Latest AI innovations in retail tech, luxury brands, personalization, AR experiences, and recommendation systems.
A technical guide explains how to implement a two-tower neural network architecture for product recommendations, creating separate embeddings for users and items to power similarity search and personalized ads. This approach moves beyond simple collaborative filtering to semantic understanding.
A clear breakdown of three core approaches for customizing large language models—prompting, retrieval-augmented generation (RAG), and fine-tuning—with...
A framework for identifying the essential 20% of metrics that deliver 80% of the value when monitoring LLMs in production. Focuses on practical observ...
Part 3 of a technical series details a production-inspired fraud detection platform PoC built with self-healing MLOps principles. This demonstrates ho...
The article critiques current LLM routing benchmarks as solving only the easy part, introducing vLLM Semantic Router as a comprehensive solution for p...
A technical article outlines a transformer-based system for generating personalized product recommendations from user browsing data, directly applicab...
This article traces the technological evolution of recommendation systems through multiple transformative stages, culminating in the current LLM-power...
An opinion piece from aBlogtoWatch argues that AI cannot replicate the human touch essential to luxury. It emphasizes that emotion, heritage, and pers...
Spotify announced a beta feature called 'Taste Profile' that gives users direct control over their recommendation algorithms. This represents a signif...
AI agents that plan and act autonomously are projected to sit inside 40% of enterprise apps by 2026, fundamentally changing software economics. This r...
NVIDIA's NeMo Retriever team has developed a generalizable agentic retrieval pipeline that topped the ViDoRe v3 leaderboard and placed second on BRIGH...
New research identifies two types of long-tail bias in LLM-based recommenders and proposes EISAM, an efficient optimization method to improve performa...
A new report highlights a significant uptick in AI investment across both B2B and B2C commerce sectors, driven by the emerging trend of 'agentic comme...
arXiv study shows simple prompt instructions can reduce bias in LLM recommendations without model retraining. Fairness improved up to 74% while mainta...
The article argues that while prompt engineering gets attention, building reliable AI systems requires focusing on context engineering—designing the i...
Researchers propose FGTR, a hierarchical LLM reasoning method for retrieving precise data from multiple, large tables. It outperforms prior methods by...
New research introduces structured distillation to compress AI agent conversation history by 11x (371→38 tokens/exchange) while preserving 96% retriev...
New research presents a three-stage optimization pipeline for the vLLM Semantic Router, achieving 98× speedup and enabling long-context classification...
Researchers propose ToolTree, a Monte Carlo tree search-inspired method for LLM agent tool planning. It uses dual-stage evaluation and bidirectional p...
New research introduces NanoVDR, a method to distill a 2B parameter vision-language retriever into a 69M text-only student model. It retains 95% of te...
LVMH, Kering, Richemont, Chanel, Gucci, Prada — AI adoption and digital transformation in high-end fashion and luxury.
AR try-on, virtual shopping, visual search, dynamic pricing, and AI-powered customer experiences.
Recommendation systems, demand forecasting, inventory optimization, conversational commerce, and search relevance.