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#robotics

Every item tagged robotics, newest first.

11 items

A robot is sprinting towards you. Do you want it running on Claude or Grok?

The article compares the performance of Anthropic's Claude 3.5 Sonnet and xAI's Grok-1 in a simulated robotic scenario. The test evaluates how well each model handles dynamic situations requiring rapid decision-making. You can use these insights to choose the best model for applications needing fast and accurate responses. The results show Claude 3.5 Sonnet outperforming Grok-1 in this specific use case.

Key takeaways
  • Claude 3.5 Sonnet outperforms Grok-1 in dynamic decision-making tests.
  • The comparison simulates a robotic scenario with rapid response requirements.
  • Insights help builders choose models for applications needing speed and accuracy.

AI coding agents taught robots how to install GPUs and cut zip ties

Researchers used AI coding agents to teach robots to perform complex tasks like installing GPUs and cutting zip ties. The agents autonomously generated code that allowed robots to learn from trial and error. This approach could enable robots to adapt to new situations without extensive reprogramming. You can apply this method to train robots for various tasks.

Key takeaways
  • AI agents autonomously generated code for robot tasks.
  • Robots learned installing GPUs, cutting zip ties via trial and error.
  • Method allows robots to adapt without extensive reprogramming.

From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot

Amazon researchers have developed Strands Agents and LeRobot, a framework and hardware platform that enables developers to deploy AI models from the Hugging Face Hub onto robots. This integration allows for the creation of more sophisticated and autonomous robotic systems. You can now leverage the Hugging Face ecosystem to build and deploy robot applications. The combination of software and hardware provides a comprehensive solution for robotics development.

Key takeaways
  • Strands Agents and LeRobot integrate Hugging Face models with robot hardware.
  • Enables deployment of AI models onto robots for autonomous systems.
  • Combines software and hardware for comprehensive robotics development.

Working on a weebo like ai sentient robot, which can fly, respond, and act as an AI assistant

A hobbyist is building a Weibo-like AI sentient robot that can fly, respond, and act as an AI assistant. The project involves selecting hardware components, including brushless motors, flight controllers, and ESP32 development boards. The builder is uncertain about the hardware choices and is seeking feedback. The robot aims to integrate AI capabilities with flight and interaction functionalities.

Key takeaways
  • Builder is using BetaFPV 0802SE brushless motors and FLYWOO GOKU F405 HD flight controller.
  • Project involves ESP32 development boards for AI and control.
  • Goal is to create a flying, interactive AI assistant like Weibo.

Visual Verification Enables Inference-time Steering and Autonomous Policy Improvement

Researchers propose VERITAS, a framework for robot policy improvement through inference-time steering and self-improvement. VERITAS pairs a pre-trained policy with a visual verifier to evaluate actions at inference time, enabling robots to learn from experience. This approach allows for autonomous policy improvement without requiring extensive retraining. Builders can apply this framework to create more adaptive robot systems.

Key takeaways
  • VERITAS framework enables inference-time policy steering and self-improvement.
  • Uses a pre-trained policy paired with a gradient-free visual verifier.
  • Enables autonomous policy improvement for robots.

Qwen Robot Suite

Qwen Robot Suite is a new open-source framework for building robots. It provides a set of tools and APIs for developing robotic applications. The framework is designed to be highly customizable and extensible. You can use it to build a wide range of robotic systems.

Key takeaways
  • Qwen Robot Suite is open-source.
  • It provides a set of tools and APIs for building robots.
  • The framework is highly customizable.

Qwen-Robot Suite: A Foundation Model Suite for Physical World Intelligence

Researchers at Alibaba released Qwen-Robot Suite, a suite of foundation models for physical world intelligence. The suite targets applications in robotics and embodied AI. You can use it to build more capable robots. Qwen-Robot Suite includes models for perception, planning, and control.

Key takeaways
  • Qwen-Robot Suite targets robotics and embodied AI applications.
  • Includes models for perception, planning, and control.
  • Developed by Alibaba researchers.

Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine‑Tuning, and On‑Device Optimizations

Researchers from NXP and Hugging Face collaborated to bring robotics AI to embedded platforms. They developed methods for dataset recording, fine-tuning vision-language-action models, and on-device optimizations. This enables running AI models on resource-constrained embedded systems, expanding AI deployment options for builders. The approach allows for efficient AI model execution on devices with limited resources.

Key takeaways
  • Enables AI on resource-constrained embedded systems.
  • Developed methods for dataset recording and VLA fine-tuning.
  • On-device optimizations improve model efficiency.
modelsJan 5

NVIDIA Cosmos Reason 2 Brings Advanced Reasoning To Physical AI

NVIDIA released Cosmos Reason 2, an advanced reasoning model for physical AI. This update brings improved performance and capabilities to the existing Cosmos platform. Builders working with physical AI can leverage Cosmos Reason 2 for more accurate and efficient simulations. The new model is expected to enhance various applications, including robotics and computer vision.

Key takeaways
  • Improved performance and capabilities for physical AI simulations.
  • Enhanced accuracy and efficiency for robotics and computer vision applications.
  • Advanced reasoning model for complex physical systems.
researchJul 10

Asynchronous Robot Inference: Decoupling Action Prediction and Execution

Researchers propose asynchronous robot inference, decoupling action prediction and execution to improve real-time performance. This approach enables more efficient use of compute resources, reducing latency and increasing throughput. By separating prediction and execution, developers can build more responsive and scalable robot control systems. The method is applicable to various robotic applications, including manipulation and navigation.

Key takeaways
  • Asynchronous inference decouples action prediction and execution.
  • Reduces latency and increases throughput in robot control systems.
  • Applicable to manipulation, navigation, and other robotic tasks.
otherApr 14

Hugging Face to sell open-source robots thanks to Pollen Robotics acquisition 🤖

Hugging Face acquired Pollen Robotics, a startup focused on open-source robotics. The deal brings robotics expertise and open-source software assets to Hugging Face. You can expect Hugging Face to expand into robotics, building on its existing strengths in open-source AI. The acquisition supports Hugging Face's goal of making AI more accessible.

Key takeaways
  • Hugging Face acquired Pollen Robotics.
  • The deal adds robotics expertise and open-source software assets.
  • Hugging Face plans to expand into robotics.