I'm going for a similar strategy, rather with exclusive national distributors, any chance I could know more about how exactly you executed your partnership's creation?
Like, cold outreach with a pitch then a doc saying more, what would you recommend to be in the doc now that you have that experience and how did you filter and find your potential partners?
Could be over email too if you prefer.
How could the gps position and the park boundary not be exact? Phones GPS give a 2 meters accuracy, and a park boundary is a well defined hard line polygon.
Being close to the border changes nothing, I can just add a buffer outwards the park polygon to account for that.
Asking because I'm afraid I may be missing something here due to this being something I already worked on.
Well I already pointed out that if you're within a couple meters of the boundary, you won't have good confidence because of this fact.
>and a park boundary is a well defined hard line polygon.
Is it? I'm no expert on parks, but surely some of them have borders along rivers. Many US states have such borders.
>Being close to the border changes nothing, I can just add a buffer outwards the park polygon to account for that.
That doesn't account for the 2m accuracy. What if I'm standing exactly 1m from the boundary when I take the photo? You have no idea if I'm really in the park or not from the GPS data.
I also have serious doubts about your 2m accuracy claim, based on personal experience. Maybe if you're standing in a wide-open desert with nothing around you, but anywhere else, the accuracy isn't that great, especially around buildings. GPS accuracy is terrible in cities.
Anyway, the requirement is for determining if a photo was taken in a park or not. The resolution wasn't stated, however: just how accurate do we need to be? If I'm in a canoe in a river that borders a park, but the river isn't part of the park, but the shoreline a few meters away is, our algorithm might claim I'm in the park, when I'm really not. The requirement wasn't "somewhere near a park", but "in a park". Rivers change their courses over time, so some polygons aren't going to accurately describe this border.
Let's be real, GPS is much more accurate than whatever boundary for the national park that someone might come up with, where the park starts is really ambiguos unless there's a physical man made divisor like a fence.
If you need to know 100% that the bird is in the park at that precise moment it can be tricky. If you need to identify a Bird-of-prey in the Alpha quadrant you can understand the Klingon proverb a sharp knife is nothing without a sharp eye.
About displaying the vector tiles, which project goes well with it?
I like Leaflet and worked extensively with it, but it has some compatibility problems with vector tiles and other small issues when dragging vector tiles for example.
Is Maplibre the gold standard for vector tiles now?
Oh hey I really love writing great docs, of course not always I have the opportunity to do so, but could you point me to one you consider great?
Can be anything, no need to be some modern live docs.
I want to see what is in the past that was so great but we lost, maybe I can incorporate some of it.
How do you handle the minimum denominator issue that is invariably present in all cross platform tools? In other words, what are the sacrifices you made in each platform to make it all work? And why each of these specifically?
Skip isn't a minimum denominator framework. With Skip, you write normal iOS code. So you legitimately make zero sacrifices to your iOS app.
Now of course Skip can't have complete Android coverage for every iOS framework - far from it. So if you use something on the iOS side that has no Android coverage, you have to create a separate code path for Android, where typically you'll utilize an equivalent Android framework/function. Skip has several mechanisms for integrating Android code, including being able to call Kotlin and Java API directly from your Swift. These mechanisms are also how you can differentiate parts of your Android app as desired, and how we create our own cross-platform libraries.
Exact accuracy depends on the domain and tasks. Processing emails will naturally have higher accuracy than 150+ pages of private credit documents. Generally, we see 95%+ accuracy out of the box and can go up to 99%+ with fine-tuning, and human in the loop validation.
Nice that you mentioned it. Just a few weeks ago I didn't even know abstract syntax trees, AST's, existed, and I had that exact experience in order to build some stuff that works with them.
Like, cold outreach with a pitch then a doc saying more, what would you recommend to be in the doc now that you have that experience and how did you filter and find your potential partners? Could be over email too if you prefer.