Tootfinder

#Herbst-Impressionen vom Panoramaweg Bad Belzig. Fünfblättriger Wilder Wein (Parthenocissus quinquefolia) in knalligen Farben.
Für eine #Sommerwanderung in diesem Bundesland findet Ihr Routenideen mit GPX-Track übrigens unter

AI robotics startup Physical Intelligence claims vision-language-action models learn to align human videos and robot data as pre-training is scaled up (Physical Intelligence)
https://www.physicalintelligence.company/research/human_to_robot

Emergence of Human to Robot Transfer in Vision-Language-Action Models
Exploring how transfer from human videos to robotic tasks emerges in robotic foundation models as they scale.

My interests in sealife & medieval history converge with the exhibition of woodcut prints by @… in the beautiful space of #StBenetsCam, founded before the Norman conquest:

AquaClaire (@AquaClaire@ecoevo.social)
Attached: 1 image Two powerful artworks by Pangrok Sulap are now on display in the beautiful space of St Bene't's in Cambridge: https://www.stbenetschurch.org/laut 📷 Revd Devin McLachlan 🧵 1/2 #sealife #StBenetsCam #BottomTrawling #ocean #pollution #MarineConservation #PangrokSulap #IconicFishes #Cambridge

Harmonic, an AI math startup co-founded by Vlad Tenev, raised a $120M Series C led by Ribbit at a $1.45B valuation, bringing its total funding to $295M (Krystal Hu/Reuters)
https://www.reuters.com/business/robinhood-ceos-…

Robot Learning: A Tutorial
Francesco Capuano, Caroline Pascal, Adil Zouitine, Thomas Wolf, Michel Aractingi
https://arxiv.org/abs/2510.12403 https://arxiv.…

Robot Learning: A Tutorial
Robot learning is at an inflection point, driven by rapid advancements in machine learning and the growing availability of large-scale robotics data. This shift from classical, model-based methods to data-driven, learning-based paradigms is unlocking unprecedented capabilities in autonomous systems. This tutorial navigates the landscape of modern robot learning, charting a course from the foundational principles of Reinforcement Learning and Behavioral Cloning to generalist, language-conditione…

After years of patient investment, China is on the cusp of a robotics revolution.

If embodied intelligence
— think AI-powered robots that can navigate the real world
— is the next frontier of AI, then China appears poised to dominate.
Though the United States still has distinct advantages in software, advanced AI chips and foundational research, China leads in robot hardware, deployment and policy support.

Last year, China installed nearly 300,000 robots in its fact…

The Chinese robots are coming
China is miles ahead in the race to dominate a technology that could define the 21st century.

VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing
Yixiao Wang, Mingxiao Huo, Zhixuan Liang, Yushi Du, Lingfeng Sun, Haotian Lin, Jinghuan Shang, Chensheng Peng, Mohit Bansal, Mingyu Ding, Masayoshi Tomizuka
https://arxiv.org/abs/2510.05213

VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing
Pretrained vision foundation models (VFMs) advance robotic learning via rich visual representations, yet individual VFMs typically excel only in specific domains, limiting generality across tasks. Distilling multiple VFMs into a unified representation for policy can mitigate this limitation but often yields inflexible task-specific feature selection and requires costly full re-training to incorporate robot-domain knowledge. We propose VER, a Vision Expert transformer for Robot learning. During …

Reliable and Scalable Robot Policy Evaluation with Imperfect Simulators
Apurva Badithela, David Snyder, Lihan Zha, Joseph Mikhail, Matthew O'Kelly, Anushri Dixit, Anirudha Majumdar
https://arxiv.org/abs/2510.04354

Reliable and Scalable Robot Policy Evaluation with Imperfect Simulators
Rapid progress in imitation learning, foundation models, and large-scale datasets has led to robot manipulation policies that generalize to a wide-range of tasks and environments. However, rigorous evaluation of these policies remains a challenge. Typically in practice, robot policies are often evaluated on a small number of hardware trials without any statistical assurances. We present SureSim, a framework to augment large-scale simulation with relatively small-scale real-world testing to prov…

Qargo, which offers a cloud-based transport management service for carriers, freight forwarders, and third-party logistics, raised a $33M Series B led by Sofina (Tamara Djurickovic/Tech.eu)
https://tech.eu/2025/12/11/qargo-expands-ai-driven-transpor…

Qargo expands AI-driven transport management with $33M Series B
Qargo, an intelligent transport management system (TMS), has raised $33 million in a Series B funding round led by Sofina, with participation from existing investor Balderton Capital. The round follows Qargo’s rapid expansion across key European logistics hubs over the last 18 months. This latest investment brings Qargo’s total funding to $54 million.Founded in 2020, Qargo is a cloud-based transport management platform designed for carriers, freight forwarders, and 3PLs. It helps log…

Placeit! A Framework for Learning Robot Object Placement Skills
Amina Ferrad, Johann Huber, Fran\c{c}ois H\'el\'enon, Julien Gleyze, Mahdi Khoramshahi, St\'ephane Doncieux
https://arxiv.org/abs/2510.09267

Placeit! A Framework for Learning Robot Object Placement Skills
Robotics research has made significant strides in learning, yet mastering basic skills like object placement remains a fundamental challenge. A key bottleneck is the acquisition of large-scale, high-quality data, which is often a manual and laborious process. Inspired by Graspit!, a foundational work that used simulation to automatically generate dexterous grasp poses, we introduce Placeit!, an evolutionary-computation framework for generating valid placement positions for rigid objects. Placei…