Business Wire

Rubber Ducky Labs Raises $1.5 Million to Build Operational Analytics for Recommender Systems

SAN FRANCISCO--(BUSINESS WIRE)--Rubber Ducky Labs, a company dedicated to making recommender systems easier to build and imbue with human knowledge, today announces $1.5 million seed investment round ...
Noozhawk

Researchers Receive Google Grant to Build Better Conversational Recommender Systems

Click to share on Facebook (Opens in new window) Click to email a link to a friend (Opens in new window) Click to print (Opens in new window) Click to share on X (Opens in new window) An emerging ...
Searchenginejournal.com

Google’s Recommender System Breakthrough Detects Semantic Intent

Google published a research paper about helping recommender systems understand what users mean when they interact with them. Their goal with this new approach is to overcome the limitations inherent ...
Forbes

Auto-Evaluation: A New Lens For AI Relevance

Artificial intelligence is now central to how digital platforms decide what to show—whether a post in your feed, search result or product suggestion. Traditionally, these systems focused on engagement ...
Digital Journal

From bias to understanding: A causal path toward trustworthy recommendation

Opinions expressed by Digital Journal contributors are their own. The global race in artificial intelligence is undergoing a profound transformation. The goal is no longer just to build more powerful ...
VentureBeat

How LinkedIn replaced five feed retrieval systems with one LLM model, at 1.3 billion-user scale

LinkedIn's feed reaches more than 1.3 billion members — and the architecture behind it hadn't kept pace. The system had accumulated five separate retrieval pipelines, each with its own infrastructure ...