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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 NVIDIA Llama Nemotron?

The NVIDIA Llama Nemotron family includes a range of advanced language models optimized for intricate reasoning tasks and a diverse set of agentic AI functions. These models excel in fields such as sophisticated scientific analysis, complex mathematics, programming, adhering to detailed instructions, and executing tool interactions. Engineered with flexibility in mind, they can be deployed across various environments, from data centers to personal computers, and they incorporate a feature that allows users to toggle reasoning capabilities, which reduces inference costs during simpler tasks. The Llama Nemotron series is tailored to address distinct deployment needs, building on the foundation of Llama models while benefiting from NVIDIA's advanced post-training methodologies. This results in a significant accuracy enhancement of up to 20% over the original models and enables inference speeds that can reach five times faster than other leading open reasoning alternatives. Such impressive efficiency not only allows for tackling more complex reasoning challenges but also enhances decision-making processes and substantially decreases operational costs for enterprises. Furthermore, the Llama Nemotron models stand as a pivotal leap forward in AI technology, making them ideal for organizations eager to incorporate state-of-the-art reasoning capabilities into their operations and strategies.

Media

Media

Integrations Supported

Gemini
Llama
Logitech Capture
NVIDIA AI Data Platform
NVIDIA AI Enterprise
NVIDIA Blueprints
NVIDIA DGX Cloud
NVIDIA NIM
NVIDIA NeMo

Integrations Supported

Gemini
Llama
Logitech Capture
NVIDIA AI Data Platform
NVIDIA AI Enterprise
NVIDIA Blueprints
NVIDIA DGX Cloud
NVIDIA NIM
NVIDIA NeMo

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

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

www.nvidia.com/en-us/ai-data-science/foundation-models/llama-nemotron/

Categories and Features

Categories and Features

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