Experimental News Clipping Site

Tag: tokens

  • Hacker News: Spark-TTS: Text-2-Speech Model Single-Stream Decoupled Tokens [pdf]

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    Kurt Seifried
    in

    Source URL: https://arxiv.org/abs/2503.01710 Source: Hacker News Title: Spark-TTS: Text-2-Speech Model Single-Stream Decoupled Tokens [pdf] Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses Spark-TTS, an innovative LLM-based text-to-speech model that contributes to advancements in zero-shot TTS synthesis. Its efficient design allows for customizable voice generation through a unique token representation and a…

  • Hacker News: Smaller but Better: Unifying Layout Generation with Smaller LLMs

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    Kurt Seifried
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    Source URL: https://arxiv.org/abs/2502.14005 Source: Hacker News Title: Smaller but Better: Unifying Layout Generation with Smaller LLMs Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper presents LGGPT, a large language model designed for unified layout generation, emphasizing its efficiency and performance even with a smaller size compared to larger models. It introduces novel…

  • Simon Willison’s Weblog: State-of-the-art text embedding via the Gemini API

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Mar/7/gemini-embeddings/#atom-everything Source: Simon Willison’s Weblog Title: State-of-the-art text embedding via the Gemini API Feedly Summary: State-of-the-art text embedding via the Gemini API Gemini just released their new text embedding model, with the snappy name gemini-embedding-exp-03-07. It supports 8,000 input tokens – up from 3,000 – and outputs vectors that are a lot larger…

  • Hacker News: Some Thoughts on Autoregressive Models

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    Kurt Seifried
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    Source URL: https://wonderfall.dev/autoregressive/ Source: Hacker News Title: Some Thoughts on Autoregressive Models Feedly Summary: Comments AI Summary and Description: Yes **Summary:** This text offers a comprehensive critique of autoregressive (AR) models, particularly large language models (LLMs), highlighting their strengths and limitations regarding human-like cognition and reasoning. It emphasizes the need for alternative architectures that integrate…

  • 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: SepLLM: Accelerate LLMs by Compressing One Segment into One Separator

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    Kurt Seifried
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    Source URL: https://sepllm.github.io/ Source: Hacker News Title: SepLLM: Accelerate LLMs by Compressing One Segment into One Separator Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses a novel framework called SepLLM designed to enhance the performance of Large Language Models (LLMs) by improving inference speed and computational efficiency. It identifies an innovative…

  • Hacker News: MFA Fatigue: A Growing Headache for Schools

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    Kurt Seifried
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    Source URL: https://healthtechmagazine.net/article/2024/04/mfa-fatigue-growing-headache-healthcare-and-how-combat-it Source: Hacker News Title: MFA Fatigue: A Growing Headache for Schools Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the vulnerability of healthcare workers to cyberattacks, particularly focusing on the challenges posed by multi-factor authentication (MFA) fatigue. It emphasizes the importance of adapting security measures to mitigate risks…

  • 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…