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      Kore.ai Technical Blog

      One-stop for everything related to AI-first
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      Random Chain-Of-Thought For LLMs, Distilling Self-Evaluation Capability

      Here I discuss the five emerging architectural principles for LLM implementations & how curation & enrichment of...

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      What Is Multi-Task Language Understanding or MMLU?

      With one of the Google LLM launches, Gemini Ultra was shown as having exceeded human expert level using the MMLU...

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      Large Language Model Programs

      A study named Large Language Model Programs explores how LLMs can be implemented in applications.

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      Data Delivery To Large Language Models

      It has been said that every AI strategy should start with a data strategy. The Data Strategy should consist of four...

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      Generative AI Trends to Watch in 2025 & Beyond

      We are six weeks into 2025, and already a number of developments have taken the world by storm. In article I build on...

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      As-Needed Decomposition & Planning Using Large Language Models — ADaPT

      There has been a shift with regard to LLM implementations to decompose tasks and solve each step in an interactive...

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      Self-Consistency For Chain-Of-Thought Prompting

      The paper on Self-Consistency Prompting was published 7 March 2023, as an improvement on Chain-Of-Thought Prompting. At...

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      The Anatomy Of Chain-Of-Thought Prompting (CoT)

      The research on Chain-Of-Thought Prompting (CoT) was published on 10 Jan 2023, and since then, there has been a...

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      Contrastive Chain-Of-Thought Prompting

      Contrastive Chain-of-Thought Prompting (CCoT) uses both positive & negative demonstrations to improve LLM reasoning.

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      OpenAI Structured JSON Output With Adherence

      In the past, when using OpenAI’s JSON mode there was no guarantee that the model output will match the specified and...

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