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A Guide to Mastering Large Language Models

Unite.AI

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. From chatbots to search engines to creative writing aids, LLMs are powering cutting-edge applications across industries. Retrieval augments LLMs by allowing huge external context.

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ODSC West Recap, Slides, and Minisodes Podcast, Open-Source Data Catalogs, and Limitations of LLMs

ODSC - Open Data Science

Understanding the Core Limitations of Large Language Models: Insights from Gary Marcus Gary Marcus, a leading voice and critic of AI, shared his thoughts in a recent podcast, where he explored LLMs’ limitations, the need for hybrid AI approaches, and more.

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Evaluation Derangement Syndrome (EDS) in the GPU-poor’s GenAI. Part 1: the case for Evaluation-Driven Development

deepsense.ai

Even though the team we established consisted of elite LLM experts, the task proved very challenging. 2023 Witscript 3: A hybrid AI system for improvising jokes in a conversation , Toplyn J., 2004 BLEURT: Learning robust metrics for text generation , Sellam T., Galstyan A. Cresswell J.C., Hosseinzadeh R. Kotelnikova A.,

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Understanding the Core Limitations of Large Language Models: Insights from Gary Marcus

ODSC - Open Data Science

Marcus’s views provide a deep dive into why LLMs, despite their breakthroughs, are not suited for tasks requiring complex reasoning and abstraction. This blog explores Marcus’s insights, addressing LLMs’ inherent limitations, the need for hybrid AI approaches, and the societal implications of current AI practices.