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Flash News List

List of Flash News about diffusion models

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2025-03-31
18:00
UCBerkeley's New Diffusion Model Accelerates Image Generation

According to DeepLearning.AI, Kevin Frans and colleagues at UCBerkeley have introduced a novel method to accelerate image generation using diffusion models. This 'shortcut' approach allows models to take larger noise-removal steps, effectively equivalent to multiple smaller steps, without compromising output quality. This advancement could potentially improve the efficiency of image-based trading analytics by allowing faster data processing and model training. [Source: DeepLearning.AI]

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2025-02-27
05:15
Diffusion Models as an Alternative to Transformers in Text Generation Explored

According to Andrew Ng, a new approach by Stefano Ermon and his team explores diffusion models as an alternative to traditional transformers for text generation. This method generates the entire text simultaneously using a coarse-to-fine process, potentially impacting trading strategies reliant on text analysis by offering more efficient computational methods. The emphasis on non-sequential token generation could lead to faster and more scalable text data processing, which is crucial for high-frequency trading algorithms.

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