Create Your Own Service Design AI Assistant - Building your own service design large language model
AI Summary
Meeting Summary (Outline Form)
- Introduction
- Host: Greg Ly
- Co-hosts: Brandon (Precocity), Brenda
- Absent: Robin
- Sponsors: Slalom and Precocity
- Series: Part two of AI-powered service design
- Previous session: Available on YouTube (by Leton Lucky)
- Recap
- Service Network (S network) Dallas chapter event
- Over 50 past sessions available on YouTube
- Topics range from journey mapping to advanced service design
- Presentation by Preston
- Presenter: Preston McAfee, Director of Emerging Technologies at Tonic 3
- Focus: Building an AI agent for service design
- Overview:
- Essential AI terminology
- Tools in the ecosystem
- Building GPT agents
- Live demo
- AI Terminology
- AI (Artificial Intelligence)
- Agent: AI system directed at a single purpose
- Co-pilot: AI working alongside a user
- Generative AI: Generates text, images, music
- Large Language Models (LLMs)
- Retrieval Augmented Generation (RAG)
- Vector: Numerical representation in 3D space
- Tools for Local AI
- LM Studio: Local LLMs
- GPT for All: Local chat with LLMs
- Autogen Studio: Create agents with a front end
- Crew AI: Build agents without a front end
- Lexi: AI Agent for Service Design
- Created to assist users in integrating AI into service design
- Adapts responses to user’s expertise level
- Grounded on service design knowledge and reports
- Can be upgraded with voice synthesis (Lexi 2.0)
- Building a Service Design Team with AI Agents
- Agents with different roles and tasks
- Researching service design topics and historical data
- Generating insights and reports
- Learning Curve and Tool Evaluation
- Approximate time to learn and use tools effectively: 1 month
- Evaluation of tools based on ease of use, performance, community support, etc.
- Current leading tools: Claude, GPT-4, Sonet 3.5
- Q&A Session
- Addressed concerns about data privacy with local AI models
- Discussed the potential impact of AI on the critical thinking aspect of service design
- Explored business cases for AI application in service design
- Mentioned the use of virtual machines for running models with massive compute power
- Closing Remarks
- Acknowledgment of the rapid evolution of AI technology
- Encouragement for attendees to share their experiences with AI tools on LinkedIn
- Anticipation of future developments and discussions in the field of service design and AI
- Resources
- YouTube channel for further technical details
- LinkedIn for community engagement and sharing experiences