During the week, I often collect and share links I find interesting on Elder Research’s Slack. I shared a short list on LinkedIn and reproduce it here.
A short link roundup for this week:
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More writing about LLMs and programming. There are some real long-term concerns around ‘LLM dependency,’ but they do seem to provide a real boost to more senior folks. Matt Bezdek points out, too, that good StackOverflow answers come from folks with deep subject knowledge, which is something LLMs just don’t have (yet?); the ability to edit and augment generated code is super important.
“New Junior Developers Can’t Actually Code
“The 70% problem: Hard truths about AI-assisted coding” -
Gaussian processes vs. FFTs or Fourier terms in models. GPs are expensive (though Hilbert space GPs are better), but they fit data in a more natural space (time, not frequency).
“Modeling Autocorrelation: FFT vs Gaussian Processes”
“State Space Models and Structural Time Series, with Jesse Grabowski” -
A neat idea for a prior (ARR2) that conditions time-series models based on expected R-squared (e.g., neither 0 nor 1) and makes models more robust.
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A review of the excellent uv tool set for Python, one year on. (Spoiler: It’s a really good tool.)
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A gallery of figures with accompanying code for producing them using base R graphics. (I like ggplot2 just fine but would like to use the base system more.)