Tag: computational efficiency

  • Hacker News: Fine-Tuning LLMs: A Review of Technologies, Research, Best Practices, Challenges

    Source URL: https://arxiv.org/abs/2408.13296 Source: Hacker News Title: Fine-Tuning LLMs: A Review of Technologies, Research, Best Practices, Challenges Feedly Summary: Comments AI Summary and Description: Yes Summary: This guide extensively covers the fine-tuning of Large Language Models (LLMs), detailing methodologies, techniques, and practical applications. Its relevance to AI and LLM security professionals is underscored by discussions…

  • Simon Willison’s Weblog: lm.rs: run inference on Language Models locally on the CPU with Rust

    Source URL: https://simonwillison.net/2024/Oct/11/lmrs/ Source: Simon Willison’s Weblog Title: lm.rs: run inference on Language Models locally on the CPU with Rust Feedly Summary: lm.rs: run inference on Language Models locally on the CPU with Rust Impressive new LLM inference implementation in Rust by Samuel Vitorino. I tried it just now on an M2 Mac with 64GB…

  • Hacker News: Addition Is All You Need for Energy-Efficient Language Models

    Source URL: https://arxiv.org/abs/2410.00907 Source: Hacker News Title: Addition Is All You Need for Energy-Efficient Language Models Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper presents a novel approach to reducing energy consumption in large language models by using an innovative algorithm called L-Mul, which approximates floating-point multiplication through integer addition. This method…

  • Slashdot: Researchers Claim New Technique Slashes AI Energy Use By 95%

    Source URL: https://science.slashdot.org/story/24/10/08/2035247/researchers-claim-new-technique-slashes-ai-energy-use-by-95?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Researchers Claim New Technique Slashes AI Energy Use By 95% Feedly Summary: AI Summary and Description: Yes Summary: Researchers at BitEnergy AI, Inc. have introduced Linear-Complexity Multiplication (L-Mul), a novel technique that reduces AI model power consumption by up to 95% by replacing floating-point multiplications with integer additions. This…

  • Hacker News: Alternatives to cosine similarity

    Source URL: https://tomhazledine.com/cosine-similarity-alternatives/ Source: Hacker News Title: Alternatives to cosine similarity Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses various methods for comparing vectors, particularly in the context of LLM embeddings, emphasizing the utility of cosine similarity over alternative distance functions like Euclidean and Manhattan distances. It underscores the significance of…

  • Hacker News: Matrix Multiplication in Finite Fields

    Source URL: https://fileforma.substack.com/p/update-ffgemm-finite-field-general Source: Hacker News Title: Matrix Multiplication in Finite Fields Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses Fileforma, a laboratory focused on researching custom binary formats for AI, particularly alternatives to traditional floating-point formats. The introduction of the ffGEMM library highlights the importance of finite fields in fast…

  • Hacker News: Baiting the Bots

    Source URL: https://conspirator0.substack.com/p/baiting-the-bot Source: Hacker News Title: Baiting the Bots Feedly Summary: Comments AI Summary and Description: Yes Summary: The text analyzes the behavior of various chatbots based on large language models (LLMs) like Llama 3.1 in response to simpler, nonsensical bots. It reveals key insights into human-like engagement and computational efficiency in AI-based conversations,…

  • Hacker News: How does cosine similarity work?

    Source URL: https://tomhazledine.com/cosine-similarity/ Source: Hacker News Title: How does cosine similarity work? Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides an in-depth exploration of cosine similarity in the context of comparing large language model (LLM) embeddings. It discusses the mathematical principles behind cosine similarity, its significance in measuring vector similarity, and…

  • Hacker News: Self-Supervised Learning for Videos

    Source URL: https://www.lightly.ai/post/self-supervised-learning-for-videos Source: Hacker News Title: Self-Supervised Learning for Videos Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses advancements in self-supervised learning techniques specifically focusing on video data, highlighting architectures such as VideoMAE and its follow-ups, which address the unique challenges intrinsic to video – namely, temporal redundancy and correlation.…