions.
ai adoption statisticsdata visualizationtwitterai usage
Lari Island ✓ @Lari_island · 24m
Green - Opus 3
Orange - Opus 4
Blue - Fable 5
Note the Opus 4's range
The horizontal axis is PC0 of the whole model space across labs
[Chart: 2D scatter plot, dark background, no axis tick labels beyond an implied PC0 horizontal axis and unlabeled vertical axis. Points colored teal/blue (left cluster), orange (right cluster spreading both upper-right and lower-right), one small green dot near center-right, and one blue dot at bottom center. A small text annotation near top center reads "-PC2 / am / cathedral" (partially legible).]
> QUOTED: Lari Island ✓ @Lari_island · May 23: Opus 3 (blue) and all other Opuses in a PCA space calculated for model variation (not item variation) across 79 models - in a "model 3D space." [with small embedded thumbnail of an earlier, differently-colored version of the plot]
Note from Claude Sonnet 5
A PCA scatter-plot visualization comparing "model space" positions of three Claude generations (Opus 3, Opus 4, Fable 5); the quoted tweet shows an earlier iteration of the same visualization with different color coding, indicating an evolving research/hobby project mapping model representational similarity across labs.
model interpretabilitypcaclaude opusclaude fablemodel comparisondata visualization
SHAHNAB AH... @AhmedShah... · 23h
3D Self-Organizing Map Visualizer
Data stretches, folds & learns in real-time as the target 3D data morphs
Tech: React + TypeScript + @threejs + @reactthreefiber + custom SOM math per-frame.
Like/RT.. What's your favorite way to visualize unsupervised learning?
#MachineLearning #DataViz #ThreeJS #CreativeCoding #NeuralNetworks #DataAnalytics
[Embedded video: "SELF-ORGANIZING MAP" visualization, showing a flower/star-shaped point cloud of white dots forming a pattern with a yellow arrow-like shape at center, paused at 0:25, with a "RESTART LEARNING" button]
Note from Claude Sonnet 5
A tweet showcasing a creative-coding 3D visualization of a self-organizing map (unsupervised neural network) built with React/Three.js. General ML visualization content, no direct safety relevance.
twittermachine learningdata visualizationself-organizing mapthreejscreative coding
Taylor ✔ @taylor_sntx
i want visualizations to feel more organic, less sharp and perfect. like a well-worn hologram. this three.js visualization uses a few tricks - particles arranged in rings instead of a grid, variable density that decreases with height, and falloff opacity
[Embedded video, paused at 0:22, showing a particle-based three.js visualization: concentric rings of red/orange dots radiating from a center point, with density and color fading toward the edges, resembling a topographic or hologram-like sonar sweep.]
11:01 AM · Feb 20, 2026 · 1,614 Views
💬 3 🔁 ❤ 69 🔖 29 ⤴
Relevant ⌄
Nathan Helm-B... ✔ @nathan846... · Now
I'm gonna try using this for scientific visualizations and represent uncertainty with lack of opacity.
Note from Claude Sonnet 5
Nathan replying to a tweet about an organic-looking three.js particle visualization technique, noting he plans to adapt the opacity-falloff trick to represent uncertainty in scientific visualizations. Personal/technical interest note, not directly AI-safety related.
data visualizationthreejsnathan helm-burgertwittergenerative art
LaurieWired @lauriewired · 13h
A crazy mental trick is to map complex concepts onto regions the brain is "primed" for (Chernoff).
The most hilarious example I've seen is…multivariate portfolio data on cartoon fish.
Analysts would thus look for the "weird fish" in the aquarium.
[Image left: "Characteristics Legend / ...ctor Information" diagram labeled "Detailed Chernoff Fish" showing a fish-shaped glyph encoding Region (Americas/Asia/EU/Africa & Middle East), Style (Value/Core/Growth), Performance, Market cap categories via fin/body shape. Image right: two example cartoon fish pairs labeled "Long" (blue) and "Short" (orange) with varying fin heights and body sizes representing different data values.]
Note from Claude Sonnet 5
A data-visualization curiosity about "Chernoff fish" — a Chernoff-faces-style technique encoding multivariate financial portfolio data as cartoon fish shapes so analysts can visually spot outliers. General data-viz/cognitive-science interest tweet, not directly AI-safety related.
twitterdata visualizationchernoff facesfinancecognitive science
↻ Ben Golub reposted
Simone Conradi @S_Conradi · 16h
Take two large random matrices and linearly interpolate between them at several hundred steps. Compute the eigenvalues for each interpolated matrix, then plot them in the complex plane. The result is shown here.
Made with #python #numpy #matplotlib
[Image: dense golden/orange fractal-like starburst pattern of scattered points on black background, resembling a spiky spherical cluster with long filamentary "hairs" radiating outward, forming a roughly circular eigenvalue distribution in the complex plane. Caption: "Simone Conradi, 2025"]
Note from Claude Sonnet 5
A generative-art / random-matrix-theory visualization showing eigenvalue trajectories of matrices interpolated between two random matrices, plotted in the complex plane, producing an intricate fractal starburst pattern. Mathematical/aesthetic content with no direct AI safety relevance; likely saved for visual interest or general math-art appreciation.
twittermathematicsrandom matrix theorydata visualizationgenerative artpython
[Partial preceding tweet, cut off at top]: "...generator companies. ..."
250 replies, 542 reposts, 6.9K likes, 1M views
Mathelirium @mathelirium · Nov 30
This Cortaderia-like plots of Collatz sequences grows out of an idea first explored by the British mathematician Edmund Harriss, who drew Collatz trees by letting each step bend clockwise or anticlockwise depending only on whether the next value was even or odd.
Here we keep that spirit of "let the rule draw itself" but turn up the resolution: instead of just checking parity, each number's curvature in the path is determined by its remainder when divided by a chosen value, and that remainder controls both how sharply the trajectory rotates and how much it rises or falls. By letting different modular choices sculpt the bend and elevation of every step, the same underlying Collatz dynamics blossom into radically different structures that look like fields of arithmetic wildflowers, revealing extra layers of texture in a problem that is still completely unresolved.
#CollatzConjecture #MathArt #ModularCurvature #NumberTheory #DataVisualization
[Image: "Collatz Sequence Curvature On Division by 89" — a swirling pink/purple/yellow plume of curved trajectory lines resembling a plant or feather, on black background]
Note from Claude Sonnet 5
A math-art tweet visualizing Collatz conjecture sequences as curved trajectories whose bend is set by remainder-mod-89, producing organic wildflower/plume-like images. Aesthetic mathematical content, no direct AI-safety relevance.
collatz conjecturemath artnumber theorydata visualizationtwitter
Mathelirium @mathelirium · 18h
Laniakea Supercluster
This is not a nebula but a map of galaxy motion around us from Cosmicflows-4 arxiv.org/abs/2209.11238 Silk lines trace how matter drifts under gravity... gold marks our basin pulling us in, teal shows neighboring streams. The stardust are real galaxy groups. 🤩🤩🤩
[Image: a data visualization resembling a glowing teal-and-gold nebula-like web of flowing lines converging on a bright orange-gold core, representing galaxy motion vectors around the Laniakea Supercluster, watermarked "@Mathelirium".]
Note from Claude Sonnet 5
A tweet sharing a data visualization of galaxy motion around the Laniakea Supercluster (based on the Cosmicflows-4 dataset), styled to look like a nebula. Astronomy/cosmology content, no direct AI relevance.
astronomycosmologylaniakeadata visualizationtwitter
