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Apple Researchers Introduce FastVLM: Achieving State-of-the-Art Resolution-Latency-Accuracy Trade-off in Vision Language Models

Vision Language Models (VLMs) allow both text inputs and visual understanding. However, image resolution is crucial for VLM performance for processing text and chart-rich data. Increasing image resolution creates significant challenges. First, pretrained vision encoders often struggle with high-resolution images due to inefficient pretraining requirements. Running inference on high-resolution images increases computational costs and latency…

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Deep Think is now rolling out

How Deep Think works: extending Gemini’s parallel “thinking time” Just as people tackle complex problems by taking the time to explore different angles, weigh potential solutions, and refine a final answer, Deep Think pushes the frontier of thinking capabilities by using parallel thinking techniques. This approach lets Gemini generate many ideas at once and consider…

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NVIDIA AI Presents ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning

Estimated reading time: 5 minutes Introduction Embodied AI agents are increasingly being called upon to interpret complex, multimodal instructions and act robustly in dynamic environments. ThinkAct, presented by researchers from Nvidia and National Taiwan University, offers a breakthrough for vision-language-action (VLA) reasoning, introducing reinforced visual latent planning to…

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VLM2Vec-V2: A Unified Computer Vision Framework for Multimodal Embedding Learning Across Images, Videos, and Visual Documents

Embedding models act as bridges between different data modalities by encoding diverse multimodal information into a shared dense representation space. There have been advancements in embedding models in recent years, driven by progress in large foundation models. However, existing multimodal embedding models are trained on datasets such as MMEB and M-BEIR, with most focus only…

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URBAN-SIM: Advancing Autonomous Micromobility with Scalable Urban Simulation

Micromobility solutions—such as delivery robots, mobility scooters, and electric wheelchairs—are rapidly transforming short-distance urban travel. Despite their growing popularity as flexible, eco-friendly transport alternatives, most micromobility devices still rely heavily on human control. This dependence limits operational efficiency and raises safety concerns, especially in complex, crowded city environments filled with dynamic obstacles like pedestrians and…

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How Autonomous Agents Are Quietly Reshaping Supply Chains Aiiot Talk

Supply chains are the lifeblood of global commerce, yet they remain plagued by inefficiencies—delays, stockouts, overproduction, and unpredictable disruptions. Enter autonomous AI agents, the silent orchestrators now optimizing logistics with superhuman precision. Unlike traditional software, these agents learn, adapt, and make decisions in real-time, often without human intervention. “AI agents don’t just follow rules—they rewrite them. In…

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