A critique of using AI to automate science, arguing that metrics have become goals, distorting scientific progress.
A professor shares open research problems inspired by his graduate machine learning class, focusing on design-based ML and competitive testing theory.
A lecture reflection on the gap between mathematical theory and practical engineering in machine learning, arguing for social analysis over functional analysis.
A machine learning professor critiques the foundational concept of a 'data-generating distribution' and shares insights from teaching a truly distribution-free course.
A timeline of beginner-friendly 'Hello World' examples in machine learning and AI, from Random Forests in 2013 to modern RLVR models in 2025.
A historical overview of beginner-friendly 'Hello World' examples in machine learning and AI, from 2013's Random Forests to 2025's Qwen3 with RLVR.
A developer builds a motion-controlled Street Fighter game using a Bangle.js smartwatch, WebAI, and TensorFlow.js for gesture recognition.
A critique of Reformist RL's inefficiency and a proposal for more effective alternatives in reinforcement learning.
A simplified, non-technical definition of reinforcement learning as an iterative optimization process based on external feedback.
A technical lecture on applying policy gradient methods to derive optimization algorithms, focusing on the unbiased gradient estimator and its applications.
Summary of a talk on using R for geospatial predictive mapping, covering methods like Kriging and Random Forests, and tools for evaluating prediction reliability.
Discusses handling class imbalance in predictive modeling, using medical and zebra analogies to explain adjusting for prior probabilities and error costs.
Explores the fundamental differences between animal intelligence and AI/LLM intelligence, focusing on their distinct evolutionary and optimization pressures.
Analysis of the rising prominence of Chinese AI labs like DeepSeek and Kimi in the global AI landscape and their rapid technological advancements.
Explores the concept of 'human collapse' from a tech podcast, arguing for seeking 'entropy' and new inputs to stay creative and unpredictable, with mentions of AI tools.
Explores the concept of AI Agents, defining them and examining their role in the AI ecosystem, with references to LangChain and Anthropic.
A list of over 50 Python project ideas for beginners and advanced learners, covering algorithms, networking, and machine learning.
Explains the difference between AI and Machine Learning, with AI as the goal of intelligent systems and ML as a key approach to achieve it.
A blog post exploring the differences between AI and ML, clarifying terminology and common misconceptions in the field.
Explains how rerankers improve search and AI results by reordering retrieved documents for better precision and relevance.
