@christopher

data and research at @lichess

 Leipzig, Germany
hf.co/christopher
Joined July 2009
  • Tweets1.7K
  • Following213
  • Followers5.2K
248Media
Interesting release by @jure Leskovec's group: RT-J (86M "relational transformer" ) and THE JOIN, a web-crawled corpus of 639 relational databases with 6K forecasting tasks. (data and models on @huggingface)
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- arxiv.org/abs/2610.17867v3 - huggingface.co/datasets/stan… - huggingface.co/stanford-star…
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Can't get Schmidhubered if I Schmidhuber myself.
Stanford NLP Group
@stanfordnlpOct 6
Everyone wants those AI scientists! But how possible is it for an LLM to generate novel research ideas rather than just optimizing hyperparameters (broadly construed)? Building directly on the once novel work of @SchmidhuberAI!
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Christopher Akiki retweeted
Marco🍞
@marco_computersSep 30
🚨 [Token][ization] Paper Alert 🚨 Tokenization is a wildly understudied area of language modeling despite it having effects across all of NLP. Over the past ~8 months, 32 (!) tokenizer researchers put together the most comprehensive survey of the field. Check it out!
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Christopher Akiki retweeted
Maxime Labonne
@maximelabonneSep 21
ChessLFM went full circle and is now on the home page of @lichess Super cool to see, Lichess is where I collected all the seed data. Based on my limited chess skills, I never thought I'd have an article there.
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Love this new slop option on linkedin. They seem to at least be self-aware.
linkedin report message menu: post hidden in feed. You'll Hide posts by Jamie Seems like AI slop (underlined) Report post

ALT linkedin report message menu: post hidden in feed. You'll Hide posts by Jamie Seems like AI slop (underlined) Report post

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Very interesting looking viz fail.
odd looking graph. everything is bundled. colorful edges. black background.

ALT odd looking graph. everything is bundled. colorful edges. black background.

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t-SNE on SigLIP embeddings of 1,360 @OReillyMedia cover animals. The penguin cluster is my favorite.
t-SNE plot of animal engravings.

ALT t-SNE plot of animal engravings.

Christopher Akiki@christopherJul 16
O'Reilly animals sorted by orientation using PCA.
Image quilt of O'Reilly media animals sorted by direction.

ALT Image quilt of O'Reilly media animals sorted by direction.

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O'Reilly animals sorted by orientation using PCA.
Image quilt of O'Reilly media animals sorted by direction.

ALT Image quilt of O'Reilly media animals sorted by direction.

Christopher Akiki@christopherJul 13
Image quilt of all @OReillyMedia book covers sorted by color.
List of all O'Reilly books, sorted by hue.

ALT List of all O'Reilly books, sorted by hue.

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Image quilt of all @OReillyMedia book covers sorted by color.
List of all O'Reilly books, sorted by hue.

ALT List of all O'Reilly books, sorted by hue.

Christopher Akiki@christopherJul 11
An image quilt of all @OReillyMedia animals.
small multiple photo of 1360 oreilly animals

ALT small multiple photo of 1360 oreilly animals

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An image quilt of all @OReillyMedia animals.
small multiple photo of 1360 oreilly animals

ALT small multiple photo of 1360 oreilly animals

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Christopher Akiki retweeted
Ian Johnson 🔬🤖
@enjalotJul 11
single 5090 running parametric umap on 8 million points. getting ready to push to 16 million then 150 million 🌌
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The McManifold (2216 burger recipes as 146-dimensional ingredient vectors)
small multiples umap plots of the burger dataset.

ALT small multiples umap plots of the burger dataset.

Nature Portfolio
@NaturePortfolioJul 3
Using burgers as a model system, a generative AI system rediscovers the classic Big Mac without explicit supervision and generates novel burgers optimized for deliciousness, sustainability, or nutrition, according to a paper in npj Science of Food. go.nature.com/3SU7JDQ
This is figure 2, which shows rediscovering classic burger and discovering delicious burgers.

ALT This is figure 2, which shows rediscovering classic burger and discovering delicious burgers.

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Some fun looking UMAP tomfoolery.
UMAP plot.

ALT UMAP plot.

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4 years ago today, BLOOM finished training.
BigScience Large Model Training@BigScienceLLM28 Jun 2022
▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓ 100%
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10M Bohemian eigenvalues of all 19x19 {-1, 1} companion matrices.
rainbow colormap scatterplot of a fractal structure. Circular, symmetric.

ALT rainbow colormap scatterplot of a fractal structure. Circular, symmetric.

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work in progress: 1 million synthetic personas from @NVIDIAAI's Nemotron-Personas-USA dataset.
scatter plot of 1 million personas from https://huggingface.co/datasets/nvidia/Nemotron-Personas-USA

ALT scatter plot of 1 million personas from https://huggingface.co/datasets/nvidia/Nemotron-Personas-USA

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Been trying to reproduce datashader functionality using only Apache Arrow and Acero as a learning exercise. This is a 1-billion point Clifford attractor rendered in ~8s from a 9GB parquet file. (No JIT)
Clifford attractor

ALT Clifford attractor

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What's everyone using for their CPU-intensive data workflows? Modal? Lambda? Hetzner? Something else?
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