
Dive into practical methods for integrating fine-tuned AI systems with external data sources, focusing on Retrieval Augmented Generation (RAG) and real-time data connectivity for enhanced AI applications.

Discover how AI inference capabilities enhance object storage systems by automating metadata generation, enabling advanced object detection, and improving searchability of stored data.

Discover how to manage unstructured data sprawl across hybrid multi-cloud environments using Crystal, an open-source platform for unified data protection, security, governance, and insights optimization.

Master distributed computing fundamentals through MapReduce, exploring cluster computing challenges, file systems, and practical applications like PageRank and community detection algorithms.

Explore how Cloudera Data Platform leverages Azure Kubernetes Service for flexible, scalable Big Data environments. Learn about cloud agility, cost optimization, and hybrid data cloud models.

Explore Kamelets as event sources in Knative, learn installation, discovery, deployment, and management. Live demo showcases integration with event-driven applications using Apache Camel connectors.

Explore Volcano: a powerful batch scheduling system for high-performance workloads on Kubernetes. Learn key concepts, features, and real-world use cases for ML/DL, big data, and bioinformatics applications.

Explore scalable data processing using Knative and Benthos, focusing on batch processing challenges and solutions for enterprise use cases. Learn about transaction-based resiliency and data transformation techniques.

Learn to build a product recommendation system using Argo Workflows on Kubernetes. Explore DataOps, pipelines, and tools like Minio and Apache Spark for efficient data processing and analysis.

Explore solutions for sharing GPUs among multiple containers in Kubernetes, improving resource utilization and cost-efficiency for inference workloads. Performance results and demos included.

Explore Cloud Native Digital Twin architecture for factory digitization and carbon neutrality in metal processing, featuring Kubernetes, Semantic Web frameworks, and declarative data processing.

Explore Azure's latest database innovations, AI technologies, and real-world applications. Learn to unlock your data's potential for enhanced application development and analytics.

Explore IFC's AI journey: Scaling MALENA platform with Lakehouse, optimizing LLM serving, and leveraging GPU for enhanced performance in addressing global development challenges.

Explore strategies for extending data governance to AI systems, ensuring trust, compliance, and collaboration while integrating Collibra with Databricks Unity Catalog for tailored solutions.

Optimize engineering design with cloud-based generative AI. Learn how Rolls-Royce and Databricks reduced cGAN training time by 30x using distributed computing, MLflow, and Unity Catalog for aerospace compliance.

Explore best practices for managing AI model lifecycles, focusing on governance, monitoring, and performance tracking. Learn to optimize model delivery while ensuring compliance and accountability.

Explore ethical AI implementation using Databricks' platform. Learn about governance, compliance, security, and tools for safe AI integration in business.

Explore how AI and data analytics are revolutionizing global healthcare delivery, focusing on identifying medical deserts and improving access to services in low and middle-income countries.

Explore efficient MLOps framework design for ML model development and deployment, covering environment management, CI/CD pipelines, and tools like Unity Catalog and MLflow for model monitoring and progression.

Explore comprehensive tools for evaluating GenAI applications, including inference tables, Lakehouse Monitoring, and MLflow. Learn best practices for offline and real-time quality assurance in production environments.

Learn to scale OpenTelemetry collectors using Kafka for improved observability in large-scale systems. Explore architecture, implementation, and monitoring techniques for efficient data processing and analysis.