Reasoning tasks are a fundamental aspect of artificial intelligence, encompassing areas like commonsense understanding, mathematical problem-solving, and symbolic reasoning. These tasks often involve multiple steps of logical inference, which large language models (LLMs) attempt to mimic through structured approaches such…
In this tutorial, we implement the Agent Communication Protocol (ACP) through building a flexible, ACP-compliant messaging system in Python, leveraging Google’s Gemini API for natural language processing. Beginning with the installation and configuration of the google-generativeai library, the tutorial introduces…
State-of-the-art models show human-competitive accuracy on AIME, GPQA, MATH-500, and OlympiadBench, solving Olympiad-level problems. Recent multimodal foundation models have advanced benchmarks for disciplinary knowledge and mathematical reasoning. However, these evaluations miss a crucial aspect of machine intelligence: physical reasoning, which…
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…
Biomedical research is a rapidly evolving field that seeks to advance human health by uncovering the mechanisms behind diseases, identifying new therapeutic targets, and developing effective treatments. This field encompasses diverse areas, including genetics, molecular biology, pharmacology, and clinical studies,…
DeepSeek, the Chinese AI Unicorn, has released an updated version of its R1 reasoning model, named DeepSeek-R1-0528. This release enhances the model’s capabilities in mathematics, programming, and general logical reasoning, positioning it as a formidable open-source alternative to leading models…
Long CoT reasoning improves large language models’ performance on complex tasks but comes with drawbacks. The typical “think-then-answer” method slows down response times, disrupting real-time interactions like those in chatbots. It also risks inaccuracies, as errors in earlier reasoning steps…
Video generation models have become a core technology for creating dynamic content by transforming text prompts into high-quality video sequences. Diffusion models, in particular, have established themselves as a leading approach for this task. These models work by starting from…
In this tutorial, we will explore how to create a sophisticated Self-Improving AI Agent using Google’s cutting-edge Gemini API. This self-improving agent demonstrates autonomous problem-solving, dynamically evaluates performance, learns from successes and failures, and iteratively enhances its capabilities through reflective…
In recent months, there has been growing interest in applying diffusion models—originally designed for continuous data, such as images—to natural language processing tasks. This has led to the development of Discrete Diffusion Language Models (DLMs), which treat text generation as…
