China: “Remove all VPNs”
Apple: “Sure thing”
China: “…and podcast apps”
Apple: “Can do boss!”
China: “…and also hand over all iCloud data for our citizens”
Apple: “I mean why wouldn’t we? Here you go!”
EU: “Allow alternate app stores, and do it fairly”
Apple: “Ahhh hell no! This is so unfair you guys are bullies! Malware! Privacy! We have standards! Unlike you we care about our users!”
One day I’d like to write a “Senior Software Engineer” chatbot that randomly responds to questions with answers like:
- “It depends…”
- “What are you trying to accomplish?”
- “You’re asking the wrong question.”
{stplanr} is an #rstats 📦”for sustainable transport planning with R.”
“It provides functions for solving common problems in transport planning and modelling, such as how to best get from point A to point B. The overall aim is to provide a reproducible, transparent and accessible toolkit to help people better understand transport systems and inform policy.” By @robinlovelace & others, docs at @rOpenSci 📦
https://docs.ropensci.org/stplanr/
Tools for transport planning with an emphasis on spatial transport data and non-motorized modes. The package was originally developed to support the Propensity to Cycle Tool, a publicly available strategic cycle network planning tool (Lovelace et al. 2017) <doi:10.5198/jtlu.2016.862>, but has since been extended to support public transport routing and accessibility analysis (Moreno-Monroy et al. 2017) <doi:10.1016/j.jtrangeo.2017.08.012> and routing with locally hosted routing engines such as OSRM (Lowans et al. 2023) <doi:10.1016/j.enconman.2023.117337>. The main functions are for creating and manipulating geographic "desire lines" from origin-destination (OD) data (building on the od package); calculating routes on the transport network locally and via interfaces to routing services such as <https://cyclestreets.net/> (Desjardins et al. 2021) <doi:10.1007/s11116-021-10197-1>; and calculating route segment attributes such as bearing. The package implements the travel flow aggregration method described in Morgan and Lovelace (2020) <doi:10.1177/2399808320942779> and the OD jittering method described in Lovelace et al. (2022) <doi:10.32866/001c.33873>. Further information on the package's aim and scope can be found in the vignettes and in a paper in the R Journal (Lovelace and Ellison 2018) <doi:10.32614/RJ-2018-053>, and in a paper outlining the landscape of open source software for geographic methods in transport planning (Lovelace, 2021) <doi:10.1007/s10109-020-00342-2>.
I'm writing a thing on safety standards for AI/LLM use in transport modelling. I would love to how y'all are using LLMs for modelling purposes.
Please do reshare if you can so I can get a wider sample size.
Y’all, we need to have a Talk about relatively well-meaning but sexist assumptions. I’m not singling anyone out - this happens to me a lot.
I get routine pings to speak, present, or serve on boards related to educating kids (especially girls) on tech, and build DEI programs. The people who ask usually start with “because you are an expert on it”.
I am very happy to be an expert on a few things - namely digital forensics and incident response and industrial cybersecurity. I’m passable at threat intel and OSINT. It wouldn’t be embarrassing for me to talk about martial arts.
However, I have zero training on DEI or girls in tech initiatives (that’s a whole real career field), and I have no children. I’m don’t even have biological nieces or nephews. If you’re saying you think I’m an expert at that, it means someone is just looking at how I appear and making assumptions, then asking me to do free work. Others may not be as chill about this.
Russell Ivanovic
Lorin Hochstein 
Nic Magnier
Sharon Machlis
Marc Hedlund
Lesley Carhart 
Tim Gent
Adrienne 📊
Scott Santens