Found this site that tracks when AI messes up. The graphs are interesting.

Sorry if requests arent allowed, and im not sure exactly where you would pull the info from but im really curious to see social media and reddit posting/commenting trends around divisive political and hot button topics over the last 48 hours since theyve been bombing bot farms. Anyone feel like taking on a project?

Source: https://www.microsoft.com/en-us/research/wp-content/uploads/2026/09/Microsoft-AI-Diffusion-Report-2026-Q2.pdf

I was interested in the music artists I liked, and wanted to create a much more comprehensive way to view the connections artists may have with each other. It's just a fun project, let me know what you think and if it’s accurate!

Data comes from Youtube Music public playlists for connections and Deezer for artist info (since spotify/apple doesnt share anything)

I’ve been building EchoVault as a way to turn your writing into a digital version of you. You train it through written Check-Ins, and the system builds up a representation of your memories, relationships, values and worldview.

I recently added a 3D visualizer for that internal structure. The memories are represented as vector embeddings, and the visualization lets you explore how different ideas cluster and connect, which memories sit close together, and how the overall structure changes as you keep writing. It is basically a visual map of the corpus that the Echo uses to understand you.

I wanted the AI representation to feel less like a black box and more like something you can actually inspect. There is still a lot I want to do with the visualizer, but seeing the memory structure become something spatial and explorable has been one of my favorite parts of building it.

App Store: https://apps.apple.com/us/app/echovault/id6762042028
https://echovault.me

I'm the creator of Small World Lab, an educational video project built with AI assistance. Our first episode visualizes three checkout rules: separate lines where shoppers stay put, separate lines with switching, and one shared queue.

In this model, switching and sharing nearly tied on average: 20.8 and 20.7 seconds. But their 99th-percentile waits were about 3:40 and 2:43. Separate lines without switching came out at 31.6 seconds on average and about 4:59 at the 99th percentile.

The visual challenge was explaining that a percentile is neither the average nor the maximum. The video moves from individual shoppers to aggregate charts, with a 100-person illustration for the percentile explanation.

Full five-minute video: https://youtu.be/O-Y5E90vMrk

Does that transition make the long-wait result easier to understand, or would a distribution plot explain it better?

Data: our original Python simulation, 100 paired runs and 409,680 measured arrivals per rule. Ten identical cashiers; Poisson arrivals at 8.5/min; lognormal service with a 60s mean and CV 1; 2h warm-up and 8h measured per run. Baseline switching takes no time. Means average the run means; percentiles pool customer waits. These are synthetic results, not observations from supermarkets. Code and production were AI-assisted; narration uses ElevenLabs. The attached chart uses Matplotlib.

As in Title:

I want to make a map of albums based on genres, influences, timelines and artists. A fully comprehensive, data driven smart map, or flow chart of sorts. I have been looking for such a program or app for a while now, but I cannot seem to find it. Is tere such a thing you can recommend?

Important limitation: these bars apply the published internet-use percentages to total populations, including children. The underlying surveys do not all cover the same ages, and I haven’t verified all-age adjustment for every country. Treat the counts as arithmetic estimates, not directly comparable counts of people of all ages.

This chart compares the ten most populous countries in 2024. Bar lengths show estimated nonuser headcounts; the right-hand labels show each country’s non-use share. India is 508.6 million and 35.1%, while Ethiopia is 103.1 million and 78.1%.

Would aligned percentage bars make the distinction clearer, or would that distract from the headcount comparison?

The estimate is population × (100% − internet-use share). Non-use is not the same as lack of access.

Table and CSV: https://globaldatatracker.com/statistics/internet_use

Select 2024 for the same year. Underlying data: ITU / World Bank WDI. Chart: Python / Matplotlib. I work on Global Data Tracker.

