Developing compact yet high-performing language models remains a significant challenge in artificial intelligence. Large-scale models often require extensive computational resources, making them ...

Agentic AI stands at the intersection of autonomy, intelligence, and adaptability, offering solutions that can sense, reason, and act in real or virtual environments with minimal human oversight. At ...

Knowledge graphs have been used tremendously in the field of enterprise lately, with their applications realized in multiple data forms from legal persons to registered capital and shareholder’s ...

Developing compact yet high-performing language models remains a significant challenge in artificial intelligence. Large-scale models often require extensive computational resources, making them ...

Large language models (LLMs) have become indispensable for various natural language processing applications, including machine translation, text summarization, and conversational AI. However, their ...

The critical issue of restricted access to high-quality reasoning datasets has limited open-source AI-driven logical and mathematical reasoning advancements. While proprietary models have leveraged ...

Yandex, a global tech company, develops and open-sources Perforator, an innovative tool for continuous real-time monitoring and analysis of servers and applications. Perforator helps developers ...

Vision-Language Models (VLMs) have significantly expanded AI’s ability to process multimodal information, yet they face persistent challenges. Proprietary models such as GPT-4V and Gemini-1.5-Pro ...

Reinforcement learning (RL) trains agents to make sequential decisions by maximizing cumulative rewards. It has diverse applications, including robotics, gaming, and automation, where agents interact ...

Large Language Models (LLMs) have emerged as transformative tools in research and industry, with their performance directly correlating to model size. However, training these massive models presents ...

Large Language Models (LLMs) have become an indispensable part of contemporary life, shaping the future of nearly every conceivable domain. They are widely acknowledged for their impressive ...

Post-training quantization (PTQ) focuses on reducing the size and improving the speed of large language models (LLMs) to make them more practical for real-world use. Such models require large data ...