The assumption that data visualization innovation is declining needs more evidence. Regardless the article asserts it’s true then contorts itself arguing for it

The assumption that data visualization innovation is declining needs more evidence. Regardless the article asserts it’s true then contorts itself arguing for it. As others have said - the “patterns” have been invented & some pretty good stuff is now out there. For example: - https://acko.net/tv/toolsforthought/ https://acko.net/tv/toolsforthought/ - https://ciechanow.ski/mechanical-watch/ https://ciechanow.ski/mechanical-watch/ - https://ciechanow.ski/bicycle/ https://ciechanow.ski/bicycle/ - many science & data exploration youtube channels There’s less need to create completely new techniques after the Cambrian Explosion is over, we already have a baseline of patterns & can draw from them & it’s less work. That doesn’t look as much like innovation but has plenty of value. Even cooler: thanks to dataviz folks past and present, plenty of visualization libraries exist, almost all are open source, and they work spectacularly well. Give your data to any reasonably new reasoning LLM; ask it something like “write some code to visualize the story that’s in this data”, and prepare to be wowed at what it can produce. Some examples: - https://x.com/omarsar0/status/1894164720862523651 https://x.com/omarsar0/status/1894164720862523651 - https://x.com/christiancooper/status/1881345352235954322 https://x.com/christiancooper/status/1881345352235954322 - https://reddit.com/r/ClaudeAI/comments/1ja1yal/claude_37_sonnet_making_3blue1brown_kind_of/ https://reddit.com/r/ClaudeAI/comments/1ja1yal/claude_37_son... The takeaway is be careful assuming something went away. Maybe new stuff is still happening but is a minority of the overall stuff that exists. There’s great data viz out there, none of which has gone away & all of which can be used as a starting point without inventing from scratch. The “invention rate” declining is part of the cycle.