In the world of machine learning and artificial intelligence (AI), data is considered to be the most important asset. However, that data needs to be annotated, i.e. tagged with labels and categories, to make it more useful for machine learning and AI applications. For every machine-learning and AI model, the performance and accuracy depend on […]
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In the ever-evolving world of artificial intelligence (AI), there’s one concept that stands out for its precision and transformative potential: semantic segmentation. This sophisticated method allows AI to interpret and analyze images at a pixel level, enabling machines to “see” the world with human-like understanding. From autonomous vehicles navigating busy streets to healthcare systems detecting
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High-quality data, in today’s world of Artificial Intelligence and Machine Learning, drives the latter toward success. When it is data marking with marks that go upon text, audio, video, and images to allow computers to “learn” them and subsequently start making decisions regarding the subject data, that comes under the header of Data Annotated. Annotating
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AI chatbots are an integral part of our lives today. Considering how rapidly the world of artificial intelligence is evolving, these tools can be used to answer questions and generate content to help with coding and research. Of the numerous AI chatbots now available to stand out in prominence, DeepSeek and ChatGPT. It was a
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In the world of machine learning and artificial intelligence (AI), data is considered to be the most important asset. However, that data needs to be annotated, i.e. tagged with labels and categories, to make it more useful for machine learning and AI applications. For every machine-learning model, the performance and accuracy depend on the quality
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Machine Learning (ML) is an exciting world where algorithms learn to identify patterns and solve complex problems, from recommending your next favorite movie to diagnosing diseases. However, getting these models to perform at their best is no walk in the park. It is at the core of modern technological advancements, driving innovations in industries ranging
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The way we use technology has been completely transformed by artificial intelligence (AI), which is propelling progress across many fields. Large Language Models (LLMs), Machine Learning (ML), And Generative AI are examples of specialized subsets of artificial intelligence that address various facets of creativity and intellect. Although AI is the general term, ML drives the
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Large language models (LLMs) have shaken up the world of natural language processing (NLP). These AI models are remarkably good at understanding, generating or manipulating human language. They produce texts that resemble those of humans, respond to inquiries and give useful information. However, what happens when for a very particular purpose, you require something like
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A large language model (or LLM) is an artificial intelligence (AI) program that can recognize and generate texts and perform various other tasks. In other words, it is a computer program that can understand and generate human language. LLMs are based on machine learning called deep learning, i.e. they deal with large amounts of unstructured
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In the evolving world of artificial intelligence (AI), you must have heard of these two terms: RAG and fine-tuning LLM. Both of these work on how large language models (LLMs) are operated and improved. They work in different ways to fulfill different purposes, with the help of different types of methods. Let’s see how these
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