#Nemotron

Nvidia is managing the worst hit to its reputation in its three-decade history from the revelations that its CEO Jensen Huang had an affair with a woman reportedly working for China’s spy agencies (read our latest on that here).…

Hyundai Motor Group and AIM Intelligence explore NVIDIA NemoClaw and OpenShell for secure enterprise agents, and LG AI Research opens API for ‘K-EXAONE-2.5’ trained on Nemotron datasets.

Chris Alexiuk is a senior product research engineer in deep learning at NVIDIA who specializes in making open large language models (LLMs) practical for working developers.

AI is expanding beyond the data center as developers build a new generation of agents to act at the edge: monitoring driver attention and cabin conditions…

Mô hình chuyển giọng nói thành văn bản mã nguồn mở tốt nhất vào tháng 10 năm 2026 là Nemotron 3.5...

Cách sử dụng NVIDIA Nemotron 3.5 Transcribe miễn phí (mô hình chuyển giọng nói thành văn bản...

As AI adoption expands globally, people across languages and cultures are using it in more aspects of their daily lives. General-purpose language models serve…

Single-turn chatbots are evolving into long-running agents that can reason, maintain context, use tools, and run efficiently across many turns to complete…

As context windows grow longer, moving large model weights efficiently becomes critical to performance. A common way to address this is quantization…

Industrial machinery generates more alarms than technicians can triage. For each important alarm requiring follow-up, the technician pulls historical context…

Customization is what enables developers to take a general model and tailor it to use cases, domains, languages, and more. However, customization comes with a…

Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware…

I used one RTX PRO 6000 Blackwell 96 GB per model to run three copies of a local LLM as coding workers at the same time (llama.cpp b11803, CUDA, Q8_0 GGUF, --parallel 3, 64K context per slot). A cloud model planned, the GPU did all the code writing.…

New model families for vision and language, retrieval, tabular data, biology, robotics and quantum computing supercharge development in Europe.

Long-running AI agents spend most of their time on high-volume execution: tool calls, result validation, and subagent delegation. Using a frontier reasoning…

Teams customize their models to hit their targets for latency, speed, memory, and compute. With the open NVIDIA Nemotron family of models…

AI is changing the pace of cybersecurity. Agentic systems can coordinate work and pursue complex objectives over long horizons. Security teams are beginning to…

Deploying a large language model is only the first step toward production-ready serving. Production teams also need to serve as many concurrent users as…

Always-on agents are taking on longer, more complex enterprise workflows. A single request can involve reading a document, checking information across sources…

Status: building now. Started 21 Oct 2026 for the Nebius x NVIDIA Global AI Hackathon. Submission...