MLOps Architecture

From the same track

Session AI/ML

Lessons Learned From Building LinkedIn’s AI Data Platform

Tuesday Apr 9 / 10:35AM BST

Taking AI from lab to business is notoriously difficult. It is not just about picking which model flavor of the day to use. More important is making every step of the process reliable and productive.

Speaker image - Felix GV
Felix GV

Principal Staff Engineer @LinkedIn

Session AI/ML

Mind Your Language Models: An Approach to Architecting Intelligent Systems

Tuesday Apr 9 / 11:45AM BST

As large language models (LLMs) emerge from the realm of proof-of-concept (POC) and into mainstream production, the demand for effective architectural strategies intensifies.

Speaker image - Nischal HP
Nischal HP

Vice President of Data Science @Scoutbee, Decade of Experience Building Enterprise AI

Session

Flawed ML Security: Mitigating Security Vulnerabilities in Data & Machine Learning Infrastructure with MLSecOps

Tuesday Apr 9 / 02:45PM BST

The operation and maintenance of large scale production machine learning systems has uncovered new challenges which require fundamentally different approaches to that of traditional software.

Speaker image - Adrian Gonzalez-Martin
Adrian Gonzalez-Martin

Senior MLOps Engineer @Bloomberg

Session

Large Language Models for Code: Exploring the Landscape, Opportunities, and Challenges

Tuesday Apr 9 / 03:55PM BST

In the rapidly evolving landscape of software development, Large Language Models (LLMs) for code have emerged as a groundbreaking tool for code completion, synthesis and analysis.

Speaker image - Loubna Ben Allal
Loubna Ben Allal

Machine Learning Engineer @Hugging Face

Session

Connecting the Dots: Applying Generative AI

Tuesday Apr 9 / 01:35PM BST

Details coming soon.