Vol. I · No. 163TUE, SEP 29, 2026
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R²D²: Scaling Multimodal Robot Learning with NVIDIA Isaac Lab

Building robust, intelligent robots requires testing them in complex environments. However, gathering data in the physical world is expensive, slow, and often... Building robust, intelligent robots requires testing them in complex environments. However, gathering data in the physical world is expensive, slow, and often dangerous. It is nearly impossible to safely train for real-world critical risks, such as high-speed collisions or hardware failures. Worse, real-world data is usually biased toward “normal” conditions, leaving robots unprepared for the… Source

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Using Accelerated Computing to Live-Steer Scientific Experiments at Massive Research Facilities

Scientists and engineers who design and build unique scientific research facilities face similar challenges. These include managing massive data rates that... Scientists and engineers who design and build unique scientific research facilities face similar challenges. These include managing massive data rates that exceed current computational infrastructure capacity to extract scientific insights and driving the experiments in real time. These challenges are obstacles to maximizing the impact of scientific discoveries and significantly slow the pace of… Source

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Automating Inference Optimizations with NVIDIA TensorRT LLM AutoDeploy

NVIDIA TensorRT LLM enables developers to build high-performance inference engines for large language models (LLMs), but deploying a new architecture... NVIDIA TensorRT LLM enables developers to build high-performance inference engines for large language models (LLMs), but deploying a new architecture traditionally requires significant manual effort. To address this challenge, today we are announcing the availability of AutoDeploy as a beta feature in TensorRT LLM. AutoDeploy compiles off-the-shelf PyTorch models into inference-optimized… Source

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Testing ads in ChatGPT

OpenAI tests advertising in ChatGPT free tier with privacy controls and answer independence guarantees.

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3 Ways NVFP4 Accelerates AI Training and Inference

The latest AI models continue to grow in size and complexity, demanding increasing amounts of compute performance for training and inference—far beyond what... The latest AI models continue to grow in size and complexity, demanding increasing amounts of compute performance for training and inference—far beyond what Moore’s Law can keep up with. That’s why NVIDIA engages in extreme codesign. Designing across multiple chips and a mountain of software cohesively enables large generational leaps in AI factory performance and efficiency. Source

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How to Build License-Compliant Synthetic Data Pipelines for AI Model Distillation

Specialized AI models are built to perform specific tasks or solve particular problems. But if you’ve ever tried to fine-tune or distill a domain-specific... Specialized AI models are built to perform specific tasks or solve particular problems. But if you’ve ever tried to fine-tune or distill a domain-specific model, you’ve probably hit a few blockers, such as: These challenges often prevent promising AI projects from progressing beyond the experimental phase. This post walks you through how to remove all four of these blockers using a… Source

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Introducing OpenAI Frontier

OpenAI Frontier is enterprise platform for building, deploying, and managing AI agents with governance and context management.

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GPT-5.3-Codex System Card

System card for GPT-5.3-Codex describes most capable agentic coding model combining coding performance with reasoning.

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Introducing GPT-5.3-Codex

GPT-5.3-Codex pairs frontier coding performance with reasoning for long-horizon agent-based technical tasks.

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Build with Kimi K2.5 Multimodal VLM Using NVIDIA GPU-Accelerated Endpoints

Kimi K2.5 is the newest open vision language model (VLM) from the Kimi family of models. Kimi K2.5 is a general-purpose multimodal model that excels in current... Kimi K2.5 is the newest open vision language model (VLM) from the Kimi family of models. Kimi K2.5 is a general-purpose multimodal model that excels in current high-demand tasks such as agentic AI workflows, chat, reasoning, coding, mathematics, and more. The model was trained using the open source Megatron‑LM framework. Megatron-LM provides accelerated computing for scalability and GPU… Source

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Claude is a space to think

Anthropic commits to keeping Claude ad-free, arguing advertising incentives conflict with trustworthy AI assistance.

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How to Build a Document Processing Pipeline for RAG with Nemotron

What if your AI agent could instantly parse complex PDFs, extract nested tables, and "see" data within charts as easily as reading a text file? With NVIDIA... What if your AI agent could instantly parse complex PDFs, extract nested tables, and “see” data within charts as easily as reading a text file? With NVIDIA Nemotron RAG, you can build a high-throughput intelligent document processing pipeline that handles massive document workloads with precision and accuracy. This post walks you through the core components of a multimodal retrieval pipeline… Source

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30 stories