Experimental News Clipping Site

Tag: attention mechanism

  • Simon Willison’s Weblog: AbsenceBench: Language Models Can’t Tell What’s Missing

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Jun/20/absencebench/#atom-everything Source: Simon Willison’s Weblog Title: AbsenceBench: Language Models Can’t Tell What’s Missing Feedly Summary: AbsenceBench: Language Models Can’t Tell What’s Missing Here’s another interesting result to file under the “jagged frontier" of LLMs, where their strengths and weaknesses are often unintuitive. Long context models have been getting increasingly good at passing "Needle…

  • Hacker News: Simple Explanation of LLMs

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    Kurt Seifried
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    Source URL: https://blog.oedemis.io/understanding-llms-a-simple-guide-to-large-language-models Source: Hacker News Title: Simple Explanation of LLMs Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text provides a comprehensive overview of Large Language Models (LLMs), highlighting their rapid adoption in AI, the foundational concepts behind their architecture, such as attention mechanisms and tokenization, and their implications for various fields.…

  • Hacker News: Writing an LLM from scratch, part 8 – trainable self-attention

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    Kurt Seifried
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    Source URL: https://www.gilesthomas.com/2025/03/llm-from-scratch-8-trainable-self-attention Source: Hacker News Title: Writing an LLM from scratch, part 8 – trainable self-attention Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text provides an in-depth exploration of implementing self-attention mechanisms in large language models (LLMs), focusing on the mathematical operations and concepts involved. This detailed explanation serves as a…

  • Hacker News: Go-attention: A full attention mechanism and transformer in pure Go

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    Kurt Seifried
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    Source URL: https://github.com/takara-ai/go-attention Source: Hacker News Title: Go-attention: A full attention mechanism and transformer in pure Go Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text presents a pure Go implementation of attention mechanisms and transformer layers by takara.ai. This implementation emphasizes high performance and usability, making it valuable for applications in AI,…

  • Hacker News: 3x Improvement with Infinite Retrieval: Attention Enhanced LLMs in Long-Context

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    Kurt Seifried
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    Source URL: https://arxiv.org/abs/2502.12962 Source: Hacker News Title: 3x Improvement with Infinite Retrieval: Attention Enhanced LLMs in Long-Context Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses a novel approach called InfiniRetri, which enhances long-context processing capabilities of Large Language Models (LLMs) by utilizing their own attention mechanisms for improved retrieval accuracy. This…

  • Hacker News: DeepDive in everything of Llama3: revealing detailed insights and implementation

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    Kurt Seifried
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    Source URL: https://github.com/therealoliver/Deepdive-llama3-from-scratch Source: Hacker News Title: DeepDive in everything of Llama3: revealing detailed insights and implementation Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text details an in-depth exploration of implementing the Llama3 model from the ground up, focusing on structural optimizations, attention mechanisms, and how updates to model architecture enhance understanding…

  • Cloud Blog: Optimizing image generation pipelines on Google Cloud: A practical guide

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/guide-to-optimizing-image-generation-pipelines/ Source: Cloud Blog Title: Optimizing image generation pipelines on Google Cloud: A practical guide Feedly Summary: Generative AI diffusion models such as Stable Diffusion and Flux produce stunning visuals, empowering creators across various verticals with impressive image generation capabilities. However, generating high-quality images through sophisticated pipelines can be computationally demanding, even with…

  • Hacker News: Implementing LLaMA3 in 100 Lines of Pure Jax

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    Kurt Seifried
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    Source URL: https://saurabhalone.com/blogs/llama3/web Source: Hacker News Title: Implementing LLaMA3 in 100 Lines of Pure Jax Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides a comprehensive tutorial on implementing the LLaMA 3 language model using JAX, emphasizing its functional programming nature and its suitability for educational purposes. This tutorial is particularly relevant…

  • Hacker News: Why LLMs still suck at OCR

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    Kurt Seifried
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    Source URL: https://www.runpulse.com/blog/why-llms-suck-at-ocr Source: Hacker News Title: Why LLMs still suck at OCR Feedly Summary: Comments AI Summary and Description: Yes Summary: The text explores the challenges faced when using Large Language Models (LLMs) for tasks like Optical Character Recognition (OCR) and complex data extraction, emphasizing their limitations in processing intricate document layouts and the…

  • Hacker News: A minimal PyTorch implementation for training your own small LLM from scratch

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    Kurt Seifried
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    Source URL: https://github.com/Om-Alve/smolGPT Source: Hacker News Title: A minimal PyTorch implementation for training your own small LLM from scratch Feedly Summary: Comments AI Summary and Description: Yes **Summary:** This text describes a minimal PyTorch implementation for training a small Language Model (LLM) from scratch, intended primarily for educational purposes. It showcases modern techniques in LLM…