A New Artificial Intelligence (AI) Research Approach Presents Prompt-Based In-Context Learning As An Algorithm Learning Problem From A Statistical Perspective

In-context learning is a recent paradigm where a large language model (LLM) observes a test instance and a few training examples as its input and directly decodes the output without any update to its parameters. This implicit training contrasts with the usual training where the weights are changed based on the examples.  Here comes the…

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Meet LOMO (LOw-Memory Optimization): A New AI Optimizer that Fuses the Gradient Computation and the Parameter Update in One Step to Reduce Memory Usage

Large Language Models have transformed Natural Language Processing by showcasing amazing skills like emergence and grokking and driving model size to increase continually. The bar for NLP research is raised by training these models with billions of parameters, such as those with 30B to 175B parameters. It is challenging for small labs and businesses to…

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AI Researchers from Bytedance and the King Abdullah University of Science and Technology Present a Novel Framework For Animating Hair Blowing in Still Portrait Photos

  Hair is one of the most remarkable features of the human body, impressing with its dynamic qualities that bring scenes to life. Studies have consistently demonstrated that dynamic elements have a stronger appeal and fascination than static images. Social media platforms like TikTok and Instagram witness the daily sharing of vast portrait photos as…

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