From Pixels to Pavements: Use Cases for Generative AI in the Automotive Industry
Oddly enough, my son gave me styling tips, started writing out high-intensity daily workout plans to keep old men in shape, and started sharing stock trading tips like a pro. Did. But miracle miracle, he also wrote poetry and stopped asking for help with his homework. With all that said, ChatGPT, the natural language processing (NLP)-based AI chatbot that’s changing everything, doesn’t really know whether to send flowers or brick bats. (So my son is a poet?)
Nodding to its massive appeal, ChatGPT has amassed 100 million users within two months of its launch, beating out the highly successful game-changer automatic rice cooker in 1950s Japan. (And yes, ChatGPT can flat Please tell me how to cook perfect rice. In another milestone, GPT-3-based models increased from 1 to 300,000, despite MarketsnMarkets estimating that the market size will grow rapidly from $11.3 billion in 2023 to $51.8 billion by 2028. It took me only 6 months to do it. In addition, deals closed – from 65 deals worth $271 million to over 110 deals worth $2.6 billion – underscore the rapid rise in valuations of generative AI companies .
The technology roadmap (Figure 1) is similarly tumultuous, shifting focus from text and coding to images and video, and eventually to fully autonomous generative AI systems. The sheer pervasiveness and power of this technology will underscore the need for strong ethical and regulatory safeguards, leading to an almost endless number of use cases.
Generative technology roadmap
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A World of Infinite Possibilities
Generative AI tools, consisting of large-scale language AI models and image AI models, have opened up a world of possibilities for the content creation industry. These include automating content generation, improving content quality, diversity, accuracy and relevance, and enhancing content personalization. Generative AI models leave all areas of content creation untouched, including marketing, software, design, entertainment, and interpersonal communication.
Markets and Markets recently conducted several roundtables in the EU and US. As a result, it has gone from supporting productivity gains, initially in areas such as content creation, to delivering operational and resource efficiencies in areas such as predictive maintenance, and, ultimately, in areas such as pharmaceutical and product development. We have found that this leads to support for long-term innovation. , the use cases for generative AI will only increase in parallel with the expansion of its capabilities (Figure 2).
Use cases for generative AI in the B2B sector
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Needless to say, the auto industry will also benefit greatly.
Generative AI and the future of the automotive industry
Generative AI is widely considered to be the key to unlocking the future of true autonomous vehicles (AVs). In April 2023, Chinese technology start-up Haomo.AI, backed by Great Wall Motors, launched DriveGPT, an autonomous driving assistance platform based on generative large-scale models (LLM). The platform combines reinforcement learning from human feedback (RLHF) with real-world manual driving data to enhance cognitive decision-making capabilities in autonomous driving.
Generative AI models support three important avenues of AV research and development: simultaneous generation of multiple scenarios, prediction of future vehicle trajectories, and sophistication of the decision-making inference chain. By introducing algorithms to generate new content such as images, videos, and even text, Generative AI can create virtual environments and simulate real-world scenarios, allowing AV to create safe and controlled environments. You will be able to learn and adapt.
AV development requires accurate and reliable sensor data for training purposes. Generative AI generates large amounts of synthetic data representing real-world driving scenarios, eliminating the need for costly and time-consuming field testing. Moreover, real-time decision making in AVs is based on a wide range of inputs such as sensor data, traffic patterns, and pedestrian behavior. By generating massive amounts of data, generative AI helps create more sophisticated and actionable algorithms that can be used to train decision-making models.
Beyond AV, generative AI will play a central role in pushing the boundaries of vehicle personalization. For example, Faraday Future Intelligent Electric (FF)’s recently announced generative AI product stack represents a use case for full-stack generative AI software that enhances the cockpit domain to personalize driver services and experiences. Common features include intelligent search, text queries, translations, and recommendations for video/audio entertainment choices.
Generative AI further extends the idea of personalization by learning and predicting user preferences. Examples include route predictions and customized marketplace and service recommendations along the route, even though the user doesn’t need to enter a destination. Imagine the joy of having destinations and routes suggested based on the time of day or your favorite coffee bar, with minimal effort.
A prominent future use case will be in-vehicle personal assistants with generative AI, so to speak, like Siri on steroids or Alexa on Acid. Essentially, it’s an intelligent personal assistant with conversational and other support capabilities, much like what SoundHound introduced with its generative AI voice assistant for automotive solutions.
Elsewhere, generative models are effectively applied across marketing and advertising departments to create more meaningful customer engagement. For example, Jasper, a generative AI tool built on GPT-3, can churn out sales emails, blogs, social media posts, and other customer-centric marketing content. Image generation models like the DALL-E 2 are getting a lot of attention in advertising. For auto companies that have traditionally spent a disproportionate amount of money on marketing with little to no effect, generative AI is expected to better track and deliver on that spending. increase.
Beyond marketing, generative AI applications across the manufacturing and supply chains support cost optimization, delivering significant savings directly to the bottom line.
And finally, there is the issue of product development. The auto industry typically spends him over $1 billion over the course of a few years developing new products, and there’s no guarantee the bet will pay off. Generative models have the potential to shorten the time between design, development and delivery due to their superior ability to synthesize and analyze data, detect patterns and predict outcomes. In fact, it could potentially reduce the time required to develop the platform/architecture and manufacture a new electric vehicle (EV) by at least 3-6 months.
A winning combination: human imagination and innovation
The World Economic Forum’s Future of Work Report 2023 estimates that nearly 43% of tasks will be performed by machines by 2027. Finance, banking, administration, business, insurance, marketing, management, sales, automotive, IT, health, retail, media, sports, travel…no industry remains untouched. Writers, designers, poets, artists… no creative pursuit is ever left in isolation.
In April of this year, Boris Erdagsen was selected as the winner of the Sony World Photography Awards in the ‘Creative Photography’ category. He declined to accept the award, stating that it was generated by his AI. His gesture was meant to provoke a debate about whether AI-generated images can be considered art. What is technology worth without human imagination and creativity? Will such powerful technology empower or undermine human ingenuity?
As the boundaries blur and the human experience shifts, the debate around generative AI (its enormous benefits and risks) will only become more complex. It takes a great combination of human imagination and technological innovation to successfully tackle this wonderful new world. In the meantime, I can only hope my son doesn’t hallucinate that he wants to be the next Poet Laureate.
For the purpose of full disclosure, this article is titled courtesy of ChatGPT.
This article is an excerpt from the recent market and market report Generative AI Market, contributed by Rounak Singh and Sushmit Chakraborthy
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