Just how big is the market for humanoid robots? Big enough to soak up a whopping ~75 GWh of solid-state battery capacity between now and 2035 βΒ nearly 1500x growth!
moreβ¦Itβs been a big week for humanoid robots with a first-ever humanoid to directly connect to a low-Earth orbit satellite from one firm and plans announced to launch a robot into space by another. It seems like the robot space race is on βΒ and China is winning.
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To make humanoid robots useful, they need cognition and loco-manipulation that span perception, planning, and whole-body control in dynamic environments.Β ...To make humanoid robots useful, they need cognition and loco-manipulation that span perception, planning, and whole-body control in dynamic environments. Building these generalist robots requires a workflow that unifies simulation, control, and learning for robots to acquire complex skills before transferring into the real world. In this post, we present NVIDIA Isaac GR00T N1.6β¦
Generalist robot policies must operate across diverse tasks, embodiments, and environments, requiring scalable, repeatable simulation-based evaluation. Setting...Generalist robot policies must operate across diverse tasks, embodiments, and environments, requiring scalable, repeatable simulation-based evaluation. Setting up large-scale policy evaluations is tedious and manual. Without a systematic approach, developers need to build high-overhead custom infrastructure, yet task libraries remain limited in complexity and diversity.
NVIDIA is introducing the NVIDIA Jetson T4000, bringing high-performance AI and real-time reasoning to a wider range of robotics and edge AI applications....NVIDIA is introducing the NVIDIA Jetson T4000, bringing high-performance AI and real-time reasoning to a wider range of robotics and edge AI applications. Optimized for tighter power and thermal envelopes, T4000 delivers up to 1200β―FP4β―TFLOPs of AI compute and 64β―GB of memory, providing an ideal balance of performance, efficiency, and scalability. With its energy-efficient design and productionβ¦
Building powerful physical AI models requires diverse, controllable, and physically-grounded data at scale. Collecting large-scale, diverse real-world datasets...Building powerful physical AI models requires diverse, controllable, and physically-grounded data at scale. Collecting large-scale, diverse real-world datasets for training can be expensive, time-intensive, and dangerous. NVIDIA Cosmos open world foundation models (WFMs) address these challenges by enabling scalable, high-fidelity synthetic data generation for physical AI and the augmentation ofβ¦
Building autonomous robots requires robust, low-latency visual perception for depth, obstacle recognition, localization, and navigation in dynamic environments....
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