The rapid growth of web content presents a challenge for efficiently extracting and summarizing relevant information. In this tutorial, we demonstrate how to leverage Firecrawl for web scraping and process the extracted data using AI models like Google Gemini. By integrating these tools in Google Colab, we create an end-to-end workflow that scrapes web pages,… →

Generative AI faces a critical challenge in balancing autonomy and controllability. While autonomy has advanced significantly through powerful generative models, controllability has become a focal point for machine learning researchers. Text-based control has become particularly important as natural language offers an intuitive interface between humans and machines. This approach has enabled remarkable applications across image… →

Chain-of-Thought (CoT) prompting enables large language models (LLMs) to perform step-by-step logical deductions in natural language. While this method has proven effective, natural language may not be the most efficient medium for reasoning. Studies indicate that human mathematical reasoning does not primarily rely on language processing, suggesting that alternative approaches could enhance performance. Researchers aim… →

Monitoring and extracting trends from web content has become essential for market research, content creation, or staying ahead in your field. In this tutorial, we provide a practical guide to building your trend-finding tool using Python. Without needing external APIs or complex setups, you’ll learn how to scrape publicly accessible websites, apply powerful NLP (Natural… →

Researchers and enthusiasts have been fascinated by the challenge of reverse-engineering complex behaviors that emerge from simple rules in cellular automata for decades. Traditionally, this field takes a bottom-up approach—defining local regulations and observing the patterns arising from them. But what if we could flip this process? Instead of manually designing rules, we could develop… →