Build On-Device AI Companions with NVIDIA ACE Game Agent SDK and Unreal Engine 5 Plugins
NVIDIA expands Unreal Engine 5 integration with new tools for building on-device AI characters using the ACE Game Agent SDK and RTX technologies.
The auto-updated technology brief
NVIDIA expands Unreal Engine 5 integration with new tools for building on-device AI characters using the ACE Game Agent SDK and RTX technologies.
NVIDIA introduces Confidential Computing, a hardware-rooted security solution designed to protect data privacy and sovereignty during AI inference without compromising performance.
Microsoft and NVIDIA have partnered to provide new tools enabling developers to build personal AI agents on Windows PCs, enhancing AI integration with easier setup and native security.
NVIDIA developed an AI agent using Nemotron to assist technicians in managing and analyzing industrial machinery alarms by providing historical context and recommendations.
NVIDIA discusses how shaders use resource binding to access GPU resources and introduces end-to-end support for Vulkan descriptor heaps to streamline this process.
NVIDIA introduces the BioNeMo Agent Toolkit, enabling AI scientists to assist in life science discovery by reading papers, generating hypotheses, writing code, and calling APIs in an iterative scientific process.
NVIDIA introduces Nemotron 3 Ultra using NVFP4 4-bit floating point quantization with Model Optimizer to efficiently move large model weights for longer context windows.
NVIDIA Omniverse NuRec is a neural reconstruction pipeline that builds high-fidelity 3D representations of real-world environments from multisensor data, optimized using NVIDIA Nsight developer tools.
NVIDIA's GPU-accelerated query engines overcome memory and I/O bandwidth constraints using hardware advances like high bandwidth memory, NVLink-C2C, and decompression engines in the GB200 NVL4.
NVIDIA introduces Isaac GR00T to streamline humanoid robot policy development, addressing fragmented workflows and infrastructure challenges.
Training large language models (LLMs) at massive scale faces infrastructure challenges due to long runtimes and thousands of GPUs. Nonuniform tensor parallelism helps mitigate slowdowns caused by device unavailability and resource fluctuations.
Amazon EC2 C9g and C9gd instances, powered by AWS Graviton5, are now generally available. They deliver up to 25% better compute performance than previous generation, feature fastest memory in the cloud, and offer local NVMe storage options for demanding workloads.