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  • How Formula 1® uses generative AI to accelerate race-day issue resolution
    by Carlos Contreras on February 18, 2025 at 21:08

    In this post, we explain how F1 and AWS have developed a root cause analysis (RCA) assistant powered by Amazon Bedrock to reduce manual intervention and accelerate the resolution of recurrent operational issues during races from weeks to minutes. The RCA assistant enables the F1 team to spend more time on innovation and improving its services, ultimately delivering an exceptional experience for fans and partners. The successful collaboration between F1 and AWS showcases the transformative potential of generative AI in empowering teams to accomplish more in less time.

  • Using Amazon Rekognition to improve bicycle safety
    by Mike George on February 17, 2025 at 16:51

    To better protect themselves, many cyclists are starting to ride with cameras mounted to the front or back of their bicycle. In this blog post, I will demonstrate a machine learning solution that cyclists can use to better identify close calls. The architecture of the solution uses Amazon Rekognition to detect vehicles in recorded bike ride videos. It then analyzes the video to determine if any vehicles are passing too close to the cyclist, within the 3-foot safe distance required by law. The solution automatically generates video clips of these dangerous passing events, which can then be shared with authorities to help improve cyclist safety.

  • Build a dynamic, role-based AI agent using Amazon Bedrock inline agents
    by Ishan Singh on February 13, 2025 at 20:56

    In this post, we explore how to build an application using Amazon Bedrock inline agents, demonstrating how a single AI assistant can adapt its capabilities dynamically based on user roles.

  • Use language embeddings for zero-shot classification and semantic search with Amazon Bedrock
    by Tom Rogers on February 13, 2025 at 20:53

    In this post, we explore what language embeddings are and how they can be used to enhance your application. We show how, by using the properties of embeddings, we can implement a real-time zero-shot classifier and can add powerful features such as semantic search.

  • Fine-tune LLMs with synthetic data for context-based Q&A using Amazon Bedrock
    by Sue Cha on February 12, 2025 at 17:44

    In this post, we explore how to use Amazon Bedrock to generate synthetic training data to fine-tune an LLM. Additionally, we provide concrete evaluation results that showcase the power of synthetic data in fine-tuning when data is scarce.

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