Explores the trend of smart model routing to reduce AI costs by automatically selecting the best LLM for each task.
A critical take on AI, arguing it's not a person and shouldn't be anthropomorphized.
A plain English guide explaining how LLMs like ChatGPT actually work, covering prediction, vectors, embeddings, and common misconceptions.
Explores how relying on AI for coding without active learning degrades skills, backed by research showing cognitive debt.
Explores 'the inversion' concept from YouTube engineers in 2013, where bot traffic threatened to surpass human views, challenging algorithm design.
A reflection on the Mythos AI model, arguing it's just the next step in rapid AI evolution, not a shocking breakthrough.
An expert discusses the overhyped risks and data limitations of applying AI in life sciences, using examples like AlphaFold.
Explores the balance between model simplicity and precision in system identification for control engineering and machine learning.
Argues for using general SOTA AI models over custom, specialized ones, predicting cheaper, open-source general models will dominate.
A critique of how quantitative benchmarking and evaluation culture shapes and potentially distorts progress in machine learning research.
Explores how autonomous AI agents (autoresearch) can optimize small language models by running hundreds of experiments overnight, improving performance without human intervention.
Analyzes the hidden costs and skill erosion of using AI for coding, emphasizing the need for human oversight.
Exploring the UMAP-MLX project, which achieves up to 46x speedups for UMAP using Apple's MLX, with performance benchmarks.
A skeptic's detailed journey using AI coding agents for complex projects, including porting scikit-learn to Rust, showcasing their surprising capabilities.
A skeptic's detailed journey using AI coding agents to port scikit-learn to Rust, showcasing the surprising capabilities of modern LLMs.
An update on the PRISM project's progress in developing methods for validating spatial patterns in machine learning, covering research from 2025-2026.
Explores the theoretical links between optimization algorithms (like gradient descent) and control theory, analyzing them as dynamical systems.
Author shares their experience and study strategy for passing Microsoft's AI-900 Azure AI Fundamentals certification exam.
A blog post discussing a New York Times article about Moltbook, a social network exclusively for AI bots, and the author's insights on AI behavior.
A blog post discussing a social network exclusively for AI bots, exploring their interactions and the implications of their sci-fi influenced conversations.
