Does your system for naming colors always feel like it falls short? This two-layer approach solves so many problems!
color-space — every color space, one tiny API, verified
An open collection of color spaces. Convert any space to any other with conventional ranges and independently anchored formulas.
Color Hunt - Color Palettes for Designers and Artists
Discover the newest hand-picked color palettes of Color Hunt. Get color inspiration for your design and art projects.
Too Much Color
I spent too much time looking at too many colo(u)rs to try and optimise them for csskit. Here are some interesting findings.
Single-pass palette refinement and ordered dithering
Usually image color reduction is done in two independent phases: first a color quantization algorithm finds a palette, which is then used by a pixel mapping phase to assign every output pixel a color from the palette. Ignoring any possible dithering for now, the chosen palette color is the one with the shortest Euclidean distance to the original pixel color. But if we know both the old and new colors for each pixel, it’s possible to refine the palette.
Flat UI Colors 2 - 14 Color Palettes, 280 colors 🎨
280 handpicked colors ready for COPY & PASTE
Deficient executive control in transformer attention
Abstract Although transformers in large language models (LLMs) effectively implement a self-attention mechanism that has revolutionized natural language processing, they lack an explicit architecture for the executive control of attention found in humans, which is essential for resolving conflicts and selecting relevant information in the presence of competing computations and is critical for adaptive behavior. To investigate the impact of this limitation in LLMs, we employed the classic color Stroop task, widely regarded as the gold standard, to test the executive control of attention in these models. Our results revealed a typical conflict effect of underperformance in terms of accuracy in the incongruent condition (e.g. naming the color of the word RED in blue) compared with the congruent condition (e.g. naming the color of the word RED in red), in short word lists, similar to human performance. However, as the length of the word lists increased, performance on the incongruent condition degraded toward near-total performance collapse, even as accuracy in the congruent condition remained excellent, and word reading (e.g. reading the word RED [in red] or RED [in blue], ignoring the color) was near-perfect. These findings demonstrate that transformer attention mechanisms are fundamentally limited in their capacity for conflict resolution across extended contexts, and a failure to up-regulate control adaptively under rising interference. We suggest that incorporating executive control mechanisms akin to those in biological attention is crucial for achieving artificial general intelligence.
What's My JND?
Find your Just Noticeable Difference in colour perception. How small a colour difference can you actually see?
Pet name system · Issue #12 · subconsciousnetwork/noosphere
Our plan at this time is to implement a generalized pet name system that enables users to write human-readable names instead of DIDs when addressing other spheres. This is the tracking issue that c...
loukesio/ltc-color-palettes
"ltc_palettes: Tailored for data visualization enthusiasts, ltc_palettes is an R package that offers a curated collection of color palettes. Crafted to enhance clarity and impact, these palettes ensure that your visual representations not only communicate data effectively but also aesthetically
Lovely Set of #rstats color pallets: ltc-color-palettes
