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VL-Cogito: Advancing Multimodal Reasoning with Progressive Curriculum Reinforcement Learning

Multimodal reasoning, where models integrate and interpret information from multiple sources such as text, images, and diagrams, is a frontier challenge in AI. VL-Cogito is a state-of-the-art Multimodal Large Language Model (MLLM) proposed by DAMO Academy (Alibaba Group) and partners, introducing a robust reinforcement learning pipeline that fundamentally upgrades the reasoning skills of large models…

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NVIDIA AI Introduces End-to-End AI Stack, Cosmos Physical AI Models and New Omniverse Libraries for Advanced Robotics

Nvidia made major waves at SIGGRAPH 2025 by unveiling a suite of new Cosmos world models, robust simulation libraries, and cutting-edge infrastructure—all designed to accelerate the next era of physical AI for robotics, autonomous vehicles, and industrial applications. Let’s break down the technological details, what this means for developers, and why it matters to the…

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NASA Releases Galileo: The Open-Source Multimodal Model Advancing Earth Observation and Remote Sensing

Introduction Galileo is an open-source, highly multimodal foundation model developed to process, analyze, and understand diverse Earth observation (EO) data streams—including optical, radar, elevation, climate, and auxiliary maps—at scale. Galileo is developed with the support from researchers from McGill University, NASA Harvest Ai2, Carleton University, University of British Columbia, Vector Institute, and Arizona State University.…

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Genie 3: A new frontier for world models

Acknowledgments Genie 3 was made possible due to key research and engineering contributions from Phil Ball, Jakob Bauer, Frank Belletti, Bethanie Brownfield, Ariel Ephrat, Shlomi Fruchter, Agrim Gupta, Kristian Holsheimer, Aleks Holynski, Jiri Hron, Christos Kaplanis, Marjorie Limont, Matt McGill, Yanko Oliveira, Jack Parker-Holder, Frank Perbet, Guy Scully, Jeremy Shar, Stephen Spencer, Omer Tov, Ruben…

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NVIDIA AI Releases GraspGen: A Diffusion-Based Framework for 6-DOF Grasping in Robotics

Robotic grasping is a cornerstone task for automation and manipulation, critical in domains spanning from industrial picking to service and humanoid robotics. Despite decades of research, achieving robust, general-purpose 6-degree-of-freedom (6-DOF) grasping remains a challenging open problem. Recently, NVIDIA unveiled GraspGen, a novel diffusion-based grasp generation framework that promises to bring state-of-the-art (SOTA) performance with unprecedented…

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Enterprise AI Investments 2025: Top Use-Cases

TLDR Content‑generation AI and Code‑generation AI together soak up ≈ $50 B+ in U.S. VC capital, dwarfing every other category. Cyber‑Sec, RPA, and Conversational AI - lead enterprise deployment charts. They win on clear ROI, fast time‑to‑value, and rich vendor ecosystems. 1. Use-Cases with the Widest Enterprise Adoption We’ve established that Enterprise spend on AI will be…

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