sql vs pandas vs ai agents for analytics
a comparison of sql, pandas, and a claude agent on three analytics problems across speed, accuracy, and other dimensions.
topic
data science
treat pdfs as images for zero-shot parsing with gemma 4
render pdf pages to images and use gemma 4 to extract structured data without ocr or layout parsers.
10 probability concepts for machine learning
a plain-language guide to ten essential probability ideas that make machine learning work, from random variables to entropy.
cora: per-slice orthogonal rotation for svd-based low-rank adaptation
cora introduces per-slice coherent orthogonal rotations to preserve pretrained geometry in svd-based fine-tuning, improving parameter efficiency.
data scientists shift to ai oversight roles
data scientists now spend more time managing ai systems than building models, with new roles in governance, prompt engineering, and agent supervision.
hugging face ml intern: your first ml agent
a cli agent that automates machine learning tasks from plain english descriptions, handling coding, training, and model publishing.
small language models power next-gen agents
small language models are replacing large models for repetitive agent tasks, offering speed, cost savings, and on-device privacy.
daily brief: 2026-07-04
midjourney pushes hollywood on ai transparency, meta's agent progress stalls, and open source ai gaps get mapped.
daily brief: 2026-07-03
today's digest covers new ai tools, research on neural nets and time series, and a reality check on ai hype.
getting started with the claude api in python
learn to set up the claude python sdk, make api calls, handle responses, use system prompts, and stream output.
shallow neural nets as smooth variational problems
a new formulation replaces discrete neural network training with a globally well-posed variational problem over parameter densities, enabling direct solution via a linear system.
measuring lag relevance in time series forecasts
new model-agnostic method uses shapley values and ghost variables to measure lag importance in univariate time series forecasting.
daily brief: 2026-07-02
meta quietly ships an ai game maker, openai proposes a stake in a us wealth fund, and researchers rethink how we measure machine intelligence.
10 agentic ai frameworks to know in 2026
a rundown of ten agentic ai frameworks, from langgraph to llamaindex workflows, with notes on their strengths and best use cases.
how low-dimensional data structure shapes classification
a mathematical framework extends cover's function-counting theory to analyze how low-dimensional data structure affects binary classification capacity and generalization.
humanity's last exam is a distraction
a look at the hle benchmark, why it was created, and the divided expert opinions on its value for evaluating ai systems.
fourier neural operators learn pde solutions efficiently
new theory proves fourier neural operators can approximate and learn time-dependent solutions of dissipative partial differential equations with polynomial sample complexity.
deep multitask learning for mixed outcomes with shared sparsity
a new method uses deep neural networks and rank-based optimization to handle mixed outcome types in multitask learning with shared predictor selection.