Many teams struggle with connecting data extraction, transformation, and reporting into a seamless automated pipeline. Pentaho offers capabilities across ETL, data integration, and reporting, but implementing full BI automation still raises questions around scheduling, scalability, and maintenance. What are the best practices or real-world approaches to using Pentaho for fully automated BI processes while ensuring(Read More)

With newer models getting larger (especially in LLMs and multimodal setups), memory constraints are becoming a major bottleneck during training and inference. Looking for practical approaches others are using to manage this, such as: Gradient checkpointing vs mixed precision Model sharding or distributed training strategies Efficient data loading and batching Would be useful to understand(Read More)