I'm looking for 5-10 #chess players to test out a tool I'm building. Preferably who play on @lichess.org and are 1200+ in rapid or blitz.
And if you coach chess at all, I'd be extra grateful to have you test it!
NOTE: it is _NOT_ an "LLM chess coach" tool, I promise!
🙏
Ah very cool! Any chance you can share the code for that?
This absolutely phenomenal. What framework did you use for the frontend? cc @lelandmcinnes.bsky.social
Any chess position with 8 pieces on the board and at least one pair of opposed pawns has been solved! Lichess can now tell you definitively if it's a win, loss or draw with no engine required. Read about the massive technological undertaking to accomplish this partial 8 piece tablebase on our blog:
github.com/cakiki/chess...
In case you want to play with the files, I made this kaitai parser for the op1 format.
Looking forward to your course on there!
They're parameter sweeps of the UMAP algorithm, varying the number of neighbors (rows) and the spread of the data (columns).
3 by 3 grid of networks color-mapped with "plasma" and with edge-bundling. Lung looking structure.
UMAP connectivity plots of 3,627 chess openings from the @lichess.org datasets (huggingface.co/datasets/Lic...)
I think you'll appreciate it's actually chess opening positions from @lichess.org : huggingface.co/datasets/Lic...
3 by 3 grid of the same plot in different colormaps. Plot is an edge-bundled connectivity graph. Color maps are, left-to-right and top-to-bottom: viridis, plasma, inferno, magma, cividis, binary, copper, coolwarm, managua.
Which colormap do you think looks the nicest? I'm leaning toward plasma.
I'm not 100% sure if DBLP (dblp.org) indexes non-English venues, but the plot itself is only authors, not papers.
Organic looking scatterplot. Blob in the bottom left. Hedgehog looking.
Organic looking scatterplot. Sort of looks like Romanesco broccoli.
Scatterplot of 4 million computer science authors, laid out according to co-authorship connections. Large blob in the bottom left are all single authors; removing them lets the plot breathe more somehow.
The source of the data is the @dblp.org bibliography.
Who is winning the open AI race?
Our new study Economies of Open Intelligence maps @hf.co 851k models' downloads 2020→2025.
1) Power rebalance: US tech ↓; China + community ↑
2) Models size & efficient ↑ (MoE, quant, multimodal)
3) Intermediary layers ↑ (adapters/quantizers)
4) Transparency ↓
/🧵
Researchers at Google DeepMind used our free puzzle database and reinforcement learning to train a model to generate creative chess puzzles.
➡️ Read more on this by Tom Zahavy from the DeepMind discovery team: lichess.org/@/tomas135/b...
![Three scatterplots of colorful points.
titles = ['Color Space', 'Text Space', 'Image Space']
subtitles = ['Embeddings of color features', 'Text embedding of color names', 'Image embeddings of color swatches']](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:s62ilc26irrbo2dndmdzboqi/bafkreieocq6xfp5xzela4ge3f4nidi4krh7ufkxftg423pjwmipz53zmpm)
Three scatterplots of colorful points. titles = ['Color Space', 'Text Space', 'Image Space'] subtitles = ['Embeddings of color features', 'Text embedding of color names', 'Image embeddings of color swatches']
Three different ways to represent colo(u)r. Work in progress, inspired by an old post by Kat Zhang / The Poet Engineer.
- Dataset: huggingface.co/datasets/Hug...
- Embeddings: huggingface.co/datasets/air... (H/T @loubnabnl.hf.co for recommending this)
- Sasha's talk: ted.com/talks/sasha_...
- Tools: datamapplot and EVōC by @lelandmcinnes.bsky.social and colleagues at the Tutte Institute and openTSNE by @pavlinpolicar.bsky.social
Scatterplot of a document corpus with cluster information in the form of colors and cluster labels. Includes labels like computing, mental health, religion, etc.
I made this annotated scatter plot of 1 million FineWeb-Edu documents for @sashamtl.bsky.social's new TED talk.
A four frame comic about the Cambodian genocide. In the first frame, a man can be seen from the back, looking at a window. The text reads: "I never ask my father about Cambodia." In the second frame, a silhouette of the father can be seen, screaming in his sleep, arms reaching into nothingness. The text reads: "What could he say, really, that he didn't already scream in his nightmares?". The third frame shows the father pondering on something, expression neutral. The text reads: But sometimes he would say "It's funny, when it happened, all the fish left the river. They never came back." . The fourth frame shows the father lowering his head, thinking. He says: "I guess they knew."
The second page of the comic on the Cambodian genocide, and everything to come. The first frame shows the daughter, young, silent and unsure of what to say. The text reads: "I didn't say anything then." In the present, the daughter, now an adult, looks at the Seine in Paris. The text reads "But I often think of it now.". The daughter then crouches near the Seine to see if there are any fish left. She says: "Are you still here?".
When the fish left the river:
Also really love how organic the plot looks with "inferno" (left) and "viridis" (right).
Update: the color map in this post is misleading. See the quoted post for context.
bsky.app/profile/caki...
Thanks to @jamesabednar.bsky.social I realized I had used the wrong background color for the colormap I had chosen. This is another version of the plot (different embeddings) with the corrected background.
Glad you like it! Nothing yet, only a very messy jupyter notebook for now. I will share the code and data pipelines once they're all cleaned up.
Huge props to @lelandmcinnes.bsky.social for optimizing the hammer bundling code in datashader and to Barrett Lyon's inspring work at the Opte Project.
organic looking graph of the BGP nodes of the internet. black and white
Map of the internet: 1.3M nodes (BGP)
"Allô maman bobo" is another poignant classic. www.youtube.com/watch?v=AgdU...
Photo of three hard disk drives.
We're cooking.. 👀
very colorful scatterplot of player deaths in mario maker levels. "inferno" colormap. some level elements highlighted.
526.9 million player deaths in 24.7 million levels of Super Mario Maker 2. Data by @tgr.bsky.social
