VGG v GoogleNet: Just how deep can they go?
mayberay.bearblog.dev·22h
📊Embeddings
Guide to Contrastive Learning: Techniques, Models, and Applications
medium.com·16h·
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📊Embeddings
BRILLIANT @GoogleDeepMind research.
threadreaderapp.com·2h
📊Embeddings
Knowledge and data-driven two-layer networking for accurate metabolite annotation in untargeted metabolomics
nature.com·19h
🍄Mycorrhizal Networks
Understanding LLMs: Insights from Mechanistic Interpretability
lesswrong.com·12h
🧠LLM Inference
🌟Introducing Art-0-8B: Reasoning the way you want it to with Adaptive Thinking🌟
huggingface.co·19h·
Discuss: r/LocalLLaMA
🆕New AI
LongCat-Flash, a language model with 560B total parameters, MoE architecture
github.com·3h·
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💾Prompt Caching
From Multi-Head to Latent Attention: The Evolution of Attention Mechanisms
vinithavn.medium.com·23h·
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🧠LLM Inference
An Interview with Julio Barba
halide.cx·22h·
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🗜️Vector Compression
Sheet-Pan Ravioli With Burst Tomatoes
cooking.nytimes.com·19h
🍳Cooking
Computing simplified coverage polygons
volkerkrause.eu·21h·
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🗜️Vector Compression
Ensemble Learning
en.wikipedia.org·13h·
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📊Statistical Ranking
Thermal facial image analyses predict age and metabolic diseases
cell.com·34m·
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📇Vector Indexing
🎲 Atlas: a lace knitting stitch pattern
gannetdesigns.com·7h
🏹Apache Arrow
Tradeoffs of Highly-Expressive Types
jnkr.tech·9h·
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🧩Types
Szoboszlai’s sublime dummy something more than a cog in Liverpool’s red machine | Barney Ronay
theguardian.com·22h
🆕New AI
The Art of Transformer Programming (2023)
yanivle.github.io·7h·
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💻Programming languages
This graphic helped me finally understand what Sequential Consistency means by showing what *isn't* sequentially consistent.
bsky.app·3h·
Discuss: Bluesky
🧵Async
Sheafification - The optimal path to mathematical mastery
sheafification.com·46m·
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🧩Types
Bootstrapping a Forth for Art
tia.mat.br·6h·
Discuss: Lobsters, Hacker News
🪄Prompt Engineering