Programming Leftovers

posted by Roy Schestowitz on Jul 05, 2026

• R / R-Script

  • DataGeeek ☛ Understanding Tail Analysis in Financial Markets

    In financial markets, distinguishing between information-driven movements and liquidity-driven shocks is critical. The reference study we based our work on highlights the importance of tail analysis: comparing Gaussian (thin-tailed) and Student‑t (fat-tailed) distributions to understand whether price changes are more likely to reflect genuine information or temporary liquidity imbalances.

• Python

  • Lalit Maganti ☛ Perfetto v57: fixing PyTorch traces, plus journald logs and an AI skill

    We just released Perfetto v57 and I wanted to share the new things I’m most excited about. This is something I wanted to do for past releases but I just never quite got round to it. It’s also something I plan on doing more of going forward: there might even be dedicated pieces if I think the feature deserves it!

  • Drew Breunig ☛ Understanding the Dynamics of the AI Ecosystem with Pace Layers

    Imagine: as these layers move at different rates, friction builds between them, slowing the upper layer and quickening the lower. This negotiation, translation, between the layers is constructive when their speeds are different, but in balance. When they’re not, things get weird.

  • Julia Language Blog Aggregator ☛ Metal.jl 1.10: Linear algebra, FFTs, and a faster runtime

    Metal.jl 1.10 is a big release. It adds native matrix multiplication, GPU-accelerated linear solvers and FFTs, BFloat16 support, and MPS-backed reductions, scans and sorting. The runtime also got considerably faster and leaner, and there is a new in-process profiler.

    Before getting into the new features, one thing to flag up front: Metal.jl 1.10 requires macOS 14 or later, up from macOS 13. On older systems the package now refuses to initialize, and Metal.functional() returns false. The supported range is macOS 14 through 26, on Julia 1.10 through 1.13.

• Raku and Perl

  • Perl ☛ The AI Revolution is Validating 40 Years of Perl Philosophy

    But if you've been paying attention to Perl since 1987, you know this isn't a revolution--it's a homecoming.

    When Larry Wall created Perl, he didn't just build a language to sit closer to the metal; he built it to sit closer to speech. While computer science worshiped at the altar of rigid mathematical purism, Perl introduced a context-aware structure built on nouns, verbs, singulars, and plurals.