ML model serving/prediction API can be scaled on Kubernetes by adding or removing Pod instances. With a live demo, we will explain how scaling can be done for TensorFlow (applicable to PyTorch) model running on Kubernetes.

This talk will cover the importance of a solid foundation and what management should do to fix it. To do this Jesse will be sharing a real-life analogy to show how we can be misled and what that means for our success rates.

This talk explores the real challenges around ensuring data quality and identifies a critical element that is missing from many popular approaches to data quality. We will also look at how lessons from Product Thinking, Data Mesh and Site Reliability Engineering can help us in our quest for data quality.

In this session, Timothy will introduce you to the world of Apache Pulsar and how to build real-time messaging and streaming applications with a variety of OSS libraries, schemas, languages, frameworks, and tools.

In this talk, we describe a novel hybrid ML/symbolic approach to transforming natural language sentences into RDF graph structures, as well as possible practical applications of the results in downstream tasks, such as question answering, text entailment, and others.

This talk explains why data needs have changed, and how Postgres has uniquely adjusted to those needs. The talk also explains how to store data outside of Postgres while maintaining integrated data management.

In this session, Dipti will introduce the Presto technology and share why it’s becoming so popular – in fact, companies like Facebook, Uber, Twitter, Alibaba, and much more use Presto for interactive ad hoc queries, reporting & dashboarding data lake analytics, and much more. We’ll also show a quick demo on getting Presto running in AWS.

In this talk, Gad will take a deep dive into our new strategy step-by-step, from planning to execution: his structured game plan for empowering engineers to drive your team’s rapid growth in size, responsibility, and impact.

Developing such intuition is a critical role of a leader, that strongly correlates with the company’s success. During this presentation, Kuba is going to give you a seed of this intuition by going a little bit deeper than most of the “executive guides to AI”.

Should we just throw our Jupyter Notebooks out the window and move to classic IDEs? Probably not – Jupyter Notebooks are, after all, a great tool that gives us superhuman abilities. We can, however, be more production-oriented when using them. How does this look in practice? That is exactly what we’ll cover in this talk.