@Automotive NewsAugust 2023 - Detailled Explanation: ✓ Generative AI Revs Up New Age in Auto Industry, From Design and Engineering to Production and Sales. ✓ Automative New August 2023. ✓ Detailled Explanation ✓ New Age in Auto Industry ✓ From Design And Engineering to Production and Sales

Automotive NewsAugust 2023 Generative AI Revs Up New Age in Auto Industry, From Design and Engineering to Production and Sales

 Advances in AI revolutionize the vehicle lifecycle, boosting productivity and sparking innovation. 

 Advances in AI revolutionize the vehicle lifecycle, boosting productivity and sparking innovation. Generating content and code. Creating images and videos. Testing algorithms with synthetic data.

 Generative AI is a force multiplier enabling leaps in productivity and creativity for nearly every industry, particularly transportation, where it’s streamlining workflows and driving new business.

 Across the entire auto industry, companies are exploring generative AI to improve vehicle design, engineering, and manufacturing, as well as marketing and sales.

For vehicle interiors, large language models for text-to-image generation can enable designers to type in a description of a texture, like a floral pattern, and the generative AI will put it onto the surface of a seat, door panel or dashboard. If a designer wants to use a particular image to generate an interior design texture, generative AI can handle image-to-image texture creation. Generative AI Riding Shotgun on Concept and Styling

 Design-oriented enterprises can use visual datasets and generative AI to assist their work across many fronts. This has already been achieved with coding tools such as GitHub Copilot — trained on billions of lines of code — and similarly promises to help compress lengthy design timelines.

 In particular, when looking for “scrap” design elements, generative AI models can be trained on an automaker’s portfolio as well as vehicles industrywide, assisting this workflow. This can happen first by fine-tuning a small dataset of images with transfer learning, and then by tapping into NVIDIA TAO Toolkit. Or it might require a more robust dataset of some 100 million images, depending on the requirements of the generative AI model.

 In this bring-your-own-model setup, design teams and developers could harness NVIDIA Picasso — a cloud-based foundry for building generative AI models for visual design — with Stable Diffusion.

 In this case, designers and artists prompt the generative AI for design elements, such as “rugged,” “sophisticated” or “sleek.” It then generates examples from the external world of automakers as well as from a company’s internal catalogs of images, vastly accelerating this initial phase.

 For vehicle interiors, large language models for text-to-image generation can enable designers to type in a description of a texture, like a floral pattern, and the generative AI will put it onto the surface of a seat, door panel or dashboard. If a designer wants to use a particular image to generate an interior design texture, generative AI can handle image-to-image texture creation

 Beyond the automotive product lifecycle, generative AI is also enabling new breakthroughs in autonomous vehicle (AV) development. Such research areas include the use of neural radiance field (NeRF) technology to turn recorded sensor data into fully interactive 3D simulations. These digital twin environments, as well as synthetic data generation, can be used to develop, test and validate AVs at incredible scale.

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