An infrastructure engineer explores AI Engineering, defining the role and its focus on using pre-trained models, prompt engineering, and practical application building.
Explores performance optimizations for scikit-learn's GridSearchCV by using closed-form solutions and warm starts for specific linear models.
Testing a prompt technique inspired by 'The Office' to get more concise and detailed AI-generated explanations of technical concepts like Huber regression.
A 2025 year-in-review analysis of large language models (LLMs), covering key developments in reasoning, architecture, costs, and predictions for 2026.
A curated list of notable LLM research papers from the second half of 2025, categorized by topics like reasoning, training, and multimodal models.
A curated list of notable LLM (Large Language Model) research papers published from July to December 2025, categorized by topic.
A year-in-review blog post reflecting on machine learning course blogging, revisiting 'The Bitter Lesson', and critiquing trends in ML and economics.
Critique of causal inference in statistics, highlighting the flawed assumption that treatments have no impact on future outcomes, using cancer screening trials as an example.
Explains why large language models (LLMs) like ChatGPT generate factually incorrect or fabricated information, known as hallucinations.
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.
