Unlock the power of generative AI: Simplify ad creation with AWS (AMZ303)

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Unlocking the Power of Generative AI and Simplifying Ad Creations with AWS

Introduction

  • Presentation by Gary Ginksy and Nikhil Nikar on the impact of generative AI on Amazon and Amazon Ads.
  • Aim is to explore how generative AI has impacted Amazon and focus on Amazon Ads.
  • This is a 300-level course, diving deep into the architecture and building blocks used to accelerate generative AI development.

Technological Transformation

  • Witnessed a significant shift in the past 12 months, from generative AI being an emerging concept to a widespread adoption.
  • Conversations have shifted from "what is generative AI?" to "how do we scale, go bigger, and accelerate innovation?"
  • This is a paradigm shift, not just technological progress.
  • AWS has been at the forefront of offering comprehensive solutions and services to support generative AI.

Generative AI at Amazon

  • Gary's unique role as a Solutions Architect supporting Amazon as a customer on AWS.
  • Amazon is using generative AI to empower employees and create innovative solutions for customers and partners.
  • Examples:
    • Rufus: An AI-powered shopping assistant
    • Maintenance Engineers using generative AI assistance
    • Customer service training using AI-powered synthetic personas

Generative AI in Amazon Ads

  • Nikhil's presentation on delivering generative AI solutions for Amazon Ads customers.
  • Identified a content gap and creative barrier in Amazon's advertising ecosystem.
  • Launched the Image Generator, a quick and easy way for brands to generate images for their campaigns.

Technical Deep Dive

  • Workflow diagram of the Image Generator architecture:
    • Product feature extraction
    • Product image selection and segmentation
    • Responsible AI guard rails
    • Fine-tuned language model for automatic prompt generation
    • Text-to-image generation model
    • Image upscaling and responsible AI filtering
    • Multiple image generation and selection
  • Iterative prototyping and development process using Amazon SageMaker.
  • Responsible AI integration as a core component of the workflow.

Expanding the Offerings

  • Introduced Live Images, a feature that leverages generative AI to add subtle camera motion and Parallax effects to product shots.
  • Developed an Image Editing workflow to allow advertisers to edit the generated images.
  • Launched a Video Generator, leveraging the existing architecture to generate videos for advertisers.

Streamlining the Development Process

  • Identified challenges in the prototyping to production process, including the "lost in translation" problem.
  • Developed a custom SDK with declarative annotations (e.g., @workflow, @task) to streamline the process.
  • Introduced a declarative workflow definition, allowing scientists to focus on building the workflows without worrying about the underlying infrastructure.
  • Leveraged AWS services like Lambda, Fargate, and Boto3 to optimize the deployment and execution of the workflows.

Business Impact

  • Advertisers using AI-powered creative solutions saw:
    • 5x more products advertised
    • 2x more images per advertised product
    • 177% increase in return on ad spend
    • 8% higher click-through rate
    • 4% lift in sales
    • 88% more campaign creation

Key Takeaways

  • Separate offline and online workloads for independent scaling controls.
  • Develop a custom SDK and declarative workflow model to streamline the prototyping to production process.
  • Leverage AWS services like Lambda, Fargate, and Boto3 to optimize the deployment and execution.
  • Ensure that infrastructure changes are transparent to stakeholders.

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