Computer vision

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NVIDIA’s Cosmos-Framework Tutorial: Designing a Colab-Friendly Miniature of Cosmos 3 World Models with Omnimodal Mixture-of-Transformers

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer vision, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we explore NVIDIA’s cosmos-framework from a practical Colab-friendly angle while staying honest about the hardware limits of running real Cosmos 3 checkpoints. We begin by checking the current runtime, GPU capabilities, CUDA availability, memory, and disk space to understand why full Cosmos 3 inference is not realistic on standard Colab hardware. Instead […]

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Modern VLMs Explained: How GPT-4o, Gemini, Claude Vision, and Qwen-VL Work 

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer vision, LLMs

Vision Language Models, or VLMs, are AI models that can understand both visual content and language. While earlier models like CLIP and BLIP connected images with text, modern VLMs can analyze images, read documents, interpret charts, answer visual questions, and support multimodal conversations. Models like GPT-4o, Gemini, Claude Vision, and Qwen-VL are making visual AI

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YOLO26 Tutorial: Object Detection, Pose Estimation & More

ai, AI (Artificial Intelligence), Artificial Intelligence, Beginner, Computer vision, Machine Learning

Looking to model to implement pose estimation? I know something that can perform detection, instance segmentation, pose estimation and classification, all of that in real-time. Yes, I’m talking about the YOLO26 from ultralytics.  It can aid security systems or can be fine-tuned to detect even smaller objects. Wondering how to get started? No worries, we’ll

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Deploying retail AI to scale personalisation and customer insight

ai, AI (Artificial Intelligence), AI Business Strategy, AI Hardware & Chips, AI in Action, AI Market Trends, Analytics, Artificial Intelligence, automation, Computer vision, Data Engineering & MLOps, Deep Dives, edge computing, Features, infrastructure, Infrastructure & Hardware, Marketing AI, multimodal, Multimodal AI, Natural Language Processing (NLP), Open-Source & Democratised AI, Personalisation, physical ai, Reinforcement Learning, Retail, Retail & Logistics AI, Software, strategy, World of Work

Optimising retail AI infrastructure drives the successful deployment of personalisation systems and real-time customer insight. Leaders are replacing static customer interaction patterns with data pipelines capable of modifying the user environment during a live session. Static layouts and broad segmentation rules fail to satisfy modern conversion targets. Deployments demonstrate that traditional demographic categorisation generates insufficient

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OCRmyPDF Tutorial: Convert Scanned Documents into Searchable PDF/A Files with Sidecar Text Extraction and Batch Processing

ai, AI (Artificial Intelligence), Applications, Artificial Intelligence, Computer vision, Editors Pick, Language Model, Large Language Model, Machine Learning, OCR, Staff, Technology

In this tutorial, we build an advanced, self-contained OCRmyPDF workflow. We start by installing the required system and Python dependencies, then create a synthetic image-only PDF for scanning so we can test OCR without relying on external files. From there, we use OCRmyPDF’s real public API to convert scanned documents into searchable PDFs, generate PDF/A

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Datalab Releases lift: A 9B Open-Weights Vision Model That Extracts Structured JSON From PDFs Using Schemas

agentic ai, ai, AI (Artificial Intelligence), AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Generative AI, Language Model, Large Language Model, Machine Learning, New Releases, OCR, Open Source, Promote, Software engineering, sponsored, Staff, Tech News, Technology

Datalab has released lift, a 9B open-weights vision model for structured extraction. You pass it a JSON schema, and it returns a JSON object that matches. The model reads PDFs and images directly, then decodes against your schema. This is Datalab’s first model built purely for extraction. The team already ships open-source OCR tools: chandra,

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Computer vision deployments drive retail productivity gains

ai, AI (Artificial Intelligence), AI Business Strategy, AI in Action, AI Market Trends, Artificial Intelligence, automation, Computer vision, Deep Dives, Features, How It Works, Infrastructure & Hardware, Inside AI, inventory control, physical ai, productivity, Retail, Retail & Logistics AI, shelf hardware, simbe robotics, store intelligence, World of Work

Computer vision deployments are driving retail productivity gains as operators automate physical shelf tracking to protect eroding margins. This hardware deployment directly addresses the persistent in-store execution failures currently costing the industry billions. A study authored by Coresight Research – in partnership with technology providers Simbe and RELEX Solutions – calculates the exact cost of

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Could AI tell you where you left your keys?

Aeronautical and astronautical engineering, ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Autonomous vehicles, Computer science and technology, Computer vision, Electrical engineering and computer science (EECS), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Research, Robotics, School of Engineering

An auto factory worker can remember the storage bin where she left a partly assembled component the night before, and quickly return to that spot to pick it up. But robots that may work side-by-side with her would struggle to develop and access this same type of “spatiotemporal” memory.Now, MIT researchers have developed a long-term

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Zyphra Release Zamba2-VL: Hybrid Mamba2–Transformer Vision-Language Models That Cut Time-to-First-Token by About an Order of Magnitude

ai, AI (Artificial Intelligence), AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Open Source, Software engineering, Staff, Tech News, Technology, Uncategorized, Vision Language Model

Zyphra has released Zamba2-VL, a family of open vision-language models. The release covers three sizes: 1.2B, 2.7B, and 7B parameters. Each model is built on the Zamba2 hybrid SSM–Transformer backbone. Vision-language models (VLMs) read images and text together. They answer questions about charts, documents, and photos. Most open VLMs use a dense Transformer as the

Zyphra Release Zamba2-VL: Hybrid Mamba2–Transformer Vision-Language Models That Cut Time-to-First-Token by About an Order of Magnitude Read More »