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Interactive tools are invaluable in machine learning (ML) projects, especially when demonstrating model capabilities and gathering feedback. A sketchpad is an excellent example of such a tool, allowing users to draw and interact with models in real time. Gradio, an open-source library for building user interfaces for machine learning models, simplifies the creation of such tools.
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Large Language Models like GPT-4 may feel intelligent—but how do they actually “think”? Spoiler: it’s not magic. It’s math, probabilities, and some clever mechanisms under the hood.
Published:
Interactive tools are invaluable in machine learning (ML) projects, especially when demonstrating model capabilities and gathering feedback. A sketchpad is an excellent example of such a tool, allowing users to draw and interact with models in real time. Gradio, an open-source library for building user interfaces for machine learning models, simplifies the creation of such tools.
Published:
Large Language Models like GPT-4 may feel intelligent—but how do they actually “think”? Spoiler: it’s not magic. It’s math, probabilities, and some clever mechanisms under the hood.
Published:
Understanding why deep learning models make certain predictions has become just as important as achieving high accuracy. As Computer Vision systems continue to influence decisions in healthcare, autonomous driving, security, and edge AI, the demand for transparency has never been greater. Yet, modern architectures like ResNet18—designed for depth, abstraction, and performance—often operate as opaque black boxes.
Published:
Understanding why deep learning models make certain predictions has become just as important as achieving high accuracy. As Computer Vision systems continue to influence decisions in healthcare, autonomous driving, security, and edge AI, the demand for transparency has never been greater. Yet, modern architectures like ResNet18—designed for depth, abstraction, and performance—often operate as opaque black boxes.
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Text generation is one of the most exciting applications of modern Large Language Models (LLMs), enabling tasks like content creation, code assistance, summarization, and conversational AI. With the rise of efficient open-weights models, developers can now experiment with advanced text-generation systems directly on their own hardware.
Published:
Text generation is one of the most exciting applications of modern Large Language Models (LLMs), enabling tasks like content creation, code assistance, summarization, and conversational AI. With the rise of efficient open-weights models, developers can now experiment with advanced text-generation systems directly on their own hardware.
Published:
Understanding why deep learning models make certain predictions has become just as important as achieving high accuracy. As Computer Vision systems continue to influence decisions in healthcare, autonomous driving, security, and edge AI, the demand for transparency has never been greater. Yet, modern architectures like ResNet18—designed for depth, abstraction, and performance—often operate as opaque black boxes.
Published:
Understanding why deep learning models make certain predictions has become just as important as achieving high accuracy. As Computer Vision systems continue to influence decisions in healthcare, autonomous driving, security, and edge AI, the demand for transparency has never been greater. Yet, modern architectures like ResNet18—designed for depth, abstraction, and performance—often operate as opaque black boxes.