AI/ML
Elevate Developer Experience with Generative AI Capabilities on AWS
Friday Sep 27 / 02:30PM CEST
This presentation delves into the transformative potential of generative AI on AWS to enhance the developer experience, with a particular focus on expediting the onboarding process for new developers.
Olalekan Elesin
Engineering Director @HRS Group & AWS Machine Learning Hero, 10+ Years Experience Developing and Scaling Data and AI-Driven Technology Products
Leveraging Open-Source LLMs for Production
Thursday Sep 26 / 02:30PM CEST
This talk dives into the practical use of open-source LLMs for real-world applications, weighing their pros and cons.
Andrey Cheptsov
Founder and CEO @dstack, Rethinking Container Orchestration for AI Workloads, Previously Product Manager @JetBrains Working on PyCharm and DataSpell
Efficient DevSecOps Workflows With a Little Help From AI
Thursday Sep 26 / 01:20PM CEST
From idea to the first line of code to production deployments - DevSecOps workflows help develop software faster. There is a different level of adoption, and processes feel inefficient or block progress and innovation.
Michael Friedrich
DevSecOps AI Advocate @GitLab, 20 years in hardware/software systems engineering, it is always DNS
Taking LLMs out of the Black Box: A Practical Guide to Human-in-the-Loop Distillation
Thursday Sep 26 / 10:20AM CEST
As the field of natural language processing advances and new ideas develop, we’re seeing more and more ways to use compute efficiently, producing AI systems that are cheaper to run and easier to control.
Ines Montani
Co-Founder & CEO @Explosion, Core Developer of spaCy and Prodigy, Python Software Foundation Fellow
From "Simple" Fine-Tuning to Your Own Mixture of Expert Models Using Open-Source Models
Thursday Sep 26 / 03:40PM CEST
Nowadays, training a large language model (LLM) from scratch is a huge effort, even for very large companies.
Sebastiano Galazzo
CTO @Synapsia AI, Winner of Three AI Awards, Microsoft MVP for Artificial Intelligence Category, 25 Years Working in AI and ML