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25 stories

Building a Memory-Driven Agent with NVIDIA NemoClaw

NVIDIA Technical BlogSiliconBuilding a Memory-Driven Agent with NVIDIA NemoClaw Enterprise work spans messages, decisions, projects, and obligations that change over time. An AI agent that starts without this context must reconstruct it...

Frontier Reasoning Reaches the Edge: How to Deploy and Optimize Models on NVIDIA Jetson

NVIDIA Technical BlogSiliconFrontier Reasoning Reaches the Edge: How to Deploy and Optimize Models on NVIDIA Jetson Running reasoning and agentic AI at the edge has been harder than it needs to be. Until recently, models capable of multi-step reasoning were too large to run...

How to Carry User Identity Across Federated Kubernetes and AI Platforms

NVIDIA Technical BlogSiliconHow to Carry User Identity Across Federated Kubernetes and AI Platforms Modern AI platforms are no longer a single application behind one login screen. A user may start in a central portal, open a governed dataset, launch a notebook...

NVIDIA PAIR Virtual Inference Router Expands Available Compute on Your Local Network

NVIDIA Technical BlogSiliconNVIDIA PAIR Virtual Inference Router Expands Available Compute on Your Local Network AI agents are learning to do more by working together. A lead agent can break a complex task into smaller jobs and assign those jobs to specialized subagents....

The Modern CUDA Toolbox in Practice: A Step-by-Step Optimization Walkthrough

NVIDIA Technical BlogSiliconThe Modern CUDA Toolbox in Practice: A Step-by-Step Optimization Walkthrough NVIDIA CUDA remains the foundation of GPU-accelerated computing, powering everything from scientific simulations to large-scale AI training. But writing...

Co-Designing AI Models Using Speculative Decoding for Faster LLM Inference

NVIDIA Technical BlogSiliconCo-Designing AI Models Using Speculative Decoding for Faster LLM Inference This post is the third in a series on AI model co-design. It explores how to accelerate LLM inference while maintaining accuracy using speculative decoding and...

Building an Adaptive Agentic Cybersecurity System with NVIDIA Nemotron

NVIDIA Technical BlogSiliconBuilding an Adaptive Agentic Cybersecurity System with NVIDIA Nemotron AI is changing the pace of cybersecurity. Agentic systems can coordinate work and pursue complex objectives over long horizons. Security teams are beginning to...

How to Size GPUs for AI Inference and TCO Without Overspending

NVIDIA Technical BlogSiliconHow to Size GPUs for AI Inference and TCO Without Overspending The surge in AI adoption is transforming everything from chatbots to content generation. Still, a common pain point remains: How can organizations confidently...

Run NVIDIA BioNeMo NIM Microservices for Protein Structure Prediction in Claude Science

NVIDIA Technical BlogSiliconRun NVIDIA BioNeMo NIM Microservices for Protein Structure Prediction in Claude Science Agentic AI is changing how research is done. AI scientists can read papers, propose hypotheses, call models, and determine which experiments to prioritize next....

Scale AV Perception Across Vehicle Platforms with NVIDIA Omniverse NuRec

NVIDIA Technical BlogSiliconScale AV Perception Across Vehicle Platforms with NVIDIA Omniverse NuRec A perception stack is shaped by the vehicle that carries it. Move the same software to a new carline—for example, from an SUV to a sedan or another vehicle...

Deploy an Open Model from Checkpoint to Inference in Two Commands with NVIDIA TensorRT Model Connect

NVIDIA Technical BlogSiliconDeploy an Open Model from Checkpoint to Inference in Two Commands with NVIDIA TensorRT Model Connect Open AI models are evolving faster than ever, but bringing them into native applications can still require model-specific conversion, preprocessing,...

NVIDIA NVLink Fusion Brings NVHBM to Next-Generation AI Infrastructure

NVIDIA Technical BlogSiliconNVIDIA NVLink Fusion Brings NVHBM to Next-Generation AI Infrastructure AI factories must support increasingly large models and more complex reasoning workloads. To keep up with the insatiable compute demands of AI workloads,...

How to Train a Cross-Embodiment Robot Navigation Policy with AI Agents

NVIDIA Technical BlogSiliconHow to Train a Cross-Embodiment Robot Navigation Policy with AI Agents Navigation enables a robot to turn perception and motion into purposeful autonomy. Unlike locomotion, which produces stable movement, navigation must be used to...

Experiment with Qwen3.8-Flash-Next on NVIDIA GB300 NVL72 for Agentic Coding

NVIDIA Technical BlogSiliconExperiment with Qwen3.8-Flash-Next on NVIDIA GB300 NVL72 for Agentic Coding Alibaba released the model weights for Qwen3.8-Flash-Next as a preview of the upcoming Qwen4 architecture for developers to experiment with and evaluate. It’s...

