Physical AI

Maximo Robotics completes 300,000 construction tasks in utility-scale solar projects

Original titleMaximo Robotics completes 300,000 tasks in utility-scale solar projects

Outlet: Robotics & Automation News
Published: Oct 31, 2026
Importance: 2/5

Summary

Maximo Robotics announced that its autonomous construction robots have completed over 300,000 tasks under performance-based robotics-as-a-service contracts. Crew members working alongside Max 4.0 systems achieved 2.5 times their manual installation rates per person per shift hour.

Original excerpt

Maximo Robotics, a physical-AI platform company focused on autonomous construction robotics, has announced that its US-made robotics systems have completed more than 300,000 construction tasks under performance-based robotics-as-a-service contracts. Crew members working alongside Max 4.0 systems have delivered 2.5 times their manual installation rates per person per shift hour. This improved productivity is helping electricity […]

#robotics#productivity#autonomous construction

Read the original

See all →

Oct 31

Foundry Robotics raises $100 million Series A for autonomous assembly factories

Foundry Robotics announced an oversubscribed $100 million Series A funding round led by Marlinspike Partners. The round includes participation from early backers Khosla Ventures and Red Glass Ventures, alongside new investors SE Ventures, Wing VC, and Axiom Ventures.

Robotics & Automation News

Nov 2

Meta partners with Fourier on humanoid robot for household tasks

Meta and Chinese robotics startup Fourier jointly developed humanoid robot prototype Max, a 48-kilogram robot completed in three months. The companies are working on a successor model, targeting the household robotics market for housekeeping and daily tasks.

AI Times

Nov 4

NEO-VLA, an encoder-free vision-language-action framework for robotic manipulation

The authors propose NEO-VLA, an encoder-free vision-language-action framework where images are tokenized and evolve jointly with language throughout the backbone. They show that this approach outperforms encoder-based counterparts across diverse manipulation tasks and distribution shifts.

Hugging FaceTrending 27

Oct 27

PDRVLA integrates physical dynamics into robot vision-language-action models

PDRVLA, a vision-language-action model with a lightweight physical dynamics module, generates robot actions from visual input and language instructions. It learns from public data augmented with human-to-robot synthesis and embodied chain-of-thought annotation, achieving 99.3% success on LIBERO and up to 93.6% on RoboTwin 2.0.

Hugging Face +1 moreTrending 25