Models with billions, or trillions, of parameters are becoming the norm. These models can write essays, generate code, as well as create art. But they can still get stuck on a logic puzzle like ...
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Deploying ML on Arduino: From Blink to Think
Last week, Qualcomm made waves in the maker community by acquiring Arduino. At the event "From Blink to Think" the all new Arduino Uno Q was unveilled. A board that promises linux powered ML on ...
VideoRAG: Redefining Long-Context Video Comprehension
VideoRAG, or Retrieval-Augmented Generation for Extreme Long-Context Videos, is a novel framework designed to enable large language models to comprehend multi-hour video content efficiently. ...
AI Agent in Action: Automating Desktop Tasks with VLMs
AI Agents are usually API-bound workflows, designed to execute specific tasks with minimal human intervention. But when it comes to generic, open-ended automation, we’re still in the very early days. ...
The Ultimate Guide To VLM Evaluation Metrics, Datasets, And Benchmarks
Vision-Language Models (VLMs) are powerful and figuring out how well they actually work is a real challenge. There isn’t one single test that covers everything they can do. Instead, we need to use the ...
Getting Started with VLM on Jetson Nano
Tiny Vision Language Models (VLMs) are rapidly transforming the AI landscape. Almost every week, new VLMs with smaller footprints are being released. These models are finding applications across ...
