All things AI

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  • Measuring the Inherent Bias in Embedding Models

    Introduction: Understanding Embedding Models and Semantic Spaces Imagine a giant document warehouse where every word, phrase, and sentence has a physical location. In this warehouse, phrases with similar meanings or that are commonly used together are stored close to one another, while words with no relation are placed far apart. This is how embedding models

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  • Ambiguity in User Query for RAG

    Ambiguity in user prompts is one of the more significant challenges for Retrieval-Augmented Generation (RAG) systems striving to deliver precise and actionable responses. For any system with impactful consequences, such as medical diagnostics, financial actions, asset management (e.g. cloud computing), and similar domains, it is crucial to develop strategies that can identify, interpret, and resolve

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  • The Human in the loop

    Large language models (LLMs) can “hallucinate,” generating incorrect information, which poses a considerable risk in high-stakes fields like healthcare or finance. To address this, MIT researchers created SymGen, a system that makes LLM verification faster and more accurate. SymGen allows models to generate responses with precise citations by referencing specific data points, such as cells

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  • First off

    Welcome to my blog on AI, where I explore the latest developments, best practices, and challenges in making artificial intelligence safe, ethical, and aligned with human values. As AI continues to shape industries and influence daily life, ensuring that these systems operate responsibly is essential. This blog is dedicated to unpacking critical aspects of AI

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