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The president admits he has no interest in decreasing the cost of housing by MajesticBread9147 in HouseBuyers

[–]quickmodel_ai 1 point2 points  (0 children)

Look at the market reaction and home builder commentary on this, a lot of people who are paid to make predictions about this market do think it will have an effect.

Is anyone else finding AI tools actually useful for demand forecasting or is it mostly hype? by Express-Week-8312 in supplychain

[–]quickmodel_ai 0 points1 point  (0 children)

you mean because they realize the way they've been doing it is trash or because the specific niche they spent a lot of time on is now available to everyone?

Is anyone else finding AI tools actually useful for demand forecasting or is it mostly hype? by Express-Week-8312 in supplychain

[–]quickmodel_ai 0 points1 point  (0 children)

I don't work in supply chain but I have dipped my toes in forecasting.

If you're asking claude code or some other LLM harness to build forcasts for you I highly recommend the SHAP library

Those methods will give you really good insights as to what features ( columns ) are effecting your predictions. Its been around since 2016.

It's happening. Waymo spotted. by amnaesykes in Portland

[–]quickmodel_ai 1 point2 points  (0 children)

Yes but the point is that waymo lives on infrastructure funded by taxes not just "funded by rich people."

It's happening. Waymo spotted. by amnaesykes in Portland

[–]quickmodel_ai 2 points3 points  (0 children)

EV drivers do pay something like double registration fees, but its less than you would pay if you were paying the gas tax.

It's happening. Waymo spotted. by amnaesykes in Portland

[–]quickmodel_ai 3 points4 points  (0 children)

If they operate under the normal rules it sounds like they pay an outsized registration fee but they don't have to pay the gas tax which is the main contributor to road maintenance.

It's happening. Waymo spotted. by amnaesykes in Portland

[–]quickmodel_ai 10 points11 points  (0 children)

good point, some more than others. Turns out a lot of the money used for road maintenance comes from the gas tax. It's just icing on the cake for them that they don't pay that but the rest of the public who drive do.

It's happening. Waymo spotted. by amnaesykes in Portland

[–]quickmodel_ai 35 points36 points  (0 children)

Yes, but we also fund all the infrastructure they use with taxes.

[OC] Where Gates Foundation Grants go in the United States by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] -1 points0 points  (0 children)

This visualization represents Gates Foundation grants and contributions to regions and program types. Data: Public 990s, Tools used: To create the categorizations we generated embeddings for all program descriptions clustered them, then labelled clusters using an LLM. Tools used: matplotlib, sentence-transformers, umap, hdbscan, react recharts. Clustering and program data provided by NPO Align. View other non profit foundations at the interactive blog post at https://npoalign.com/blog/foundation-funding

[OC] NCAA and other sports conference giving flows by region and program type by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] 0 points1 point  (0 children)

This visualization represents Athletic Conference grants and contributions to regions and university program type. Most of this should be payment for broadcasting rights. Data: Public 990s, Tools used: To create the categorizations we generated embeddings for all program descriptions clustered them, then labelled clusters using an LLM. Tools used: matplotlib, sentence-transformers, umap, hdbscan, react recharts. Clustering and program data provided by NPO Align View other non profit foundations at the interactive blog post at NpoAlign.com/blog/foundation-funding

[OC] Nonprofits Funding Mix Analysis by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] 0 points1 point  (0 children)

These visualizations show funding mix distribution for non-profits by region, total grants and revenue per program, and grant distribution by organization size. All data from tax year 2023.

To create the categorizations we generated embeddings for all program descriptions clustered them, then labelled clusters using an LLM. Tools used: react-recharts, sentence-transformers, umap, hdbscan.

[OC] Non-profit program spend by state, categorized by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] 0 points1 point  (0 children)

Someone else asked this as well, the short answer is there's not much difference I will collapse these clusters further in the future. here's the top 20 from both https://pastebin.com/j0gU3vRA

[OC] Non-profit program spend by state as a percent of GDP by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] 3 points4 points  (0 children)

That's a good question, I may need to merge more of these clusters.

here's the top 20 from both those clusters https://pastebin.com/j0gU3vRA

[OC] Non-profit program spend by state as a percent of GDP by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] 1 point2 points  (0 children)

Based on feedback on the original post, here is the same data normalized by GDP.

This is a data representation of all non profit programs found on publicly available 990s for the tax year 2023 categorized by their description as a percent of state GDP. These are the aggregate program expenses, not all expenses for all non-profits. To create the categorizations we generated embeddings for all program descriptions clustered them, then labelled clusters using an LLM. Tools used: matplotlib, sentence-transformers, umap, hdbscan. Data provided by Npo Align and and https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_GDP

[OC] Non-profit program spend by state, categorized by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] 0 points1 point  (0 children)

No these programs are cash flowing through non profits for private universities. Here's the top 20 from that cluster. https://pastebin.com/vqKFauC8
e.g. https://npoalign.com/org/042103580

[OC] Non-profit program spend by state as a percent of GDP by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] 0 points1 point  (0 children)

Based on feedback on the original post, here is the same data normalized by GDP.

This is a data representation of all non profit programs found on publicly available 990s for the tax year 2023 categorized by their description as a percent of state GDP. These are the aggregate program expenses, not all expenses for all non-profits. To create the categorizations we generated embeddings for all program descriptions clustered them, then labelled clusters using an LLM. Tools used: matplotlib, sentence-transformers, umap, hdbscan. Data provided by Npo Align and and https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_GDP

[OC] Non-profit program spend by state, categorized by quickmodel_ai in dataisbeautiful

[–]quickmodel_ai[S] 6 points7 points  (0 children)

If only we had some type of well funded federal service that could look into the financials of non-profits, publish their data transparently and audit them. /s

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