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Enhancing Autoregressive Decoding Efficiency: A Machine Learning Approach by Qualcomm AI Research Using Hybrid Large and Small Language Models

Marktechpost

Central to Natural Language Processing (NLP) advancements are large language models (LLMs), which have set new benchmarks for what machines can achieve in understanding and generating human language. One of the primary challenges in NLP is the computational demand for autoregressive decoding in LLMs.

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AI News Weekly - Issue #383: New York Daily News, Chicago Tribune, and others sue OpenAI and Microsoft - May 2nd 2024

AI Weekly

In the News Coalition of news publishers sue Microsoft and OpenAI A coalition of major news publishers has filed a lawsuit against Microsoft and OpenAI, accusing the tech giants of unlawfully using copyrighted articles to train their generative AI models without permission or payment. Planning a GenAI or LLM project? techmonitor.ai

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Meet EAGLE: A New Machine Learning Method for Fast LLM Decoding based on Compression

Marktechpost

Large Language Models (LLMs) like ChatGPT have revolutionized natural language processing, showcasing their prowess in various language-related tasks. However, these models grapple with a critical issue – the auto-regressive decoding process, wherein each token requires a full forward pass.

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This AI Paper from UCLA Introduces ‘SPIN’ (Self-Play fIne-tuNing): A Machine Learning Method to Convert a Weak LLM to a Strong LLM by Unleashing the Full Power of Human-Annotated Data

Marktechpost

Large Language Models (LLMs) have ushered a new era in the field of Artificial Intelligence (AI) through their exceptional natural language processing capabilities. From mathematical reasoning to code generation and even drafting legal opinions, LLMs find their applications in almost every field.

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A New AI Research Introduces Directional Stimulus Prompting (DSP): A New Prompting Framework to Better Guide the LLM in Generating the Desired Summary

Marktechpost

Natural language processing (NLP) has seen a paradigm shift in recent years, with the advent of Large Language Models (LLMs) that outperform formerly relatively tiny Language Models (LMs) like GPT-2 and T5 Raffel et al. RL offers a natural solution to bridge the gap between the optimized object (e.g.,

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A New AI Research Introduces Recognize Anything Model (RAM): A Robust Base Model For Image Tagging

Flipboard

When it comes to natural language processing (NLP) tasks, large language models (LLM) trained on massive online datasets perform exceptionally well. …

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Meta AI Research Introduces MobileLLM: Pioneering Machine Learning Innovations for Enhanced On-Device Intelligence

Marktechpost

Empirical evidence from the research highlights the superiority of MobileLLM over existing models within the same parameter constraints. Demonstrating notable improvements in accuracy across a breadth of benchmarks, MobileLLM sets a new standard for on-device LLM deployment. If you like our work, you will love our newsletter.