Title
AWS re:Invent 2023 - New LLM capabilities in Amazon SageMaker Canvas, with Bain & Company (AIM363)
Summary
- Shyam Srinivasan, a principal product manager at AWS, and Purna Doddapareni, a partner at Bain & Company, presented new features in Amazon SageMaker Canvas.
- SageMaker Canvas is a no-code workspace for business users to utilize machine learning (ML) for solving business problems.
- The session introduced new capabilities for data preparation using large language models (LLMs) without writing code.
- A new feature called "Chat for Data Prep" allows users to interact with data using natural language to query, visualize, and transform data.
- Users can import data from various sources, including on-premise, AWS data lakes, and third-party data services.
- SageMaker Canvas offers a choice of LLMs from Amazon Bedrock and open-source models from SageMaker Jumpstart.
- Data security is emphasized, with data remaining secure within the user's environment.
- Fine-tuning of LLMs is now possible without coding, allowing customization of model outputs for specific industries or use cases.
- Purna Doddapareni shared examples of how Bain & Company leverages these new features in their ventures, highlighting the convergence of low-code/no-code solutions and generative AI.
- The session concluded with a call to action for attendees to try SageMaker Canvas and provide feedback.
Insights
- The integration of LLMs into SageMaker Canvas represents a significant step towards democratizing AI, making it accessible to non-technical business users.
- The "Chat for Data Prep" feature reflects a trend towards more intuitive and natural interactions with technology, where English is humorously referred to as the "latest and best programming language."
- The ability to fine-tune LLMs within SageMaker Canvas without coding can accelerate the adoption of AI across various industries by allowing customization to specific business needs.
- The examples provided by Bain & Company demonstrate real-world applications of these new features, showcasing their potential to solve complex business problems and reduce reliance on scarce technical talent.
- The emphasis on data security within the user's environment addresses growing concerns about data privacy and compliance in the AI space.
- The session highlighted the importance of collaboration between business and technical teams, suggesting that tools like SageMaker Canvas can facilitate better communication and more efficient workflows.
- The presentation suggests a growing market for low-code/no-code and generative AI solutions, with organizations increasingly looking to empower non-technical users to contribute to technical solutions.