(2022-08-16) Martin Render Recap
Jess Martin: Render Recap - (2022-08-16) BetaWorks Render Tools for Thinking: where's the scene at?
packed with around 75 technologists
The main livestream is available as one long, 6-hour recording. Once it's cut into individual videos and re-posted, I will embed links to the individual talks below.
Jerry Michalski and John Borthwick's Introduction
Betaworks will be hosting ThinkCamp this fall, a 10-week accelerator program for Tools for Thinking startups. 8-10 companies, $250k pre-seed investment. Applications due by August 26th. Jerry will be helping Betaworks in some capacity with ThinkCamp.
A Readwise Rewrite: Tristan Howsi and Daniel Doyon
Howard Rheingold and a trip into TFT History
Themes
Interop All The Things
From Silos to Portfolios.
portfolio of tools, working together, to build their workflows
"We're so early."
the current state of these early tools is what Paul Graham wrote about in Early Work: Many great projects go through a stage early on where they don't seem very impressive, even to their creators. You have to push through this stage to reach the great work that lies beyond. But many people don't.
Why do I think we're early? A lot of reasons. We are still struggling to understand what computers as a medium are capable of. (media inventor)
A flood of new technologies has opened new doors in the adjacent possible: machine learning and artificial intelligence, powerful browser APIs like FileSystem, decentralized technologies flowing out of web3 like IPFS.
You need colleagues who can actually tell an ugly duckling from a baby swan
Interface is the key (UX)
So many of the new technologies mentioned above simply don't have well-understood user experience for working with them.
Even so simple and long-lived an idea of transclusion doesn't have a well-adopted user interface
Spatial canvases proliferate, but each takes a slightly different approach to core navigational issues like pan and zoom, selection of objects, navigation between canvases, search, even adding an item to the canvas.
how do you bring together the results of these parallel explorations? How can we learn faster?
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