Remove Knowledge Model Remove Large Language Models Remove LLM
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Anthropic Claude 3.5 Sonnet ranks number 1 for business and finance in S&P AI Benchmarks by Kensho

AWS Machine Learning Blog

Sonnet currently ranks at the top of S&P AI Benchmarks by Kensho , which assesses large language models (LLMs) for finance and business. Although these evaluations are useful in giving LLM users a sense of an LLM’s relative performance, they have limitations. Anthropic Claude 3.5

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Copyright, AI, and Provenance

O'Reilly Media

Another group of cases involving text (typically novels and novelists) argue that using copyrighted texts as part of the training data for a Large Language Model (LLM) is itself copyright infringement, 1 even if the model never reproduces those texts as part of its output. The RAG pattern has other advantages.

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The Hallucination Problem of Large Language Models

Mlearning.ai

Hallucination in the context of language models refers to the generation of text or responses that seem syntactically sound, fluent, and natural but are factually incorrect, nonsensical, or unfaithful to the provided source input. Why do LLMs Hallucinate? How can we Reduce LLM Hallucinations?