Nvidia just announced an open‑source AI agent platform built on its CUDA GPU stack, aiming to simplify building and deploying intelligent agents. The new NemoClaw security suite adds enterprise‑grade protection for AI workloads. Curious how this could reshape AI development and security? Dive into the details. #NvidiaAI #OpenSourceAI #NemoClaw #EnterpriseSecurity

🔗 https://aidailypost.com/news/nvidia-launch-open-source-ai-agent-platform-adds-nemoclaw-security

Kerala startup Genesis Labs sets up the state’s first Nvidia AI factory at SmartCity Kochi for KeyValue Software Systems, marking Kerala’s entry into exascale AI supercomputing and high-performance computing. https://english.mathrubhumi.com/news/kerala/kerala-startup-sets-up-states-first-nvidia-ai-factory-in-kochi-qdk0icgo?utm_source=dlvr.it&utm_medium=mastodon #NvidiaAI #ArtificialIntelligence #KeralaStartup #KochiTech
NVIDIA Blackwell Ultra Lowers AI Agent Cost

NVIDIA Blackwell Ultra reduces cost per token up to 35x for agentic AI, with 50x higher throughput per megawatt. Ideal for low-latency, long-context workloads.

TechLife
NVIDIA Blackwell Ultra Lowers AI Agent Cost

NVIDIA Blackwell Ultra reduces cost per token up to 35x for agentic AI, with 50x higher throughput per megawatt. Ideal for low-latency, long-context workloads.

TechLife

New Nvidia research cuts LLM reasoning cost by 8× while keeping accuracy intact. By compressing the transformer’s key‑value cache with dynamic memory tricks, inference becomes far cheaper for everyone. A must‑read for anyone building open‑source LLMs. #DynamicMemoryCompression #KeyValueCache #NvidiaAI #LLMOptimization

🔗 https://aidailypost.com/news/nvidia-technique-reduces-llm-reasoning-cost-8fold-while-preserving

Universal Music Group teams up with Nvidia to build a generative‑AI model that understands songs like a human, powering smarter search across Udio and beyond. The partnership stresses responsible AI and even taps Anthropic expertise. Could this reshape music discovery? Read on to see how AI is hitting the right note. #UniversalMusicAI #NvidiaAI #GenerativeAI #ResponsibleAI

🔗 https://aidailypost.com/news/universal-music-partners-nvidia-ai-model-smarter-song-search

🚀 Nvidia’s latest earnings reveal soaring chip demand as AI workloads explode. With $500 B market hype, new GPU orders surge and Google’s Gemini 3 LLM pushes generative AI forward. What does this mean for the future of large‑language models? Dive into the numbers and the tech behind the hype. #NvidiaAI #Gemini3 #GPU #GenerativeAI

🔗 https://aidailypost.com/news/nvidia-earnings-highlight-chip-demand-ai-expands-gemini-3-announced

🚀 Nvidia svela un futuro ricco d'innovazione con l'AI, sfidando i limiti del possibile. Accendiamo insieme la scintilla del progresso! #NvidiaAI #FuturoDigitale #socialmedia #artificialintelligence #technology

🔗 https://aibay.it/notizie/nvidia-svela-la-sua-visione-per-il-futuro-dellai-2025-10-29

Nvidia svela la sua visione per il futuro dell'AI

Nvidia punta a rendere la sua tecnologia essenziale nella vita quotidiana, consolidando la leadership nei chip per l'intelligenza artificiale.

AiBay
Alibaba Cloud claims it's achieved a miraculous 82% reduction in Nvidia AI GPU usage, effectively turning a few GPUs into a magical GPU army. 🎩✨ It's as if they're suggesting that instead of buying more GPUs, you can just sprinkle some fairy dust and watch them multiply! 🧚‍♂️💸
https://www.tomshardware.com/tech-industry/semiconductors/alibaba-says-new-pooling-system-cut-nvidia-gpu-use-by-82-percent #AlibabaCloud #NvidiaAI #GPUUsage #MagicTech #GPUArmy #HackerNews #ngated
Alibaba Cloud says it cut Nvidia AI GPU use by 82% with new pooling system— up to 9x increase in output lets 213 GPUs perform like 1,192

A paper presented at SOSP 2025 details how token-level scheduling helped one GPU serve multiple LLMs, reducing demand from 1,192 to 213 H20s.

Tom's Hardware
Alibaba Cloud says it cut Nvidia AI GPU use by 82% with new pooling system— up to 9x increase in output lets 213 GPUs perform like 1,192

A paper presented at SOSP 2025 details how token-level scheduling helped one GPU serve multiple LLMs, reducing demand from 1,192 to 213 H20s.

Tom's Hardware