Tag: tokenization

  • Hacker News: Simple Explanation of LLMs

    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: DeepDive in everything of Llama3: revealing detailed insights and implementation

    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…

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

    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…

  • Simon Willison’s Weblog: Anomalous Tokens in DeepSeek-V3 and r1

    Source URL: https://simonwillison.net/2025/Jan/26/anomalous-tokens-in-deepseek-v3-and-r1/#atom-everything Source: Simon Willison’s Weblog Title: Anomalous Tokens in DeepSeek-V3 and r1 Feedly Summary: Anomalous Tokens in DeepSeek-V3 and r1 Glitch tokens (previously) are tokens or strings that trigger strange behavior in LLMs, hinting at oddities in their tokenizers or model weights. Here’s a fun exploration of them across DeepSeek v3 and R1.…

  • Cloud Blog: Cloud CISO Perspectives: Talk cyber in business terms to win allies

    Source URL: https://cloud.google.com/blog/products/identity-security/cloud-ciso-perspectives-talk-cyber-in-business-terms-to-win-allies/ Source: Cloud Blog Title: Cloud CISO Perspectives: Talk cyber in business terms to win allies Feedly Summary: Welcome to the first Cloud CISO Perspectives for January 2025. We’re starting off the year at the top with boards of directors, and how talking about cybersecurity in business terms can help us better convey…

  • Cloud Blog: Get started with Google Cloud’s built-in tokenization for sensitive data protection

    Source URL: https://cloud.google.com/blog/products/identity-security/get-started-with-built-in-tokenization-for-sensitive-data-protection/ Source: Cloud Blog Title: Get started with Google Cloud’s built-in tokenization for sensitive data protection Feedly Summary: In many industries including finance and healthcare, sensitive data such as payment card numbers and government identification numbers need to be secured before they can be used and shared. A common approach is applying tokenization…

  • Hacker News: A16Z 2025 Big Ideas for Crypto

    Source URL: https://a16zcrypto.com/posts/article/big-ideas-crypto-2025/ Source: Hacker News Title: A16Z 2025 Big Ideas for Crypto Feedly Summary: Comments AI Summary and Description: Yes Summary: The text outlines emerging trends in AI, crypto, and governance that may shape the technology landscape in 2025. It highlights the transition of AIs into agentic roles, the necessity of unique digital identities,…

  • Hacker News: Cascading retrieval: Unifying dense and sparse vector embeddings with reranking

    Source URL: https://www.pinecone.io/blog/cascading-retrieval/ Source: Hacker News Title: Cascading retrieval: Unifying dense and sparse vector embeddings with reranking Feedly Summary: Comments AI Summary and Description: Yes Summary: Pinecone has introduced new cascading retrieval capabilities for AI search applications, enhancing the integration of dense and sparse retrieval systems. These advancements, which reportedly improve performance by up to…

  • Hacker News: Don’t Look Twice: Faster Video Transformers with Run-Length Tokenization

    Source URL: https://rccchoudhury.github.io/rlt/ Source: Hacker News Title: Don’t Look Twice: Faster Video Transformers with Run-Length Tokenization Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents a novel approach called Run-Length Tokenization (RLT) aimed at optimizing video transformers by eliminating redundant tokens. This content-aware method results in substantial speed improvements for training and…