With Dell PowerFlex, your customers can enjoy efficiency, resilience, and performance without trade-offs. This software-defined architecture supports a wide range of workloads—from databases to AI—on a single platform. When storage empowers rather than limits, partners can help customers innovate faster and gain a competitive edge. Learn more: https://t.co/G8mKa9kBcD
Introducing GEN-1.5, a one-shot learner.
It can learn new tasks in a few seconds. Show it what to do, and it generalizes.
This capability emerged from pretraining on physical data at scale, as a step towards our mission of building general intelligence for the physical world.
🤖 Build a robot manipulation policy with NVIDIA Cosmos 3 Edge and run it directly on NVIDIA Jetson Thor, without a data-center GPU in the control loop.
Follow the full workflow, from preparing Cosmos 3-DROID data and post-training a 4B model to receding-horizon control and closed-loop evaluation in RoboLab simulation.
Read the technical walkthrough ➡��� https://t.co/u2QI2B3l7n
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Always-on AI agents need fast, specialized task execution. 🦾
Run NVIDIA Nemotron 3.5 Lightning, the fastest MoE model in its class, with an average of 115 tokens/s on Jetson AGX Thor and 89 tokens/s on Jetson AGX Orin. Its open weights make it ready to customize for local AI agents that never sleep.
Try it on Jetson AI Lab: https://t.co/TeTFXvbjuF
Today, NVIDIA announced Nemotron 3.5 Lightning and NeMo Switchyard — two new open technologies for building faster, more efficient AI systems that can use the right model for each task.
Together, they give developers greater control over how and where AI runs.
⬇️
Physical AI depends on open models.
As robots become more capable, developers need to build, customize, control, and deploy their own AI.
See how NVIDIA is advancing open world models to help developers build the next generation of physical AI. 👀
Read the blog: https://t.co/IRjD2aizcR
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