Join NVIDIA's @GeForce_JacobF as we check out the new @ASUS ProArt P16 & P14 laptops, powered by the RTX Spark superchip. 🔥💻 P16: 16" 4K 120Hz OLED💻 P14: 14" 3K 120Hz OLED✨ ASUS Lumina Pro touchscreens (1600 nits!)🤫 Triple heat pipe cooling at just ~40 dBWhich one are you picking? 👇

We took a 30B model and split it in two to write tokens in parallel instead of one at a time.Introducing Nemotron-Labs-TwoTower: a diffusion language model from NVIDIA Research adapted from Nemotron-3-Nano-30B-A3B. Here’s how it works: one half holds the context, the other writes the tokens, with both reusing the pretrained model instead of training a new one from scratch.We found it kept 98.7% of the original model’s quality at 2.42× faster generation.

Before the #XboxShowcase kicks off...A GeForce RTX 5080 is up for grabs 👀Comment #RTXPowersPlay to enter for a chance to WIN.

RTX Spark laptops are Game Ready, featuring support for: 🟢 The full DLSS suite + ray tracing🟢 Reflex 🟢 G-SYNC+ More NVIDIA gaming features, all packed into a slim design.

Everything to know about RTX Spark in less than 90 seconds:- Personal AI agents- Faster creator workflows- RTX ON gamingAll in thin and light laptops, and SFF desktops.

This represents a huge swath of the AI community. I’m glad to see more creators and users focusing on it. Sure, we all love the NVIDIA RTX PRO 6000 Blackwell with its 96 GB of GDDR7 VRAM, the rumored Mac Studio M5 Ultra with 768 GB of RAM, and the other high-end gear, just like we love Ferraris, McLarens, and Lamborghinis.But the reality for most is closer to an old Honda Civic. To attract more people, young and old, of modest means, who want to run local models on their own limited rigs, we nee

Get a performance upgrade… on the hardware you already own. ✨✨Harness the power of a GeForce RTX rig in the cloud, giving you instant access to over 4,500 titles on nearly any device.Deal ends soon ➡️ https://t.co/oWls6qj6aB

NVIDIA'S RTX 5090 PUSHES 1.79 TB/S OF MEMORY BANDWIDTH AGAINST APPLE M4 MAX AT 546 GB/S AGAINST AN A100 AT 2 TB/S, A FULL LADDER FROM CONSUMER TO ENTERPRISE THAT MAPS THE TRADEOFFS NOBODY EXPLAINS04:40 holding up his macbook he runs through the spec, "this laptop has 64 gigs of unified ram, it's an m1 max, 400 gigabytes per second"memory bandwidth is the metric for llm inference, not raw compute, a 70b parameter model only generates as fast as the gpu can stream weights from vram between every t