I’m a big fan of the strict naming as an abstraction above tables and reuse as blend key approach, it also greatly simplifies aggregate resolution like you have. (Landed on the same abstraction level when building a semantic model personally).
Lots of 404s on the docs pages - might be worth an audit of links?
Thanks for the heads up. I do have a specific question on your implementation. We were thinking about launching a semantic layer as a service api. You post your model and we give you fast query generation. You can then use this in your own tools. Benefits are a fast expressive semantic layer, model hosted, and your actual data stays behind your firewall. What do you think of this?
Data is the remaining moat! (Though I LOVE the amount of accessible public data and WASM has really lowered the barrier to performant data driven UIs (webgl here though? Maybe it’s just agents), so not advocating for more moats, enjoying all the cool products )
I actually agree with your point overall, but Falcon 9 uses the Merlin, not the newer raptor 3 for starship which is more 3d printing and has had some teething issues (no definite causation, and I expect they’ll get it sorted).
I mean it was a pretty classic hype cycle - MCP was massively inflated, the blowback was also inflated, and now we're in the happy state where there are same cases where it's genuinely better and differentiated and everyone will keep iterating on it. (statelessness was a big step forward).
I took inspiration from Pokémon Go, Monster Hunter Now, and even Fatal Frame (lol).
For example: You need five distinct photos of a cat before the app will guess its age, which is also just what the model needs, since age settles at about five samples. You get XP for finding new cats, and also for shooting from a distance: the score rises with how far back you stood, so using the 3× is the legitimate way to earn it and walking up to the animal isn't.
Card designs unlock per cat, as your relationship with it deepens and there are five card designs across five cat levels.
Trading exchanges cards, not cats as the animals never leave your collection. Because a card carries the fingerprint of the photo on it, it doubles as a treasure map: find that cat in the wild yourself and the app tells you it's the one from the person you traded with.
Didn't want to overcomplicate it (it's a side-project), so there's no server and no global fingerprint registry which means no race to find a cat first. It's built around building a relationship with the cats, and hopefully finding them a forever home.
Continued on my urban tree mapping kick from the last few months - it's continued to be a good way to stress test other projects of mine [3]. I've given it a new shiny landing page [1] so I can work on SEO a bit, I'll need to do a facelift on the data explorer to bring it in line stylistically.
I'm pivoting from adding more sources to data quality - as I've tried to vet some of the city sources I'm finding fun things (Cambridge, MA, USA merges in trees from Harvard, and some are straight duplicates with slight offsets, lots of places have trees in the middle of the road, many locations are address level instead of tree level). Now trying to leverage aerial photography to drive some QA, which has been a fun area to explore!
As a huge duckdb fan, I'd love to see chDB to get proper windows support - that would make it real competition (having WASM coverage is already a big step) which would be good for the space as a whole.
Am also curious on this! Though if it’s great now I’d need a sustained period of consistency (let’s say six months) before I try it again - the rollercoaster of getting a new randomized feature and quality experience every week got old pretty quick. (And I felt bad for recommending it to a few people at the time based on a good week)
Lots of 404s on the docs pages - might be worth an audit of links?
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