Title

AWS re:Invent 2023 - Building a cloud-backed generative AI game in 60 minutes (COM201)

Summary

• Ben Elleby, CTO of Alios and AWS Serverless Hero, presents a session on building a generative AI game called EmojiOS in 60 minutes.
• Generative AI is used to create various types of content, including text, images, and data, based on patterns from existing data.
• The game EmojiOS challenges players to guess a book or movie from a set of emojis, with scoring based on semantic similarity rather than exact matches.
• Key steps in building generative AI applications include model selection, hosting, prompt engineering, and application integration.
• Criteria for model selection include medium, fine-tuning, task complexity, provision throughput, tokens per call, and cost.
• AWS Bedrock is highlighted as a fully serverless hosting solution that integrates with other cloud services.
• Prompt engineering is described as an art of creating natural language instructions to guide AI models, with techniques ranging from zero-shot to few-shot prompts.
• Inference parameters such as temperature, topK, topP, response length, and stop sequences are important for controlling AI model outputs.
• The architecture of the EmojiOS game is serverless, utilizing AWS services like CloudFront, S3, API Gateway, Lambda, DynamoDB, and EventBridge.
• The AWS SDK and Langchain framework are used for interacting with the AI models.
• Embeddings models are used for scoring by calculating the semantic similarity between vectors representing the input and the user's guess.
• The session concludes with a Q&A session and a mention of a DNS issue that prevented sharing a QR code for the game, which will be shared later on social media.

Insights

• Generative AI is becoming increasingly accessible and can be used for a wide range of creative and business applications.
• AWS provides a robust ecosystem for building and hosting generative AI applications, with serverless architecture being a key enabler for rapid development and scalability.
• Prompt engineering is a critical skill for working with generative AI, requiring a balance between creativity and predictability to achieve desired outputs.
• Inference parameters play a significant role in the quality of generative AI outputs, and understanding how to adjust them is crucial for developers.
• The use of embeddings and vector similarity for scoring in AI applications is an innovative approach that can provide nuanced and context-aware results.
• The session demonstrates the practical application of generative AI in a fun and engaging way, showcasing the potential for AI to transform gaming and other interactive experiences.