Insights into the tech stack, software infrastructure, and best
practices for architecting and implementing data pipelines
and infrastructure. Participants will learn how to enable
analytics and machine learning on rich, high-quality datasets,
regardless of whether they are operating on-premise, in a hybrid
environment, or in a cloud-native setup. Our discussions will
cover a wide range of key topics, including DataOps, MLOps,
AutoML, Cloud ML, Fast Data, and Feature Extraction.

A range of technical presentations focused on enterprise
database management in the cloud. Attendees will have the
opportunity to learn about best practices for maintaining high
data quality and optimizing database performance to meet
target goals. Additionally, we will cover topics related to data
streaming and enterprise architecture, providing insights
into how to build a modern data environment that effectively
supports data collection, processing, analytics, and machine
learning workloads in the cloud.

Various aspects of deploying, running, and scaling machine
learning, deep learning, natural language processing, generative
adversarial networks, transformers, and artificial intelligence
in production environments. We will feature a strong focus on
MLOps techniques, with the goal of improving delivery time,
reducing defects, and increasing the productivity of machine
learning projects.

Helping heavy asset organizations and manufacturers leverage
machine data and AI applications to improve operational
processes and detect anomalies. By effectively reducing
downtime and optimizing production, organizations can
achieve greater efficiency and success in their everyday
operations. We might present use cases from a variety of heavy
industry sectors, including automotive, shipyards, and other
sectors connected to the cloud.

Latest innovations in application-centric AI and their potential to transform customer experiences, enhance business processes, and drive new business models. We will explore the exciting developments in human-centric AI, including explainable AI, trustworthy AI, digital ethics, and AI for Good. We are particularly interested in the latest trends in OpenAI and the ways in which this technology is being adopted by businesses today.