Restore LLM Inference Capacity in Seconds with Shadow Engine Recovery in NVIDIA Dynamo

NVIDIA Technical BlogSiliconRestore LLM Inference Capacity in Seconds with Shadow Engine Recovery in NVIDIA Dynamo When an LLM engine process fails, the standard recovery path involves a cold restart. This requires loading weights into HBM from storage, compiling kernels,...

CUDA Python 1.0: Stable APIs, One Foundation, Full Platform Access

NVIDIA Technical BlogSiliconCUDA Python 1.0: Stable APIs, One Foundation, Full Platform Access For years, a Python developer who needed a GPU had two realistic choices: Learn NVIDIA CUDA C++ well enough to write an extension, set up a build toolchain, and...

Giga-Scale AI and the Ethernet Evolution: How Spectrum-X Ethernet Rewrites the Rules

NVIDIA Technical BlogSiliconGiga-Scale AI and the Ethernet Evolution: How Spectrum-X Ethernet Rewrites the Rules The massive growth of generative AI has fundamentally altered data center design. As distributed model training scales to span hundreds of thousands of GPUs,...

NVIDIA Vera Rubin and Blackwell Set a New Standard for Agentic AI Performance per Watt

NVIDIA Technical BlogSiliconNVIDIA Vera Rubin and Blackwell Set a New Standard for Agentic AI Performance per Watt AI agents have expanded inference from single-turn interactions into multi-step workflows that reason, invoke tools, coordinate subagents, and carry growing...

NVIDIA BlueField-4 Powers New Scale-In Network Infrastructure for Agentic AI Factories

NVIDIA Technical BlogSiliconNVIDIA BlueField-4 Powers New Scale-In Network Infrastructure for Agentic AI Factories Traditional cloud infrastructure was designed for predictable, general-purpose workloads and standard interfaces. Agentic AI factories connect diverse users,...

Solving Agentic AI Fleet Challenges with NVIDIA Vera CPU

NVIDIA Technical BlogSiliconSolving Agentic AI Fleet Challenges with NVIDIA Vera CPU AI factories are interconnected systems where fleet economics depend on how efficiently the entire stack converts power and capital into completed agent tasks....

How NVIDIA Groq 3 LPX Unlocks Ultrafast Interactivity at Long Context on NVIDIA Vera Rubin

NVIDIA Technical BlogSiliconHow NVIDIA Groq 3 LPX Unlocks Ultrafast Interactivity at Long Context on NVIDIA Vera Rubin NVIDIA Groq 3 LPX is the interactive AI inference accelerator for the NVIDIA Vera Rubin platform. At the core of the platform is NVIDIA Vera Rubin NVL72, the...

Maximizing AI Factory Performance per Watt with NVIDIA DSX MaxLPS

NVIDIA Technical BlogSiliconMaximizing AI Factory Performance per Watt with NVIDIA DSX MaxLPS AI factories are power-constrained industrial systems. The question is no longer how many GPUs fit in a data center, but how much AI output each available...

GPU-Accelerated Clustering for Financial Instruments at Scale

NVIDIA Technical BlogSiliconGPU-Accelerated Clustering for Financial Instruments at Scale Use AdaptGrow, a GPU-accelerated matrix factorization algorithm, to turn rolling correlation and tail-dependence matrices into hard clusters, soft factor...

NVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents

NVIDIA Technical BlogSiliconNVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents A frontier language model is only one component of an AI agent. The surrounding agent system—often called a harness—determines how the model receives...

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About

Accept All is a magazine, a radar and a diary about artificial intelligence and the craft of code — read from Tokyo, for people who build.

The name is the button. Code is written by agents now and reviewed by a human thumb that hovers over Accept all a hundred times a day; the whole question of this decade is what, exactly, you just accepted. So we read the diff. A magazine, because every week one model, one tool or one idea is worth reading about slowly. A radar, because we count what the labs, the Valley, GitHub and the chip makers are talking about — releases, agents, open weights, compute, funding, rules — and show it as it moves. A diary, because a seal is set each day in that day's colour, and the days add up.

We read the research labs' own posts, the American and European tech press, the Japanese and Chinese developer sites and the newsletters people actually forward, and bring it together in English and Japanese. Everything here links back to the people who wrote it; the images belong to their authors.

Accept All will keep changing. New sources, new signals, new ways of looking — a little better each week, never finished. If something here made you open a terminal, that is enough.

Thank you for reading. ありがとうございます。