It’s immaterial to Apple if I stole an iPhone from the Apple Store too.
> Also, he said that he's somehow stumbled into somehow having a commercial bottling license. If him, why not us?
Because he is a commercial bottler who is sampling from different supplier that he intends to source from for his business.
If you have thousands of resources in GCP, for example, the search is not super helpful.
People visiting for a few days go with a “10 restaurants you have to try in Portland” which are just mediocre chic restaurants you can find in every other city. They don’t realized how underrated Asian food in Portland is. Google Maps and Yelp reviews are negative signals of for Asian food.
Any posts on the internet archives to understand the history ?
And Pokémon cards because this generation has less ability to afford big purchases like a house or having a child
Github/Gitlab would be a provider of the filesystem.
The problem is app developers like Google want to own your files.
https://endtimes.dev/why-your-website-should-be-under-14kb-i...
Photography and hobbyist drones are easy enough to control, and I would expect a manual passenger drone to follow that consumer model.
This website was from/for an era where you hotlink the scripts.
SaaS can provide “open core” or better yet simply sell a hosted version of their fully open source code. If the provider fails to provide, you can fall back to self hosting.
The API equivalent would be open sourcing the data. This is the OpenStreetMap model. If the API provider fails to provide, you can fallback to the underlying data.
I’m wondering if Apple Maps is doing something similar where they set a low official limit that they can walk back on / to in the future, as to avoid legal responsibility
It is someone's quarterly performance review and OKR to improve SLO. One such SLO is average load time. If you set such metrics as a goal, and financially reward people to do it, it's easy to meet the goal: arbitrary prune out the long tail, especially if the distribution of saved locations per user follows an Pareto/power law distribution.
They've since rolled back that experiment of payload sized limit, and instead used this number based limit. I guess it makes more a cleaner explainaton and internal documentation from a product sense this way as opposed to an arbitrary engineering limit.
The issue is still apathy and laziness from the engineers... they can have this per-request limits, but cache previously loaded pinnned locations, then incrementally append more to the list on subsequent requests. Instead, they attempt to reload the source of truth from the server everytime. There is a specific behavior where I see this is the case: they will load 3,000, you add another location which is now 3,001 locally, but after a few minutes they reconcile with the server and your local machine is back to 3,000. This is especially ironically considering the Google interview's emphasis on Dynamic Programming and building up a larger solution from previous solutions...
On Desktop, you can still load all your locations. There is some weird and intuitive behavior here how they reconcile edits to existing pin. The caveat on Desktop is that they will entire to render entire regions when there is too much (somewhere in the vicinity above 3,000 but below 8,000). I've noticed in recent weeks they've rolled out a quadtree implementation where in a given rectangular region, they'd limit and cap how much saved locations they attempt to render, versus before where it would be seemingly depth-first until they reach the 3,000 limit.
These limits wouldn't be an issue if Google Maps API actually allowed fetching saved list features.
[1] https://www.reddit.com/r/GoogleMaps/comments/1cfqk52/did_i_j...
[2] https://techissuestoday.com/google-maps-limits-entries-into-...
[1] https://www.reddit.com/r/GoogleMaps/comments/1cfqk52/did_i_j...
k12 was created by industrialists who wanted obedient workers and well behaved citizens who won’t cause crime and instability in the ruling class’ assets.
School prepares workers, not the actual people changing the world.
Most high school grads will know more about how the mitochondria is the power of the cell, more so than know about taxes and personal finance. That’s by design.
People here who are judging people based on their high school accomplishments must be coming from a sheltered middle class background.
I remember a time when pure tech and traditional companies alike were hiring to expand their data engineering teams.This was during the Hadoop and Spark era when people would implement data transformation and business logic in code.Have low-code/3rd party SaaS since replaced this space or have most companies realized they aren’t getting much value out of data science and abandoned these BigData...
It feels like OP question stems from a belief that all there is to training a good model is throwing lots of compute at it. As with any product, there’s polishing and fine tuning you need to do, both before and after travel. Google can’t do that. You also have to accept imperfection and clever tricks to this end, a.k.a. the startup / hacker mentality, which Google is also not positioned to do. I think Meta has a good chance though
https://pkg.go.dev/html/template
Which is based on top of text/template.
The latter are ramen and other cheap eats, excluding shokudo. One “boutique” ramen shop owner has told me it was not cost effective to buy a ticket vending machine. I guess you have to be at a particular scale and throughput to have a ticket vending machine. And restaurants that optimize for throughput are usually not the best ones. Again unfortunately.
Then izakayas menus are in Kanji and even Japanese people have trouble ordering at times. That’s kind of the experience and point though.
Regarding QR code based menus, I’m curious whether you’ve experienced bad implementations. I live here, traveled all 47 prefectures maybe 3 times over, and have used dozens of digital menu implementation. There’s only been 1 or 2 that were smooth, but they were not ubiquitous. The face-to-face business / sales culture here means the tech products that spread are not necessarily the good ones.