Geeky Gadgets

Why Your AI Memory & Retrieval System Fails and How to Fix It

What happens when your AI-powered retrieval system gives you incomplete or irrelevant answers? Imagine searching a compliance document for a specific regulation, only to receive fragmented or ...
Yahoo Finance

POMA AI Achieves Best-in-Class RAG Chunking and Document Ingestion With 77% Token Reduction vs. Conventional Models

Berlin, BERLIN, March 16, 2026 (GLOBE NEWSWIRE)-- POMA AI, a Berlin-based document intelligence company, today released POMA-OfficeQA, an open-source benchmark demonstrating that its structure-aware ...
Forbes

Propositional Chunking For Better Vector Search

Most vector search systems struggle with a basic problem: how to break complex documents into searchable pieces. The typical approach is to split text into fixed size chunks of 200 to 500 tokens, this ...
dbta

A Deep Dive into RAG Adoption and Optimization with Elastic

Retrieval-augmented generation—or RAG—is an AI strategy that supplements text generation with information from private or proprietary data sources, according to Elastic, the search AI company. RAG ...
dbta

Beyond RAG basics: Strategies and best practices for implementing RAG

Join DBTA and Elastic as we explore advanced techniques in retrieval augmented generation (RAG). This talk provides developers, data scientists, and AI enthusiasts with essential insights to elevate ...
Geeky Gadgets

Why Your RAG System Might Be Failing You (And How to Fix It)

What if the very method you rely on to simplify information is actually sabotaging your results? Imagine a Retrieval-Augmented Generation (RAG) system tasked with answering a critical question from a ...