Flickr user Agatha Barc has some albums of historical postcards of Toronto and the University of Toronto. To me, they provide the contrasting thrills of seeing buildings that look just as they do today and seeing whole areas (like around city hall) that are now unrecognizable.
TO360 wayfinding consultation
Though I had noticed some of their signage (and, without knowing it, their printed Toronto cycling map has been a key planning tool for our urban hikes), I did not actually know about the city’s TO360 wayfinding project until I saw a post about it a few days ago.
They are currently working on the Long Branch area west of Humber Bay, and held a consultation yesterday at the local library.
The consultation was unlike anything I have done, and really cool. Some knowledgeable local residents turned up, and the TO360 people had printed maps the size of large dinner tables where people could correct errors, note things that ought to be included, and suggest places where they should include custom graphics for something like a building or monument rather than a generic labelled marker. It’s awesome to see a group with so much capability and official support working to map the city from a non-driving perspective.
As shown on p. 11 of the slides, the group is working through the whole GTA as they are funded by the city. It would be neat to explore new areas as they focus on them and contribute to forthcoming consultations. The results won’t just be used for map posts on the street and map posters in subway stations, but also future versions of the cycling map.
TMU GIS certificate
This program at Toronto Metropolitan University looks pretty cool: Applied Digital Geography and GIS
Choir photos
Yesterday I photographed the Opus 8 choir at St. Thomas’s Anglican Church: Opus 8 choir at St. Thomas’s Anglican Church
Composite of Pandemic Walks in the GTA
Pandemic walks exploring North York
Composite animation of Tristan’s Walking Club excursions
Animated using RunParticles
Commonality of photography and cartography
Limits of ChatGPT
With the world discussing AI that writes, a recent post from Bret Devereaux at A Collection of Unmitigated Pedantry offers a useful corrective, both about how present-day large language models like GPT-3 and ChatGPT are far less intelligent and capable than naive users assume, and how they pose less of a challenge than feared to writing.
I would say the key point to take away is remembering that these systems are just a blender that mixes and matches words based on probability. They cannot understand the simplest thing, and so their output will never be authoritative or credible without manual human checking. As mix-and-matchers they can also never be original — only capable of emulating what is common in what they have already seen.
