The benefits of Graphics Cards for Generative AI

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Generative AI is a part of artificial intelligence that focuses on creating new content or data from scratch, such as images, text, music, or code. Generative AI can be used for various applications, such as content creation, data augmentation, style transfer, image synthesis, and more. However, generative AI often requires a lot of computational power and memory to handle large and complex models and datasets. This is where having a professional Nvidia RTX graphics card in your Lenovo Workstation can make a difference.

The latest Nvidia RTX graphics cards are powered by the Nvidia Ada Lovelace architecture, which is designed to deliver breakthroughs in generative AI and other professional workflows. Nvidia RTX graphics cards have several features that make them ideal for generative AI, such as:

• CUDA Cores: These are the basic units of parallel processing on Nvidia GPUs, which can perform single-precision floating-point (FP32) operations at high speed. Nvidia RTX graphics cards have up to 12,800 CUDA cores, which is twice the number of the previous generation. This means that they can handle more complex and realistic graphics and simulation tasks, such as 3D modeling, rendering, and animation.
• RT Cores: These are specialized units that accelerate ray tracing, which is a technique that simulates the behavior of light and shadows in a scene. Ray tracing can create photorealistic images and videos, but it is also very computationally intensive. Nvidia RTX graphics cards have up to 100 RT cores, which can perform ray tracing operations up to twice as fast as the previous generation. This means that they can render high-quality images and videos in real time, which is useful for applications such as virtual reality, augmented reality, and game development.
• Tensor Cores: These are specialized units that accelerate deep learning, which is the core technology behind generative AI. Deep learning involves training and running neural networks, which are composed of layers of mathematical operations. Tensor Cores can perform these operations at high speed and accuracy, using different levels of precision, such as FP32, FP16, or INT8. Nvidia RTX graphics cards have up to 400 Tensor Cores, which can perform deep learning operations up to four times faster than the previous generation. This means that they can train and run generative AI models faster and more efficiently, which is useful for applications such as image synthesis, style transfer, text generation, and more.

Some examples of applications that utilize the power of Nvidia RTX graphics cards for generative AI are:

• Adobe After Effects: Digital visual effects, motion graphics, compositing and animation for post-production in film, television, gaming and entertainment. CUDA acceleration for up to 10x faster performance on key effects plus enhanced 3D ray tracing.
• Adobe Photoshop: Combine, retouch, and remix your pics. Add new color to your old black-and-whites. Make unwanted stuff disappear. Or turn a boring background into an exotic paradise. With Photoshop, everyone can Generative Fill and Generative Expand GPU-accelerated AI "Neural Filters" + over 30 other GPU accelerated features, like Blur gallery, liquify, smart sharpen and perspective warp.
• Adobe Lightroom Classic: Easily organize all your photos on your desktop and share them in a variety of ways with this desktop editing tool. You get GPU accelerated Develop module + new Sensei features like "Enhance Details" with NVIDIA GPU AI optimization. With RTX Technology it is up to 600% faster than with an integrated GPU for controlling Texture, Dehaze, & Sharpening.
• Autodesk 3Ds Max: 3ds Max professional 3D modeling, rendering, and animation software enables you to create expansive worlds and premium designs. Get the availability of Arnold with AI denoising and NVIDIA OptiX Chaos V-Ray, Otoy Octane, Maxon Redshift, Cebas final Render and third-party GPU renderers.
• Dassault Systemes SOLIDWORKS Visualize: SOLIDWORKS Visualize allows users to share real-time market development information, including high-quality graphical assets, interactive 3D content, and photorealistic renders with their sales and marketing teams before any product has been physically manufactured. You get Iray-based ray-tracing, Animation support, Network rendering and OptiX-based Artificial Intelligence denoiser.
• Blackmagic Design DaVinci Resolve: This All-in-one software tool combines editing, color correction, visual effects, motion graphics and audio post production with an easy-to-use interface. You get Real-time color correction and de-noising with RTX-accelerated AI features for re-timing and image enhancement.

These are just a selected few of the almost 1600 applications that incorporates Nvidia RTX technology into their workflow, either by making use of the powerful RT or Tensor cores. Nvidia also provides additional software like NVIDIA Broadcast, a suite of AI features that enhance live streaming and video conferencing. NVIDIA Broadcast can use RTX graphics cards to perform tasks such as virtual background, noise removal, and eye contact, which can improve the quality and immersion of online communication. NVIDIA Studio is another suite of AI tools that supercharge content creation. NVIDIA Studio can use RTX graphics cards to perform tasks such as upscaling, denoising, ray reconstruction, and more, which can improve the speed and quality of creative workflows. NVIDIA Studio also supports over 100 creative apps, such as Adobe Creative Cloud, Blender, Blackmagic Davinci Resolve, OBS Studio, and more.

In addition Lenovo provides off-the-shelf solutions all AI and Data science ready. Lenovo ThinkStation P5, P7, P8 and PX are all purpose build with AI in mind, featuring some of the ultimate CPUs available in the market right now, such as Intels XEON W and SP lineup not to mention the powerful AMD Threadripper Pro CPUs just launched for the ThinkStation P8.

In conclusion, having an Nvidia RTX graphics card in combination with a powerful workstation from Lenovo, can provide significant benefits for generative AI and other professional workflows. Nvidia RTX graphics cards can deliver industry-leading performance, thanks to their advanced features, such as CUDA Cores, RT Cores, and Tensor Cores. Nvidia RTX graphics cards can also enable various applications that utilize generative AI, such as NVIDIA Broadcast and NVIDIA Studio. Therefore, having an Nvidia RTX graphics card can be a valuable asset for anyone who wants to explore the possibilities of generative AI..

The best value for money graphics card design for AI in mind: Nvidia RTX 5000 Ada Generation Graphics Card | NVIDIA. https://www.nvidia.com/en-us/design-visualization/rtx-5000/.

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