On July 1, 2026, the AI VK team will host the RecSys Meetup in Moscow, dedicated to the transition toward hybrid architectures for Discovery technologies. Experts will discuss the implementation of LLM agents, the use of transformer models for user neuro-profiles, and the application of VLMs for content ranking.
What Happened
The AI VK team is organizing a technical meetup that will present solutions for scaling recommendations to over 10 billion objects. The program includes presentations on graph search without the use of LLMs, the application of Vision Language Models (VLM), and the integration of LLM agents into content management tasks.
Context
Modern recommendation systems in large ecosystems are transforming from classical algorithms to hybrid schemes. These new architectures combine graph structures, transformers, and generative AI to process ultra-large datasets and create real-time multimodal Discovery.
Why It Matters for the Industry
The event sets a trend for the use of hybrid AI architectures in the Russian segment, demonstrating the transition toward integrating graph RAG and multimodal models (VLM) into production pipelines. This raises the bar for the technological stack for developers and defines standards for automated content annotation at ecosystem scales.
Why It Matters for Users
Specialists and engineers will gain access to practical use cases for implementing generative AI in high-load systems and can meet the developers of Discovery platforms. This provides an opportunity to study methods for working with neuro-profiles and agentic interfaces in content feeds.
Uncertainties / Limitations
There is a difference in the applicability of these solutions: while this represents a technological shift for large ecosystems, for solo builders and startups, such architectures present an extremely high barrier to entry and an infrastructural complexity that is inaccessible to small players.
Sources
Author
Look at AI, Editorial Staff