Google’s Recommender System Breakthrough Detects Semantic Intent

Google quietly published a research paper on personalized semantics for recommender systems like Google Discover and YouTube.
InfoQ

Engineering Speed at Scale — Architectural Lessons from Sub-100-ms APIs

Sub‑100-ms APIs emerge from disciplined architecture using latency budgets, minimized hops, async fan‑out, layered caching, ...
IEEE

Comparison of Deep-Learning Models for Classification of Cellular Phenotype From Flow Cytometry Data

Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...
IEEE

A Lightweight Semantic Segmentation Network Based on Self-Attention Mechanism and State Space Model for Efficient Urban Scene Segmentation

Abstract: In the semantic segmentation of remote sensing images, methods based on convolutional neural networks (CNNs) and Transformers have been extensively studied. Nevertheless, CNN struggles to ...
InfoQ

Lessons Learned From Building LinkedIn’s First Agent: Hiring Assistant

Karthik Ramgopal and Daniel Hewlett discuss the evolution of AI at LinkedIn, from simple prompt chains to a sophisticated ...