What's Next in GenAI and Large Language Models (LLMs)

LLMs have been rapidly evolving in recent years, and there is a lot of excitement about their potential to revolutionize many different industries. Join us to discuss the latest developments in LLM research and development. Participants will learn about the different types of LLMs, their capabilities, and their limitations. They will also discuss the potential of LLMs to impact the future of work, education, healthcare, and many other areas.


From this track

Session

How Green is Green: LLMs to Understand Climate Disclosure at Scale

Assessment of the validity of climate finance claims requires a system that can handle significant variation in language, format, and structure present in climate and financial reporting documentation, and knowledge of the domain-specific language of climate science and finance.

Speaker image - Leo Browning
Leo Browning

First ML Engineer @ClimateAligned

Session

LLM and Generative AI for Sensitive Data - Navigating Security, Responsibility, and Pitfalls in Highly Regulated Industries

As large language models (LLM) become more prevalent in highly regulated industries, dealing with sensitive data and ensuring the security and ethical design of machine learning (ML) models is paramount.

Speaker image - Stefania Chaplin
Stefania Chaplin

Solutions Architect @GitLab

Speaker image - Azhir Mahmood
Azhir Mahmood

Research Scientist @PhysicsX

Session

Navigating LLM Deployment: Tips, Tricks, and Techniques

Self-hosted Language Models are going to power the next generation of applications in critical industries like financial services, healthcare, and defence.

Speaker image - Meryem Arik
Meryem Arik

Co-Founder @TitanML

Session

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.

Speaker image - Tingyi Li
Tingyi Li

Enterprise Solutions Architect @AWS

Session

Retrieval-Augmented Generation (RAG) Patterns and Best Practices

The rise of LLMs that coherently use language has led to an appetite to ground the generation of these models in facts and private collections of data.

Speaker image - Jay Alammar
Jay Alammar

Director & Engineering Fellow @Cohere & Co-Author of "Hands-On Large Language Models"

Date

Monday Apr 8 / 10:35AM BST

Share

Book your ticket for QCon London
on April 8-10, 2024.

Register

Track Host

Hien Luu

Sr. Engineering Manager @DoorDash & Author of Beginning Apache Spark 3, Speaker and Conference Committee Chair

Hien Luu is a Sr. Engineering Manager at DoorDash, leading the Machine Learning Platform team. He is particularly passionate about the intersection between Big Data and Artificial Intelligence. He is the author of the Beginning Apache Spark 3 book. He has given presentations at various conferences such as Data+AI Summit, XAI 21 Summit, MLOps World, YOW Data!, appy(), QCon (SF,NY, London).

Read more
Find Hien Luu at: