Yandex has recently made a significant contribution to the recommender systems community by releasing Yambda, the world’s largest publicly available dataset for recommender system research and development. This dataset is designed to bridge the gap between academic research and industry-scale…
Policy gradient methods have significantly advanced the reasoning capabilities of LLMs, particularly through RL. A key tool in stabilizing these methods is Kullback-Leibler (KL) regularization, which discourages drastic changes between the current policy and the reference policy. While widely used…
Diffusion-based large language models (LLMs) are being explored as a promising alternative to traditional autoregressive models, offering the potential for simultaneous multi-token generation. By using bidirectional attention mechanisms, these models aim to accelerate decoding, theoretically providing faster inference than autoregressive…
In this tutorial, we demonstrate how to build an intelligent AI assistant by integrating LangChain, Gemini 2.0 Flash, and Jina Search tools. By combining the capabilities of a powerful large language model (LLM) with an external search API, we create…
Large Reasoning Models (LRMs), trained from LLMs using reinforcement learning (RL), demonstrated great performance in complex reasoning tasks, including mathematics, STEM, and coding. However, existing LRMs face challenges in completing various puzzle tasks that require purely logical reasoning skills, which…
How Deepfakes Are Created Generative AI models enable the creation of highly realistic fake media. Most deepfakes today are produced by training deep neural networks on real images, video or audio of a target person. The two predominant AI architectures…
The Desktop Commander MCP Server is a powerful tool that brings all your development operations into one chat interface. Built on top of the MCP Filesystem Server, it allows you to search, edit, and manage files, run terminal commands, and…
BOND’s latest report on Trends – Artificial Intelligence (May 2025) presents a comprehensive data-driven snapshot of the current state and rapid evolution of AI technology. The report highlights some striking trends underscoring the unprecedented velocity of AI adoption, technological improvement,…
Large language models (LLMs), with billions of parameters, power many AI-driven services across industries. However, their massive size and complex architectures make their computational costs during inference a significant challenge. As these models evolve, optimizing the balance between computational efficiency…
Scientific research across fields like chemistry, biology, and artificial intelligence has long relied on human experts to explore knowledge, generate ideas, design experiments, and refine results. Yet, as problems grow more complex and data-intensive, discovery slows. While AI tools, such…
