The auto-updated technology brief
NVIDIA introduces multi-device inference support in TensorRT to help scale generative AI workloads across multiple GPUs without losing key optimizations, addressing memory and compute limitations of single GPUs.
AWS Summit NYC showcased new AI agent launches including Amazon Quick, AWS Continuum security, DevOps tools, and Amazon Bedrock AgentCore updates. AWS launched a Local Zone in Hanoi, Grok 4.3 model on Bedrock, Amazon S3 annotations, faster ECS scaling, and EC2 G7 instances with NVIDIA RTX PRO 4500 GPUs. Price reductions include Amazon S3 Vectors and AWS Marketplace fees.
NVIDIA accelerates bird's-eye-view (BEV) pooling on GPUs to enhance perception in autonomous vehicles, robotics, and spatial AI systems, improving performance for downstream tasks like planning and object detection.
AlphaFold2's success in drug discovery relied on extensive protein structure data. Modern AI models depend on measured data for real-time processing and deep insights. NVIDIA's DAQIRI enables real-time AI for high-speed data acquisition, advancing AI workflows.
Amazon announces general availability of EC2 G7 instances featuring NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs and custom Intel Xeon Scalable processors, delivering enhanced AI inference, graphics, and data analytics performance.
NVIDIA XR AI provides a reusable foundation to help developers integrate AI experiences into AR glasses and wearable XR devices, addressing infrastructure challenges such as live data streams, multimodal AI models, and deployment.
NVIDIA introduces Halos, a full-stack functional safety system designed to enable autonomous robots to work safely alongside humans in unstructured environments such as factories, warehouses, and hospitals.
NVIDIA introduces DGX Spark to meet enterprise demands for scalable, secure, and manageable AI infrastructure with operational maturity.
Reinforcement learning (RL) is key to aligning language models, from RLHF in AI assistants to newer RLVR workflows for reasoning and agent tasks, enabling more accurate domain-specific AI agents.
Telecom operators are adopting AI across network operations, customer care, and back-office workflows, progressing towards autonomous networks but mostly at early stages.
Amazon ECS service auto scaling now supports high-resolution (20-second) metrics, enabling faster scaling response times and improved application performance with simpler configuration.
The NVIDIA CUDA Core Compute Libraries (CCCL) provide efficient and user-friendly abstractions for CUDA developers using C++ and Python, enhancing parallel computing capabilities.