It looks like you require an email address just to provide a link to the podcast you listed. I don't buy that it is necessary to prevent scrapers.

There's a deeper issue which the author touches on, showing too much information on a map. This is possible independent of technology limits depending on what level of focus you wish each point to have. For many maps, showing a bunch of small points is an elegant solution, the map turns into more of a data visualization. But a bunch of points tells you very little about a particular thing. It is rich in aggregated information and poor in specific information.

If Google Maps just gave you a bunch of points instead of labels, it would be less functional. Every city would just be a large collection of points. Great, that might be interesting if you want to visualize how the locations are distributed in the region, but you are probably looking at the map because you want to find a particular thing.

Clustering is the natural choice: show the most important thing out of all the points in the area. A label is important, a big circle with a number in it is the worst out all the options discussed. My issue with Google Maps is that there is no visual indicator that there are other points there, and that seems to be largely driven by the fact that it is a marketing platform.

I'm working on a map that uses a hybrid approach. Each map has a narrow focus and is tied to a particular community/interest: concerts, bear sightings, hostels, food trucks, whatever you want. For each point of focus, there is a label and a thumbnail. Showing a bunch of these all in the same place is a bad user experience, so it ranks them and shows the most important one, and the thumbnail is replaced by a number indicating there are other points of focus in the vicinity. Users can click on the item to get a side panel that shows a listing of all the points.

There are also other points on the map that are secondary to its focus, public transportation vehicles and other location points that the user can filter. These are displayed as little dots, similar to the example that the author provides. If you zoom in far enough, they become more than just dots.

In designing the user experience, I tried to make it like a map experience that you might find in a strategy game. Each focus point is like a unit that will bring up more information in a side panel. If there is more than one unit there, show an overview of the units. It's a work in progress, but I'm happy with the result so far.

It is not that agents can't function with a large context window, they can if that information generally has a desirable signal (like a large initial document or a well-focused session). Mistakes and the confusing signals that come out of fixing mistakes are why performance degrades. I start to trust the context window less not as a matter of size but the amount of friction we run into. The friction can be random but it is more often an issue with the path that I have us on.

I can understand wanting to minimize your interaction with LLMs, so this might not be an attractive solution. But it seems like a worthwhile feature to have on the platform level for people who would like to continue to accept pull requests without the frustration.

https://en.wikipedia.org/wiki/The_Mountain_in_the_Sea

- I asked Claude a question about an obscure game for which there wasn't a lot of discussion or information on the web. It couldn't find the answer but it found the source code and was able to figure it out and give a complete response.

- I needed to make some edits to a minified lottie file (json that is used to produce an animation in svg or other formats). ChatGPT was able to understand the file well enough to make the edits and reproduce the rest of the content exactly as it was.

- I was working on some map features and I needed to take geolocation information and position HTML elements on the edges of a container that would indicate which direction from the current location they were. This required a lot of geometry and math that account for rotation and pitch and would have taken me some time to work through, but it was just a few seconds for the language model and it worked perfectly.

- I have some petunias that I haven't managed to kill and I heard that when a stem breaks off they can be replanted. I asked it how to do this and after warning me that selling these could constitute a black market, it helped me start several petunia plants that are thriving. My petunias are basically immortal now.

I empathize with the astroturfing concern, I file almost every statement released by Anthropic/OpenAI as bullshit. But they are an amazing tool given the right circumstances.

It's a really valuable feature that I expect will eventually be the gold standard, it was surprising how helpful it was. I think a lot of creators will embrace it, it adds credibility/authenticity. You aren't just labeling the AI content, you are labeling the content that isn't generated by AI, with a validation layer to back it up.

Every online video platform should let you label specific segments as AI generated, even better if it is a requirement with validation checks for certain kinds of content.

It has been a long time and now I feel like I should revisit it to see if that still holds.

The ideas in this work are not entirely unique or original, they fit with what many people have been saying since language models came on the scene. But it is the most articulate, earnest, and balanced that I have seen from prominent figures and institutions. It has helped me discover and question my biases. Humanity desperately needed a better champion in the conversation, and it is moving to see the Church step into that role so effectively.