Liam Bluett
I've been working in data science for around 3 years at a consulting firm called Brady Heywood. Python is my tool of choice for AI and analytics.
I'm specifically interested in how we can use embeddings and LLMs on top of traditional data analytics to derive insights from enterprises we work with.
he/him
Session
As large language models take over the world, we’re now working alongside machines that can read, write and converse – coding with CoPilot, chatting with ChatGPT and drawing with DALL-E. But how do machines, which fundamentally operate on binary code, achieve such remarkable feats? The answer lies in embeddings. Embeddings allow us to represent complex data - whether it's text, images, or even abstract concepts - as dense vectors of numbers. In this presentation, we'll demystify embeddings and give you a practical and intuitive understanding of how they work.