Agenda
Check out the different topics, each representing a single block of talks and sessions to guide you through the program of DevTalks! We look forward to welcoming you to the event and providing you with an unforgettable learning and networking experience in the world of technology.
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12:15 to 13:00
Symbiotic Futures: an exploration of trust, shared experience and even love.
Main Stage | Day 2 — 45 minutes Artificial Intelligence Technical Leadership Real case studies
We're in a world where the lines are blurred between human and machine intelligence, one where we need to build a harmonious relationship through experience. Read More...
Jeff Watkins
14:50 to 15:20
Faster, Leaner, Predictable: Quarkus vs Spring Under Real Load
DevOps Stage — 30 minutes DevOps Kubernetes Microservices
Modern organizations increasingly adopt FinOps principles to balance engineering autonomy with responsible cloud spending. In this presentation, I explore a practical comparison between Quarkus and Spring Boot through the lens of cost-efficient microservice design. Read More...
Alexandru-Cătălin Diniș
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10:00 to 10:10
Intro speech - Compliance in the age of AI
AI Product Stage — 10 minutes DevOps Generative AI Automation
Find out how Amazon is leveraging cutting-edge AI across its compliance services — from generative AI for code and regulatory documentation, to intelligent DevOps automation, ML-powered product classification, and large-scale regulatory ingestion. We'll also spotlight MILE, Amazon's latest contribution to AI research and the state of the art.
Cristian Cordos
10:15 to 11:00
Hugging Face ecosystem
AI Product Stage — 45 minutes Machine Learning AI Systems
Niels will showcase the Hugging Face ecosystem, all the tools and services Hugging Face provides for making machine learning accessible, open and collaborative.
Niels Rogge
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11:40 to 12:10
AI is Now Everyone's Problem - Act Like It!
AI Stage — 30 minutes Artificial Intelligence Generative AI
There was a time when "AI in the enterprise" meant a data science team, a Jupyter notebook, and a model that ran once a day in a corner of your data warehouse. Controlled, Contained, rarely customer-facing. That era is over. Read More...
Timo Salm