Table of Contents 1âIntroduction: The Limits of Current AI Cognition 1.1âThe Grand Challenge of Generalizable AI Artificial General Intelligence (AGI) aspires to matchâor exceedâhuman versatility: the capacity to reason across domains, remember experiences over a lifetime, and fluidly fuse perception with abstract thought. Contemporary large-language models (LLMs) have narrowed the gap in surface competence, writing […]
1. Technical Architecture Overview and Design: Alibabaâs Babel is an open-source multilingual large language model (LLM) developed to bridge language gaps in AI. It covers the top 25 most-spoken languages, collectively spoken by over 90% of the global population (Babel – Open Multilingual Large Language Models Serving Over 90% of Global Speakers). Babelâs core architecture […]
Agentic Retrieval-Augmented Generation (RAG) represents a significant advancement in AI technology, combining large language models (LLMs) with intelligent retrieval mechanisms. This paradigm shift enables systems to dynamically manage information retrieval, enhancing decision-making and problem-solving capabilities. This report explores the latest advancements in Agentic RAG, including enhanced decision-making, multi-modal retrieval, and multi-agent systems, and discusses their […]
Google’s Data Science Agent, powered by the advanced Gemini 2.0 model, represents a significant leap in automating and enhancing data analysis workflows within Google Colab. This tool is designed to simplify complex data tasks, making data science more accessible and efficient for users across various skill levels.â Key Features: Gemini 2.0 Capabilities: The integration of […]
