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Active Video Perception Iterative Evidence Seeking for Agentic Long Video Understanding

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AK

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21,321 görüntüleme • 10 ay önce •via X (Twitter)

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Mode Seeking meets Mean Seeking for Fast Long Video Generation paper:
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Mode Seeking meets Mean Seeking for Fast Long Video Generation paper:

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We’re introducing a new capability to our latest Gemini models: agentic video understanding. This allows developers to process long-form video content with more accuracy, while using up to 88% less tokens. See how it works 🧵
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We’re introducing a new capability to our latest Gemini models: agentic video understanding. This allows developers to process long-form video content with more accuracy, while using up to 88% less tokens. See how it works 🧵

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Tired of high token costs for video workflows? Agentic video understanding gives Gemini the tools to dynamically search, scan, and inspect target video segments to achieve its goal. Building on agentic vision, Gemini now actively scans visual frames, audio, and transcripts instead of ingesting video at a static 1 FPS. This reduces token consumption by up to 88%, improves accuracy, and unlocks new ways to process long-form video. Tackle complex video workflows like: ▸ Sub-second retrieval: Catch split-second cuts missed at 1 FPS ▸ Long-form search: Query multi-hour videos without overflowing context ▸ Anomaly detection: Resample interesting windows at higher FPS ▸ Counting: Accurately track repeated actions and objects over time See how agentic video understanding transforms token efficiency in Gemini 3.7 Flash when compared with static video processing:
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Tired of high token costs for video workflows? Agentic video understanding gives Gemini the tools to dynamically search, scan, and inspect target video segments to achieve its goal. Building on agentic vision, Gemini now actively scans visual frames, audio, and transcripts instead of ingesting video at a static 1 FPS. This reduces token consumption by up to 88%, improves accuracy, and unlocks new ways to process long-form video. Tackle complex video workflows like: ▸ Sub-second retrieval: Catch split-second cuts missed at 1 FPS ▸ Long-form search: Query multi-hour videos without overflowing context ▸ Anomaly detection: Resample interesting windows at higher FPS ▸ Counting: Accurately track repeated actions and objects over time See how agentic video understanding transforms token efficiency in Gemini 3.7 Flash when compared with static video processing:

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Agentic video understanding with Gemini 3.7 Flash is HUGE. Just reduced cost, less tokens, and higher accuracy. No biggie.
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Agentic video understanding with Gemini 3.7 Flash is HUGE. Just reduced cost, less tokens, and higher accuracy. No biggie.

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Introducing Long Zhao, a Senior Research Scientist at Google, who worked to build VideoPrism: A Foundational Visual Encoder for Video Understanding. Read the blog to explore innovations in video understanding tasks and more →
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Introducing Long Zhao, a Senior Research Scientist at Google, who worked to build VideoPrism: A Foundational Visual Encoder for Video Understanding. Read the blog to explore innovations in video understanding tasks and more →

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This video is only 40s long . It will change your perception about President William Ruto.
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Excited to share our new blog: Scaling Video Training with Parallelism We discuss how parallelism helps scale long-video training systems, for both understanding and generation.
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Attackers stopped working alone. They coordinate now—through agents. So, we built Project Perception: our new agentic security system. The video explains it better than a caption can.

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We’re launching agentic video understanding across our latest models: Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite! This new capability improves accuracy while cutting token consumption up to 88% and reducing costs by up to 66% for video analysis →
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Video breakdown: CVPR 2026 oral paper Shattering the efficiency bottleneck of long video understanding. Watch as we deconstruct the core innovations behind SpecTemp.
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Video breakdown: CVPR 2026 oral paper Shattering the efficiency bottleneck of long video understanding. Watch as we deconstruct the core innovations behind SpecTemp.

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1. Breaking down + understanding a long video I uploaded the entire NBA dunk contest from last night and asked which dunk had the highest score. Gemini 1.5 was incredibly able to find the specific perfect 50 dunk and details from just its long context video understanding!
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1. Breaking down + understanding a long video I uploaded the entire NBA dunk contest from last night and asked which dunk had the highest score. Gemini 1.5 was incredibly able to find the specific perfect 50 dunk and details from just its long context video understanding!

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Check out this amazing combo using Gemma4 + Falcon Perception for video tracking! 1️⃣Give Gemma 4 video frames 2️⃣It describes what it sees 3️⃣Falcon Perception takes those descriptions, segments the objects, and tracks them across the video! The best part? All running locally!

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Muse Spark 1.1 is here! Available today via API and on Of all the agentic use cases, I’m most excited about this one: going from a single video shot straight to task completion. 🚀 We’ve also polished and launched Computer Use and Video-Audio Perception for Muse Spark 1.1. Read more:
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Muse Spark 1.1 is here! Available today via API and on Of all the agentic use cases, I’m most excited about this one: going from a single video shot straight to task completion. 🚀 We’ve also polished and launched Computer Use and Video-Audio Perception for Muse Spark 1.1. Read more:

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Random thoughts. Questions. How long would it take for y’all to get arrested if they had solid video evidence of your crimes?! 🤔🪓
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Random thoughts. Questions. How long would it take for y’all to get arrested if they had solid video evidence of your crimes?! 🤔🪓

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This complete video will change your perception 👇
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This complete video will change your perception 👇

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