Artificial Intelligence (AI) has made significant progress in the last few years, with the emergence of large language models (LLMs) that mark an important milestone in its growth. With such widespread adoption, it is not uncommon to feel out of this revolution. One way that a person can remain up to date with the latest … Read more
Nvidia has introduced Lama nemotron nano vlA Vision Language Model (VLM) designed to address document level understanding tasks with efficiency and precision. This release is built on the LAMA 3.1 architecture and combined with a lightweight vision codes, and targets applications that require accurate parsing of complex document structures, such as scanned forms, financial reports … Read more
Modern software technology faces growing challenges with accurately downloading and understanding code across different programming languages ​​and large code bases. Existing embedding models often struggle to capture the deep semantics of code, resulting in poor results in tasks such as code search, cloth and semantic analysis. These limitations prevent the ability of developers to effectively … Read more
Yandex has recently made a significant contribution to the Society of the Recommendation System by releasing YambdaThe world’s largest publicly available data set for recommendation system research and development. This data set is designed to bridge academic research and applications to industry and offers nearly 5 billion anonymous user interaction events from Yandex Music-a of … Read more
Bond’s latest report on Trends – artificial intelligence (May 2025) Presents an extensive data-driven snapshot of the current state and rapid development of AI technology. The report highlights some striking trends that emphasize the unprecedented speed of AI -admission, technological improvement and market impact. This article reviews several key findings from the report and explores … Read more
Reasoning tasks are a basic aspect of artificial intelligence that includes areas such as Commonsense understanding, mathematical problem solving and symbolic reasoning. These tasks often involve several steps with logical inference that large language models (LLMs) try to emulate through structured approaches, such as chain-of-tank (COT) that pray. However, when LLMs grow in size and … Read more
Long Cot Reasoning improves the performance of the big language models on complex tasks, but comes with disadvantages. The typical “thinking-derenter-response” method slows down response times, which interferes with real-time interactions like those in chatbots. It also risks inaccuracies as errors in previous reasoning steps can lead to a misleading final answer. Unlike people who … Read more
Web navigation focuses on teaching machines how to interact with websites to perform tasks such as searching for information, shopping or booking services. Building a capable web navigation agent is a complex task because it requires understanding the structure of sites, interpretation of user goals and making a number of decisions across several steps. These … Read more
In this tutorial we introduce a streamlined approach to extracting, processing and analysis of YouTube -Videotransus using LyzrAn advanced AI-driven frame designed to simplify interaction with text data. Utilization of Lyzr’s intuitive chatbot interface along with YouTube-Transcript-API and FPDF, users can effortlessly convert video content to structured PDF documents and perform insightful analyzes through dynamic … Read more
While large reasoning models (LRMs) have shown impressive capacities in map surfaces resonance through reinforcement learning (RL), these gains do not generalize well to long-context scenarios. Applications such as multi-document QA, research synthesis and legal or economic analysis require models to process and resonate over sequences that exceed 100k-tokens. However, RL optimization in such regimes … Read more