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Unlocking Your Data to AI Platform: Generative AI for Multimodal Analytics

Sponsored Content       Traditional data platforms have long excelled at structured queries on tabular data - think “how many units did the West region sell last quarter?” This underlying relational foundation is powerful. But with the growing volume and importance of multimodal data (e.g. images, audio, unstructured text), answering nuanced semantic questions…

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National University of Singapore Researchers Introduce Dimple: A Discrete Diffusion Multimodal Language Model for Efficient and Controllable Text Generation

In recent months, there has been growing interest in applying diffusion models—originally designed for continuous data, such as images—to natural language processing tasks. This has led to the development of Discrete Diffusion Language Models (DLMs), which treat text generation as a denoising process. Unlike traditional autoregressive models, DLMs enable parallel decoding and provide better control…

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Gemini 2.5’s native audio capabilities

Safety and responsibility We’ve proactively assessed potential risks throughout every stage of the development process for these native audio features, using what we’ve learned to inform our mitigation strategies. We validate these measures through rigorous internal and external safety evaluations, including comprehensive red teaming for responsible deployment. Additionally, all audio outputs from our models are…

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Samsung Researchers Introduced ANSE (Active Noise Selection for Generation): A Model-Aware Framework for Improving Text-to-Video Diffusion Models through Attention-Based Uncertainty Estimation

Video generation models have become a core technology for creating dynamic content by transforming text prompts into high-quality video sequences. Diffusion models, in particular, have established themselves as a leading approach for this task. These models work by starting from random noise and iteratively refining it into realistic video frames. Text-to-video (T2V) models extend this…

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This AI Paper Introduces GRIT: A Method for Teaching MLLMs to Reason with Images by Interleaving Text and Visual Grounding

The core idea of Multimodal Large Language Models (MLLMs) is to create models that can combine the richness of visual content with the logic of language. However, despite advances in this field, many models struggle to connect the two domains effectively, leading to limited performance in complex reasoning tasks that involve visual components. A major…

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Gemini as a universal AI assistant

Over the last decade, we’ve laid a lot of the foundations for the modern AI era, from pioneering the Transformer architecture on which all large language models are based, to developing agent systems that can learn and plan like AlphaGo and AlphaZero. We’ve applied these techniques to make breakthroughs in quantum computing, mathematics, life sciences…

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