Real-time annotation scales with LLMs, feedback loops, and active learning to handle petabyte datasets, and ensures speed, quality, and adaptability in diverse fields.
This blog post is the first in a three-part series exploring Apache Iceberg and its role in modern data architectures and the emergence of data lakehouses.
Video deduplication optimizes storage by removing duplicates using techniques like segmentation, embeddings, and clustering to manage massive datasets efficiently.
Learn to efficiently deduplicate 100M+ images using distributed architectures, embeddings, FAISS for ANN search, and clustering to ensure accurate results.
Real-time data streaming delivers fast insights but raises privacy and compliance risks. Use encryption, tokenization, and policy enforcement for secure streaming.
This article covers how key-value caching works and how it helps optimize large language models. It includes a text generation process to make it easy to understand.
Build a multimodal RAG app with ColPali, Milvus, and a visual language model to enable Q&A on PDFs using text and visual data indexed for efficient search.
Building a Flask-based web app that has dynamic querying for population thresholds, Redis caching for faster queries, and secure, scalable architecture.
Learn about how GenAI automates ETL pipelines, generates code, adapts to schema changes, and improves data processes with speed, efficiency, and precision.
This article explains idempotency in distributed systems and ensuring consistent results regardless of multiple executions, with implementation and challenges.