←Search results

English text is being prepared.

By relevance · Total 1587 results Clear search

Monday

Sunday

Saturday

Friday

Thursday

Wednesday

  1. AIhub

    IJCAI-ECAI 2026 Tutorials and Workshops Recap (Part 1)

    In the IJCAI-ECAI 2026 tutorials and workshops recap, one tutorial focused on missing data imputation in image and tabular scenarios, covering methods ranging from statistical baselines to autoencoders and generative adversarial networks; another, the SAFER workshop, was held on August 16 in Bremen, Germany, where dozens of researchers jointly developed a roadmap for trustworthy agentic AI, proposing three main lines of advancement: safety, reliability, and sovereignty, with related extended papers and chapters planned for publication in 2027.

    In the IJCAI-ECAI 2026 tutorials and workshops recap, one tutorial focused on missing data imputation in image and tabular scenarios, covering methods ranging from statistical baselines to autoencoders and generative adversarial networks; another, the SAFER workshop, was held on August 16 in Bremen, Germany, where dozens of researchers jointly developed a roadmap for trustworthy agentic AI, proposing three main lines of advancement: safety, reliability, and sovereignty, with related extended pap

    Matched fieldsSummary、Body

    #ai-vertical#Industry news#Agents#Safety / alignment

Tuesday

  2. NVIDIA Developer · Generative AI

    How NVIDIA Isaac ROS 5.0 Uses AI Agents to Accelerate ROS 2 Nodes

    The rosidl::Buffer and CUDA buffer backend contributed by NVIDIA in ROS Lyrical allow ROS 2 nodes to exchange GPU-resident data via zero-copy when runtime conditions permit, while preserving standard ROS 2 messages and node boundaries. All nodes in Isaac ROS 5.0 have been switched to this CUDA buffer backend. The article uses the Depth Anything 3 TensorRT ROS 2 node as a migration example, in which an AI coding agent, with the help of the migrate-node-to-rosidl-buffer skill, completes the audit and a minimal interface-preserving refactor, and uses NVIDIA Nsight Systems to verify that payload-sized host-device transfers no longer occur at the ROS boundary.

    The rosidl::Buffer and CUDA buffer backend contributed by NVIDIA in ROS Lyrical allow ROS 2 nodes to exchange GPU-resident data via zero-copy when runtime conditions permit, while preserving standard ROS 2 messages and node boundaries. All nodes in Isaac ROS 5.0 have been switched to this CUDA buffer backend. The article uses the Depth Anything 3 TensorRT ROS 2 node as a migration example, in which an AI coding agent, with the help of the migrate-node-to-rosidl-buffer skill, completes the audit

    Matched fieldsSummary、Body

    #lab#Tutorials / practice#English text is being prepared.#Agents

Monday