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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.