Architecture for the Age of AI

Artificial intelligence, especially Machine Learning, Deep Learning, and Large Language Models, is increasingly becoming one of the critical factors to the success of our modern applications.

This track focuses on sharing practitioner-driven insights on what works (and what doesn't) on AI-focused software architectures, enabling you to build and sustain the AI-based systems of the future.

We will explore the latest trends and techniques for building modern software architecture for AI systems and applications.

From this track

Session

When AIOps Meets MLOps: What Does It Take To Deploy ML Models at Scale

Tuesday Apr 9 / 10:35AM BST

In this talk, we introduce the concept of AIOps referring to using AI and data-driven tooling to provision, manage and scale distributed IT infra. We particularly focus on how AIOps can be leveraged to help train and deploy machine learning models and pipelines at scale.

Speaker image - Ghida Ibrahim
Ghida Ibrahim

Chief Architect, Head of Data @Sector Alarm Group, Ex-Facebook/Meta

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

Connecting the Dots: Applying Generative AI (Limited Space - Registration Required)

Tuesday Apr 9 / 01:35PM BST

Details coming soon.

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, Previously Leader of the MLServer Project @Seldon

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 AI/ML

Lessons Learned From Building LinkedIn’s AI Data Platform

Tuesday Apr 9 / 05:05PM 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

Date

Tuesday Apr 9 / 10:35AM BST

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Track Host

Fabiane Nardon

Data Scientist, Java Champion & CTO @tail_oficial

Fabiane is a computer scientist with many years of experience in large information systems with huge amounts of data. She was chief architect of the Sao Paulo Healthcare Information System, considered the largest JavaEE application in the world and winner of the 2005 Duke's Choice Award. She leaded several communities, including the JavaTools Community at java.net, where 800+ open source projects were born. She is a frequent speaker at conferences in Brazil, her home country, and abroad, including JavaOne, OSCON, Jfokus, DockerCon, JustJava, QCon and more. She is also author of several technical articles and was in the program committee of conferences as JavaOne, OSCON, TDC and QCon. She was chosen a Java Champion by Sun Microsystems as a recognition of her contribution to the Java ecosystem. Currently, she works as CTO at Tail where she is helping to shape new disruptive Data Science based services.

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