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By Nathan Yau. A combination of highlighting others’ work and visualization guides.
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Movie runtimes framed by life expectancy

2024-11-22 18:09:19

Memento Movi, a mini-app by Michael Condouris, is what you get when you use movies as a progress bar for life expectancy. Enter your birthdate and expected lifespan. Then select a movie from the list. The percentage of your life that you’ve lived is translated to the percentage through the movie you would be, which gives you the frame in the movie.

I swear this was made just for me. [via Waxy]

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Rainbow Sky, the colors mentioned on Bluesky

2024-11-22 16:56:08

Martin Wattenberg drew up a live visualization that shows colors mentioned in Bluesky posts, via the firehose. Just let the wave of calm wash over you.

I’m sure there are many more mashups to come, but I’ll probably shift anymore sharing to Bluesky itself, so as not to inundate you with a firehose about using the firehose. It’s just refreshing to see data flowing freely after companies moving the other direction over the past several years.

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✚ Visualization Tools and Learning Resources, November 2024 Roundup

2024-11-22 03:30:08

Hi. Nathan Yau here. This is the Process, the newsletter for FlowingData members about making and using visualization and data. Every month, I collect useful tools, datasets, and resources to help you with that. With Thanksgiving coming up next week here in the states, this month’s roundup arrives early.

Become a member for access to this — plus tutorials, courses, and guides.

Our World in Data wants you to use their data with improved export and API

2024-11-22 01:27:39

Our World in Data is a hub for research and reliable data to measure the progress of the world. You’ve always been able to download data from the site, but they just made it easier with more detailed exports and an API:

For users who work with automated workflows, computational notebooks, or custom applications, we now offer direct URLs to access data in CSV format and comprehensive metadata in JSON format. This is the same data and metadata included in the zip file download package described above.

Just like with the download package, you can fetch the complete data or only the subset of the data currently displayed in the chart. You can also choose between longer column names that are easier to read for humans or shorter column names that are often more convenient to use in code.

Great news.

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LLM-driven robot made of garbage

2024-11-21 18:16:01

We like to imagine a world of autonomous robots that take care of tedious tasks so that we don’t have to. Chris Fenton likes to imagine robots made of garbage that roam around his backyard, and Grasso was born:

Who says AGI has to be super intelligent just to be A, G and I? Grasso is driven by a kind of python ‘madlib’ wrapped around two LLMs (one multi-modal, one text-only). The outer loop takes a photo with its webcam and feeds it into a multi-modal LLM to generate a scene description. That scene description is then inserted into a prompt (“This is what you currently see with your robot eyes…”) that ends with “Choose your next action” and presents a list of actions the robot can take, some of which are ‘direct’ commands, and others that are ‘open ended’ and let Grasso finish the action prompt however it chooses.

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