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  • Writer's pictureBig Data Ben

How AI and even LLMs can help drive cars

October 9, 2023

Have you ever wondered how self-driving cars can navigate the complex and unpredictable traffic situations on the road? How do they know what other drivers, pedestrians, cyclists, and animals are going to do next? How do they avoid collisions and accidents?

Well, one of the key technologies behind this amazing feat is artificial intelligence (AI), which is the ability of machines to learn from data and perform tasks that normally require human intelligence. AI can help cars understand their surroundings, plan their routes, and make decisions in real time.

One of the leading companies in the field of self-driving cars is Waymo, which is a subsidiary of Google. Waymo has been developing and testing its autonomous vehicles for over a decade, and has accumulated more than 20 million miles of driving experience on public roads.

Recently, Waymo has introduced a new AI system called MotionLM, which stands for Motion Language Model. This system can predict the future behavior of multiple road agents, such as cars, bikes, pedestrians, etc., by treating their motions as a language. Just like humans can guess what someone is going to say next based on the context and the previous words, MotionLM can guess what someone is going to do next based on the scene and the previous actions.

MotionLM is different from other existing methods that try to predict the behavior of road agents separately, without considering how they interact with each other. MotionLM can capture the joint distribution of multiple agents' actions, which means it can account for the dependencies and influences among them. This way, it can generate more realistic and consistent predictions that can help self-driving cars plan safer and smoother maneuvers.

MotionLM is also simpler and easier to train than other methods that rely on complicated techniques such as anchors or latent variables. MotionLM uses a simple language modeling objective, which is to maximize the probability of correctly predicting the next motion token in a sequence. MotionLM can learn from large amounts of data without any predefined rules or concepts.

MotionLM is a state-of-the-art multi-agent motion prediction approach that can make it possible for large language models (LLMs) to help drive cars. LLMs are powerful AI systems that can generate natural language texts based on a given input or prompt. LLMs have been used for various applications such as writing, summarizing, translating, answering questions, etc. Now, with MotionLM, LLMs can also help drive cars by understanding and predicting the language of motion.

This is an exciting development in the field of AI and self-driving cars, and we can expect to see more innovations and improvements in the future. Waymo's MotionLM is a great example of how AI can help cars drive better and safer on the road. Stay tuned for more on the latest news and developments in AI!

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