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Meta AI Researchers Release MapAnything: An End-to-End Transformer Architecture that Directly Regresses Factored, Metric 3D Scene Geometry

A team of researchers from Meta Reality Labs and Carnegie Mellon University has introduced MapAnything, an end-to-end transformer architecture that directly regresses factored metric 3D scene geometry from images and optional sensor inputs. Released under Apache 2.0 with full training and benchmarking code, MapAnything advances beyond specialist pipelines by supporting over 12 distinct 3D vision…

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Gemini achieves gold-level performance at the International Collegiate Programming Contest World Finals

Acknowledgements We thank the International Collegiate Programming Contest (ICPC) for their support. This project was a large-scale collaboration, and its success is due to the combined efforts of many individuals and teams. Hanzhao (Maggie) Lin led the overall technical direction for Gemini competitive programming and ICPC 2025 efforts, and co-led with Heng-Tze Cheng on the…

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Exploring Metaclasses in Python: Unleashing the Power of Class Creation

Image by Editor   #  Introduction   In Python, there is a concept called object-oriented programming (OOP). This programming paradigm revolves around data and objects. It works by encapsulating related state (attributes) and behavior (methods) within classes, and creating object instances from those classes. For many data scientists, Python is the first programming language they…

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IBM AI Releases Granite-Docling-258M: An Open-Source, Enterprise-Ready Document AI Model

IBM has released Granite-Docling-258M, an open-source (Apache-2.0) vision-language model designed specifically for end-to-end document conversion. The model targets layout-faithful extraction—tables, code, equations, lists, captions, and reading order—emitting a structured, machine-readable representation rather than lossy Markdown. It is available on Hugging Face with a live demo and MLX build for Apple Silicon. What’s new compared to…

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Gemini Robotics 1.5 brings AI agents into the physical world

Acknowledgements This work was developed by the Gemini Robotics team: Abbas Abdolmaleki, Saminda Abeyruwan, Joshua Ainslie, Jean-Baptiste Alayrac, Montserrat Gonzalez Arenas, Ashwin Balakrishna, Nathan Batchelor, Alex Bewley, Jeff Bingham, Michael Bloesch, Konstantinos Bousmalis, Philemon Brakel, Anthony Brohan, Thomas Buschmann, Arunkumar Byravan, Serkan Cabi, Ken Caluwaerts, Federico Casarini, Christine Chan, Oscar Chang, London Chappellet-Volpini, Jose Enrique…

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Gemini Robotics 1.5: DeepMind’s ER↔VLA Stack Brings Agentic Robots to the Real World

Can a single AI stack plan like a researcher, reason over scenes, and transfer motions across different robots—without retraining from scratch? Google DeepMind’s Gemini Robotics 1.5 says yes, by splitting embodied intelligence into two models: Gemini Robotics-ER 1.5 for high-level embodied reasoning (spatial understanding, planning, progress/success estimation, tool-use) and Gemini Robotics 1.5 for low-level visuomotor…

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10 Useful Python One-Liners for Data Engineering

Image by Editor | ChatGPT   #  Introduction   Data engineering involves processing large datasets, building ETL pipelines, and maintaining data quality. Data engineers work with streaming data, monitor system performance, handle schema changes, and ensure data consistency across distributed systems. Python one-liners can help simplify these tasks by condensing complex operations into single, readable…

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How to Master Advanced TorchVision v2 Transforms, MixUp, CutMix, and Modern CNN Training for State-of-the-Art Computer Vision?

In this tutorial, we explore advanced computer vision techniques using TorchVision’s v2 transforms, modern augmentation strategies, and powerful training enhancements. We walk through the process of building an augmentation pipeline, applying MixUp and CutMix, designing a modern CNN with attention, and implementing a robust training loop. By running everything seamlessly in Google Colab, we position…

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Strengthening our Frontier Safety Framework

We’re expanding our risk domains and refining our risk assessment process. AI breakthroughs are transforming our everyday lives, from advancing mathematics, biology and astronomy to realizing the potential of personalized education. As we build increasingly powerful AI models, we’re committed to responsibly developing our technologies and taking an evidence-based approach to staying ahead of emerging…

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