Reach Next-Level Automation With Knowledge-Based GenAI Agent

Generative AI has emerged rapidly since the release of ChatGPT, yet the industry is still at its very early stage with unclear prospects and potential. The cool concept of building AI agents with Foundation Model (FM) as its core controller has stirred up heated discussions and become one of the mainstream bets. While most people are still wondering: What exactly is an AI Agent? What can it bring and is it going to be the future? In this talk, we’ll boil down AI Agent and explore various use cases across industries on how it extends the frontiers of Generative AI and leads to next-level automation in combination with your enterprise data.

What's the focus of your work these days?

As an Enterprise Solutions Architect at Amazon Web Services based in Stockholm, Sweden, my role involves collaborating with some of the largest and most complex enterprise customers to architect, design, and develop cloud-optimized infrastructure solutions. My work is dedicated to accelerating the realization of business outcomes for my customers. Recently, my focus has shifted towards assisting companies across various industries in harnessing the potential of AI/ML and Generative AI technologies. Specifically, I am engaged in designing and implementing knowledge-based AI agents within the manufacturing and financial sectors for specialized scenarios. These initiatives aim to secure higher returns on investment, as well as achieve enhanced automation and operational excellence.

What's the motivation for your talk at QCon London 2024?

AI agent is one of the future trends for Generative AI. It is relevant for all developers to have an overview of it and contribute to the community, technologies and industries. The motivation for this talk is to democratize AI Agent for developers and give some practical guidance on how to build Generative AI applications for various use cases and tasks. 

How would you describe your main persona and target audience for this session?

Data scientists, ML Engineers, Software Developers, CTOs, Solutions Architects, Product Owners.
No specific prerequisites are necessary, although attendees with a foundational understanding of Generative AI concepts such as Foundation Models, Multi-Modality and LangChain, will find the talk more accessible.

Is there anything specific that you'd like people to walk away with after watching your session?

Some main takeaways can be:
1. Foundation Models (FMs) offer significant reasoning capabilities but have limitations, notably their inability to interact with external systems and lack of access to current knowledge sources, where AI Agent presents a promising solution to address these limitations.


2. Integrating AI Agents with FMs facilitates the development of Generative AI applications that can run tasks for a wide range of use cases and deliver up-to-date answers based on enterprise knowledge sources. However, this still requires careful consideration of trade-offs during practical and scalable adoptions given the current stage of AI Agent development. 


Speaker

Tingyi Li

Enterprise Solutions Architect @AWS

Tingyi Li works as an Enterprise Solutions Architect at Amazon Web Services(AWS) based in Stockholm Sweden, and is the founder and leader of the AWS Nordics Generative AI community. She enjoys helping customers with the architecture, design, and development of cloud-optimized infrastructure solutions. Currently, she is focusing on demystifying Generative AI and working with companies across industries to unlock business values leveraging AI/ML and Generative AI technologies. 

Prior to AWS, she worked as a Data and AI Engineer as well as in Software developer roles at Intel, Foxconn and Huawei etc, building large-scale intelligent industrial data systems and driving innovations using AI/ML. In her spare time, she also works as a part-time illustrator/prompt engineer who writes novels and plays the piano.

Read more

Date

Monday Apr 8 / 01:35PM BST ( 50 minutes )

Location

Mountbatten (6th Fl.)

Topics

AI/ML Generative AI Innovation AI Agent AI applications

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