Elevator Pitch
Unleash Go’s hidden potential in AI! While it’s not known for AI applications, Go is a powerhouse for building dynamic Retrieval-Augmented Generation (RAG) pipelines. Join us to discover how Go can supercharge your AI applications and ignite the creation of the next generation of AI services.
Description
Unleash Go’s hidden potential in the AI revolution! While Go isn’t traditionally known for AI applications, it’s a powerhouse waiting to be tapped for building dynamic Retrieval-Augmented Generation (RAG) pipelines. Join us on an exciting journey to discover how Go can supercharge your AI projects and ignite the creation of the next generation of AI tools.
In this talk, we’ll start by briefly demystifying key concepts like RAG, GenAI, and AI Agents, setting the stage for the possibilities ahead. We’ll then tackle the big question: Why does Go seem to “suck” at AI? We’ll delve into the misconceptions and limitations, and reveal how Go’s unique strengths compensate in unexpected ways.
But here’s where it gets exciting - we’ll unveil what a RAG pipeline looks like and how you can build one using Go. With its robust standard library and features like goroutines, Go excels at moving data efficiently between different models and services, making it ideal for constructing efficient AI pipelines.
Finally, we’ll explore the path forward: How can you build innovative products around these pipelines? We’ll discuss strategies for leveraging Go to create scalable, high-performance AI applications that stand out in the market.
Whether you’re an AI enthusiast looking to explore new horizons or a Go developer eager to dive into the world of AI, this talk will equip you with the insights and inspiration to harness Go’s hidden superpowers. Let’s embark on this adventure together and transform the way we build intelligent applications!
Notes
This idea for a talk has come about from over a year of research into building these kinds of pipelines under many different circumstances/languages. As a Software Engineer I’ve spent a lot of focus making pipelines that can run cost effectively and provide business value so I believe I’m qualified to talk on the subject matter.
I currently work at an AI startup where we build tools and services around RAG and GenAI so I’ve been exposed to what the current state of thinking is in this area.
There are no technical requirements for the talk other than a basic understanding of Go, and a rough understanding of GenAI (previous use of ChatGPT).