Harnessing the Power of Generative AI for Automotive Technologies on AWS

Generative AI for Automotive to Empower Software Defined Vehicles and Autonomous Mobility

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across the automotive and manufacturing industries are transforming their businesses. Just recently, generative AI applications have captured widespread attention and imagination. But chatbots powered by generative AI are just the beginning; to truly impact the industry and, by extension, consumers, companies will need to embrace the possible and empower their developers with the tools needed. We are at an exciting inflection point in the widespread adoption of ML, and we believe most customer experiences and applications will be reinvented with generative AI.

In the automotive industry, generative AI has the potential to help transform the way vehicles are designed and developed.  Generative AI is a new approach where artificial intelligence can be applied to create new content and ideas, including exploring design options, based on criteria that has been stipulated by the developer. Like all AI, generative AI is powered by ML models—very large models that are pre-trained on vast amounts of data and commonly referred to as foundation models (FMs). Today’s FMs, such as the large language models (LLMs) GPT3.5 or BLOOM, and the text-to-image model Stable Diffusion from Stability AI, can perform a wide range of tasks that span multiple domains, like writing blog posts, generating images, solving math problems, engaging in dialog, and answering questions based on a document. When applied to the automotive development process, generative AI could help automakers quickly identify the best design options for complex systems such as engines, lightweight structures, and vehicle features. By using AWS services, automotive manufacturers can now access the powerful computing resources needed to help scale their generative AI capabilities. In this blog post, we will take a cursory look at how generative AI can help OEMs with software development and in designing, training, and testing automated and autonomous driving systems. These are, after all, new technologies that we are enthusiastically exploring and integrating where possible.

Generative AI and the Journey towards Software Defined Vehicles

The automotive industry is increasingly adopting Software Defined Vehicles (SDVs) with millions of lines of code as they provide a more flexible and responsive solution for customers. SDVs have the ability to update and upgrade vehicle features through over-the-air (OTA) updates, similar to how smartphones are updated with new features and become better products over time. Generative AI can be used to create and optimize the software and control systems, as well as to help improve the performance of the vehicle’s hardware. As a vehicle’s code increases in complexity, it is important for software engineers to focus on developing new, innovative functionalities and not spend their time trying to keep up with a complex and ever-changing tool and technology landscape. Automotive customers can use Amazon CodeWhisperer, an AI coding companion that uses generative AI to help improve developer productivity by generating code suggestions in real-time based on developers’ comments in natural language and prior code in their Integrated Development Environment (IDE). Amazon CodeWhisperer analyzes existing code in the IDE (whether generated by CodeWhisperer or written by the developer), identifies problematic code with high accuracy, and provides intelligent suggestions on how to remediate it.

Using Generative AI to Help Take You to Your Destination

The journey towards highly automated and autonomous mobility is a major focus of the automotive industry. Autonomous driving requires complex software and hardware systems that must be designed to work seamlessly together. Generative AI can be an important tool in designing and testing these systems. For example, generative AI may be used by OEMs to create simulations that test the vehicle’s response to various driving scenarios. These scenarios and the accompanied simulated test data can be edge cases that statistically happen so rarely as to not be represented in typical circumstances, or so extreme as to be unsafe to test in real-world (e.g. near miss of a pedestrian crossing at night, in the rain, in the dark). This is not just an efficiency improvement but will also allow automotive companies to create more test scenarios with the potential to improve the overall system capabilities.

How the cloud and AWS can help?

AWS is focused on making it easy for our customers to leverage ML and AI, and so now we are making sure AWS is the easiest place to build with generative AI. Amazon Bedrock is a new service that makes FMs from Amazon and leading AI startups including AI21 Labs, Anthropic, and Stability AI accessible via an API. Amazon Bedrock is the easiest way for customers to build and scale generative AI-based applications using FMs, democratizing access for all builders. Bedrock (currently available in limited preview) will offer the ability to access a range of powerful FMs for text and images.

Generative AI requires a large amount of computational resources and data, which can be costly and time-consuming to acquire and manage. Whatever customers are trying to do with generative AI FMs—running them, building them, customizing them—they need performant, cost-effective infrastructure that is purpose-built for ML. AWS customers use Amazon EC2 Trn1 instances, powered by Trainium, which help to deliver up to 50% savings on training costs over any other EC2 instance. Once the generative AI models are deployed at scale, most costs will be associated with running the models and doing inference. This is when customers can use Amazon EC2 Inf2 instances powered by AWS Inferentia2, which are optimized specifically for large-scale generative AI applications with models containing hundreds of billions of parameters.

To learn more about AWS purpose built solutions for Automotive customers, please visit here. And, for more specific information on AWS’s approach to generative AI, please visit here.