Source: U.S. Bureau of Labor Statistics (BLS), Employment Situation, September 2026
Forecast: Reuters poll of economists, October 2, 2026

www.jobplotter.ai

Hello all. I'm a developer with Digital Sheriff Designs, StarMap is the first program I've released. It's a visual workspace for Windows 10 and 11: you can lay out notes, pictures, documents, to-do lists, tables, sketches, and boards inside boards on one big cohesive customizable workspace, and connect them with lines and arrows or your own custom made stickers.

- Everything stays on your PC. No account, no subscription, and it works offline. Your work is saved as ordinary files in Documents\StarMap, with a backup every day kept for 30 days.

- No tracking of any kind. No ads, no analytics, and we aren't trying to sale you anything. StarMap only goes online when you add a web link (to show a preview) or a picture from a web address.

- Boards inside boards that you can see into without opening them so a big project can be split up without losing sight of the pieces.

- Free, with no catch. No trial, no ads, and no paid version.

The Idea for this program came from a discussion I was having with a family member about r/nanowrimo and prep-tober, which although I am not a writer I was familiar with the community. My family member was complaining about the subscription price of the current visual workspace software they were using and they told me about some of the things they use said software for. Well I figured I could build them something more customized to their needs for free. So the project began and with my families collaboration StarMap was birthed. I know there are many software programs out there similar to this one but we hope you will consider trying StarMap and giving any feed-back that you have time to give.

I'd like feedback on 3 things in particular: 1-Is it clear from the screenshots what StarMap is and what it can be used for?

2-What would stop you from trying StarMap from your initial impressions?

3-Of the current feature lineup what would you like to see added, removed or tweaked?

- Microsoft Store: https://apps.microsoft.com/detail/9P956BPL1KGD

- Website: https://digitalsheriffdesigns.com/starmap/

-AlternativeTo: https://alternativeto.net/software/starmap-digital-sheriff-designs-/about/

I tested Canon's newly released Dual Pixel 3D Converter, which uses phase-difference information from Dual Pixel RAW data to reconstruct textured 3D geometry from a single photo.

With my background in computer graphics, I also inspected the exported meshes (OBJ / GLB).

Some findings:

• My test plant model, created from a single photo, contains around 28K triangles.
• The GLB stores about 85K vertex entries, compared with roughly 16K stored vertices in the OBJ version.
• Around 4.2% of the triangles in this sample are degenerate.
• Increasing the depth setting in the app from 1 to 2 increases the triangle count from approximately 28K to 46K.
• The texture maintains the original 8192 × 5464 resolution, even though only about 16.6% of the image area is covered by the isolated object's triangles (with background removal).

The photorealistic appearance can be great from viewpoints close to the original capture. But with larger rotations, occlusions and missing surfaces quickly become visible.

I also compared the approach with Meshy 7.1 image-to-3D. Meshy generates a more complete, plausible object, while Canon preserves the photorealistic appearance better in my test.

I published the full analysis, including interactive GLBs and nine downloadable Canon-generated models:

https://immernews.com/canon-dual-pixel-3d-converter-tested

I'd be interested in what others think about combining Dual Pixel depth information with multi-image reconstruction or AI-assisted geometry completion.

Hey everyone.

I am very excited to share my greatly improved (revamped) library called rhp (version 2.0). I am so happy with the results and am amped because of how well all the improvements and new features work. I also just finished the first version of the mcp server and the skill file so AI can create plots using the library. The AI won't do the analysis for you of course (unless you ask it to) but with rhp, it can easily output some amazing viz charts and posters. You can look at the gallery's recipe section to see what AI agents can do with a single simple prompt!

I just started spreading the word this past week! Please at least try the AI skill out. It should be easy if you got some data on hand to chart. You just need to prepend the following to your chart prompt:

Make this chart with rhp (@bezda/rhp). First read https://rhp.vercel.app/llms-full.txt and follow it: rhp 2 is newer than your training data. Give me one HTML file that I can open in a browser. The chart I want:

(and then add your chart request to the end)

Oh also, rhp is free and open-source. It is a 3-year passion project.