Frequently Asked Questions
What is the aim of the "GenAI & Data Engineering" track at JAX London?
This track empowers Java developers to harness AI and transform data into actionable insights. It covers advanced tools like Copilot and ChatGPT, builds understanding of LLMs (Large Language Models), and teaches how to integrate AI features seamlessly into development workflows.
Which key topics are covered by this track?
Attendees can expect to explore: The evolution of Big Data and tools for processing unstructured information. AI-powered software development, using tools like Copilot, ChatGPT, or Gemini. A deep dive into LLMs, uncovering their structure and use cases. Machine learning with Java, using Java-specific frameworks. AI feature development in applications. Building chatbots using cloud services.
Is there content that focuses on making ML techniques more aligned with software development practices?
Yes. A dedicated session—"Agile Machine Learning: From Theory to Production"—explores how to apply software engineering best practices to ML, integrating research into agile development cycles.
What data engineering topics are featured?
Several practical topics include: An introduction to data science fundamentals, helping participants understand prediction methodologies. Reactive database access patterns, which promote resilient and efficient data handling in systems. Real-world use cases involving Kafka and Kafka Connect, addressing enterprise data integration challenges.
Are there innovative intersections of AI and data technologies included?
Absolutely. For instance, the session "Pairing Machine Learning + Blockchain for Enhanced Data Tracking, Insights, and Security" demonstrates how combining machine learning with blockchain technologies can improve transparency, security, and traceability in data workflows.