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What are Large Language Models (LLM)?

UncategorisedAugust 9, 202482Views0Likes0Comments
Introduction We’ve all asked Alexa to play a song, or Siri to call someone, or ChatGPT to answer our questions. It’s quite fascinating how technology has advanced to a point where it can understand our intent and give us context aware responses. But what exactly is the technology behind all of this? Large Language Models…

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A complete guide for 2024

NanonetsAugust 8, 2024115Views0Likes0Comments
Data annotation is the process of labeling data available in video, text, or images. Labeled datasets are required for supervised machine learning so that machines can clearly understand the input patterns. In autonomous mobility, annotated datasets are essential for training self-driving vehicles to recognize and respond to road conditions, traffic signs, and potential hazards. In…

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AI in Medical Imaging: Balancing Performance and Fairness Across Populations

AI NewsAugust 8, 202482Views0Likes0Comments
As AI models become more integrated into clinical practice, assessing their performance and potential biases towards different demographic groups is crucial. Deep learning has achieved remarkable success in medical imaging tasks, but research shows these models often inherit biases from the data, leading to disparities in performance across various subgroups. For example, chest X-ray classifiers…

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What is Retrieval-Augmented Generation

UncategorisedAugust 7, 202476Views0Likes0Comments
Introduction In the AI space, where technological development is happening at a rapid pace, Retrieval Augmented Generation, or RAG, is a game-changer. But what is RAG, and why does it hold such importance in the present AI and natural language processing (NLP) world? Before answering that question, let's briefly talk about Large Language Models (LLMs).…

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Data annotation tools: A comprehensive overview

UncategorisedAugust 7, 202478Views0Likes0Comments
Data annotation tools are the unsung heroes of AI and machine learning. From self-driving cars to AI-powered healthcare systems, these tools play a crucial role in ensuring the success and accuracy of AI projects. They enable the labeling and categorization of vast data, transforming raw information into high-quality, annotated datasets from which AI and ML…

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