Amazon, and its partner, Adastra offered a one day AI overview in Toronto recently. It was a hot topic that the presenters encapsulated well. Of course, they had an AWS bias and promoted Amazon’s services, but the context and implications were presented succinctly and clearly.
Below is a synopsis of the day’s presentations on Amazon’s Generative AI (Artificial Intelligence).
AWS (Amazon Web Services – the Cloud division of Amazon) Options:
1- Powered by Amazon’s Bedrock model
These are sitting on a host of services like Amazon Titan, Cohere, Meta’s Llama 3 and many more
AAS (as a service)/managed service and no overhead
2- Amazon SageMaker
Which is a ‘build your own’ platform
Amazon emphasises, however, that not one LLM fits all. It is important to assess your needs.
New Announcement: Amazon Q (an AI powered assistant)
Designed for business use cases | you can ask questions from it now
Use Cases:
- CX/EX: onboarding, KYC, Routing, etc.
- Personalization: Forecast/advisory, recommend
- Text Analytics: Extract information from internal and external sources e.g. in the old days we had OCR with rules on top
- Predictive Analytics: Extract data
- Fraud Detection: identity fraud, anomalies
These were expensive to build and expensive to maintain and therefore fickle until now.
With AI all of the features are baked into the model and therefore a lot less development is required
Additional New Use Cases in Amazon Q:
- Improve CX and EX
- Increase knowledge of workers – think how important this is. We are all in exactly this business whether Marketing, Sales, Compliance or Analysis, etc.
- Product Innovation and Process Automation including
-
- Data Extraction
- Natural Language Interfaces to Analytics
- Personalized Content Generation
Amazon Q (Suite of Gen AI Services) Portfolio – “AI Powered Assistant” General Availability: 30.04.2024 (new!) of 3 flavours:
- Amazon Q in QuickSight (powered by Bedrock) can be considered a BI Service with AI Capabilities – structured data
- Amazon For Business – also unstructured data
- Amazon Q Developer – Assistance in writing code
Gen AI assistant for Accelerating software development and leveraging company data
These are being embedded in Amazon Services
Traditionally LLMs have been best for:
- Broad World Information
- Assisting Human Work (summarizing, teaching and Generalizing) as well as Offering knowledge, autonomous tasks and calculations
But Newly: Amazon Q in QuickSight:
- Ask questions in natural languages and ML models interpret user’s questions and generate images and reports.
- AI powered dashboard.
- On-demand answers.
- Can be extended to other Apps.
- AI assisted Story telling (tells you what is going on and provides documents and slides to present the data)
These are available in different apps including your custom apps – Pricing (in USD):
- Amazon Q Business Lite $3/user/month
- Amazon Q Business Pro $20/user/month
- Developer Free Tier
- Developer Pro Tier: $19/user/month
- etc.
Benefit: Ask yourself what is the productivity gain? We can see up to 75% productivity gain.
The AWS approach to Generative AI:
- Enterprise Focus
- Open Approach with both Proprietary and Open Source code
- Cost And Power Optimized
- Data Privacy and Security: Own Your Data/Access Control included/Permissions + Connectors to everything including Exchange/SFDC/Confluence/JIRA etc.
- Based on the RAG Architecture
Generative AI and ML Considerations For Financial Services (because the day had a Financial Services bent nominally)
- Approach? Is a human in the loop and is it possible given the amount of data? Is the input and output from structured or unstructured data?
- Governance And Compliance?
- Legal & Privacy: Think output validation and Reporting especially when using 3rd Party models
- Monitor legal and regulatory scope consistently as the scene changes and proposals like SEC’s or European regulation become updated.
Things That Need To Go Away: The Only Name Tag For An Event To Be Missing Being Mine
