AI Decoded : Solving AI Hardware, Software, and Tools

Mysteries of AI Decoded

NVIDIA hastened the transition to AI computing with the 2018 release of RTX technology and the first consumer GPU designed for AI, the GeForce RTX. With 500 AI apps and over 100 million users, the AI ecosystem for RTX PCs and workstations has flourished since then.

New capabilities are currently being introduced by generative AI, spanning from PC to cloud. Furthermore, all users will be able to manage a broad variety of AI features thanks to NVIDIA’s long experience and competence in the field of artificial intelligence.

AI on RTX is already being used by users at home and in the workplace via applications that improve productivity and enjoyment. With improved frame rates and breathtaking resolutions in their preferred games, gamers may experience the advantages of AI on GeForce RTX GPUs. Rather of repeating boring activities or staring at spinning wheels, creators may concentrate on their creative process. Additionally, developers may automate debugging and simplify processes by using generative AI for prototyping.

The AI industry is expanding quickly. AI decoded will take on more difficult duties as research progresses. And RTX will manage the rigorous performance requirements.

AI in Video Games

The biggest advances in AI decoded acceleration have been in gaming performance during the last six years. Since 2019, gamers have been able to increase frame rates and enhance picture quality by using NVIDIA DLSS. It’s a method that automatically creates pixels for video games using AI. It currently achieves up to 4x frame rate gains thanks to continuous enhancements.

Additionally, some of the best games in the world now have even better visuals because to the addition of Ray Reconstruction in the DLSS 3.5, the most recent version. This creates a new benchmark for visually richer and more engaging gameplay.

Nowadays, more than 500 games and apps that use ray tracing, DLSS, and AI-powered technologies have completely changed how people play and create.

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Beyond frames, AI decoded will enhance character interactions and allow players to replay beloved games.

With the help of NVIDIA ACE microservices, developers can now add dynamic, intelligent digital avatars to their games, such as speech and movement models driven by generative AI. Showcasing its capacity to bring game characters to life as a window into the future of PC gaming, ACE’s demonstration at CES earned them many honors.

With the help of NVIDIA RTX Remix, modders may produce breathtaking RTX remasters of vintage games. The platform offers generative AI capabilities that can convert the simple textures from vintage games into physically based, 4K-resolution rendering materials. A number of projects, such as Portal with RTX and Half-Life 2 RTX, are either in development or have already been launched.

Artificial Intelligence for Creators

By eliminating or automating laborious chores, AI decoded is enabling creativity by freeing up time for unadulterated creativity. The fastest or only supported PCs with NVIDIA RTX or GeForce RTX GPUs may use these capabilities.

RTX speeds up Adobe Premiere Pro’s Enhance Speech function, which uses AI decoded to reduce background noise and enhance speech clips so they seem professionally produced. RTX is up to 4.5 times quicker than Mac. Another Premiere tool, Auto Reframe, automatically reframes video footage for various aspect ratios by using GPU acceleration to detect and monitor the most important parts in a film.

The Magic Mask AI decoded function in DaVinci Resolve is another time-saving tool for video editors. Previously, editors had to employ a mix of rotoscoping methods or simple power windows and masks to separate the topic from the backdrop if they needed to change the color or brightness of a subject in a single shot or eliminate an unpleasant item.

That process has been entirely altered by Magic Mask. Just draw a line across the topic with it, and the AI will study it for a little while before displaying the choice. Additionally, GeForce RTX laptops may execute the function 2.5 times quicker than non-RTX laptops.

These are just a few examples of the ways artificial intelligence is accelerating creativity. RTX is presently used to accelerate over 125 AI applications.

AI for Programmers

Through scalable environments, software and hardware improvements, and new APIs, artificial intelligence is improving the way software developers create software applications.

With PC-class speed and memory footprint, NVIDIA AI Workbench enables developers to swiftly construct, test, and tweak pretrained generative AI models and LLMs. This all-in-one, user-friendly toolbox may be used on RTX PCs locally or scaled to almost any data center, public cloud, or NVIDIA DGX Cloud.

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Using NVIDIA TensorRT, a program that enables developers to fully use the Tensor Cores in RTX GPUs, developers may improve AI decoded models they have built for PC use cases.

With TensorRT-LLM for Windows, text-based apps may now take advantage of TensorRT acceleration. The open-source package improves LLM performance and comes with pre-optimized checkpoints for widely used models, such as Microsoft Phi-2, Google’s Gemma, Meta Llama 2, and Mistral.

An OpenAI Chat API TensorRT-LLM wrapper is also available to developers. Proceed with a single line of code modification. TensorRT-LLM may be used locally on an RTX PC by building an open-source autopilot for VS Code and JetBrains that taps into an LLM for quick, local LLM inference using this widely used tool.

Every week, they will provide new hardware, software, tools, and accelerations for RTX AI PC users and demystify AI decoded by making the technology more approachable.