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11 articles
NYU mathematician accuses OpenAI of unethical tactics in pursuit of solving the $1 million Navier-Stokes problem, sparking debate over AI's role in mathematical research.
Learn to build an AI-powered scientific discovery tool using Python and machine learning libraries. This tutorial demonstrates data processing, model training, and prediction techniques used by top AI researchers.
Learn how to create and fine-tune foundation models using Hugging Face's Transformers library, similar to Amazon's Frontier research team approach.
Learn to build a stateful search harness system inspired by Harness-1, a 20B parameter retrieval subagent trained with reinforcement learning. This tutorial teaches you to implement candidate pooling, evidence graph maintenance, and reinforcement learning-based decision making.
This article explains the technical concepts behind Large Language Models (LLMs) and why major companies like Airbnb are investing in proprietary AI research labs rather than relying on external partnerships.
Learn about Audio Flamingo Next (AF-Next), a new AI system that understands and describes sounds like images, opening up new possibilities for accessibility and smart technology.
Learn to build an AI research collaboration dashboard that tracks geopolitical patterns in research output, helping researchers navigate international collaboration challenges.
Learn how to implement automated hyperparameter optimization for AI model training, demonstrating how systems can find improvements that human researchers might miss.
Learn how to build a data extraction pipeline using Gemini models to transform unstructured news reports into structured disaster event data, similar to Google's Groundsource methodology.
Learn how to use Python and symbolic mathematics to explore theoretical physics concepts similar to those tackled by GPT-5.2, including creating mathematical models, performing symbolic manipulations, and validating results.
Google DeepMind researchers have used semantic evolution to create non-intuitive variants of VAD-CFR and SHOR-PSRO algorithms, significantly improving algorithmic convergence in multi-agent reinforcement learning.
