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What is Project G-Assist?

NVIDIA has launched Project G-Assist, an innovative AI assistant designed to enhance the gaming experience for GeForce RTX users by providing system optimizations, real-time diagnostics, and customizable peripheral controls through simple voice or text commands. Integrated into the NVIDIA app, G-Assist automatically adjusts game settings for optimal performance or visual fidelity, monitors and showcases key performance metrics like frame rates and system latency, and manages lighting effects on compatible devices from brands such as Logitech, Corsair, MSI, and Nanoleaf. Leveraging a locally-based Small Language Model (SLM), G-Assist ensures swift responses and operates efficiently without needing an internet connection. Users can easily engage G-Assist via the NVIDIA app overlay or by pressing Alt+G, utilizing the GeForce RTX GPU for AI inference tasks. Furthermore, developers and tech aficionados can expand G-Assist's capabilities through a community-driven plugin framework, which offers extensive resources and example plugins for inspiration. This progressive strategy not only empowers gamers but also cultivates a collaborative ecosystem for the continuous enhancement of the gaming experience, encouraging a shared journey of innovation and creativity in the gaming community.

What is Nemotron 3.5 Lightning?

NVIDIA's Nemotron 3.5 Lightning represents an advanced mixture-of-experts model that features an impressive 30 billion parameters, with 3 billion of these actively engaged, and is specifically designed to deliver efficient, high-throughput performance for AI agents that operate continuously over extended periods. This model is crafted for the execution aspects of agentic systems, skillfully handling common tasks such as invoking tools, verifying outputs, carrying out routine commands, and assigning responsibilities to subagents, while larger reasoning models focus on strategic planning and orchestration. By utilizing a mixture-of-experts framework, it selectively engages a limited number of parameters for each input token, effectively combining the vast potential of a larger model with substantially decreased computational requirements. The training process is fine-tuned for popular agent harnesses, significantly improving inference speed through methods like speculative decoding, multi-token prediction, DFlash, and DSpark, which enhance its adaptability to various operational contexts. Moreover, it supports BF16 and NVFP4 checkpoints, ensuring deployment flexibility across platforms ranging from local systems such as DGX Spark and GeForce RTX hardware to large-scale data center environments. This innovative design not only amplifies AI capabilities but also positions Nemotron 3.5 Lightning as a pivotal resource for the evolution of intelligent systems, paving the way for future advancements in the field.

Media

Media

Integrations Supported

Gemini
Gemini Enterprise
Hermes Agent
Logitech Capture
NVIDIA NemoClaw
OpenClaw

Integrations Supported

Gemini
Gemini Enterprise
Hermes Agent
Logitech Capture
NVIDIA NemoClaw
OpenClaw

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/software/nvidia-app/g-assist/

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

nvidia.com

Categories and Features

Categories and Features

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