Romario77
Joined 1 year ago
Joined 1 year ago
Second was about licensing and Apache Harmony.
So, eventually they dropped most of the big things that were planned - Project Lambda with closures, Project Jigsaw with modularisation, Collection Literals. They eventually came back, but took a while to implement, so it was a prudent decision to make.
They had to commit to half a year release cycles and LTRs every 2 years. Since then the releases became a lot more predictable. Whatever is not ready is not released (or is there as a preview feature).
This more agile approach is a lot better in my experience and we see that the changes made are more relevant and what people actually want.
Java tried to do fairly large updates and sometimes the release cycle would be very unpredictable as things would slip and take much longer than anticipated.
So to make it more predictable and to keep updates coming they switched to 6 months cadence with long term support (LTS) every two years.
This I think is a pretty good way of doing things, makes people who plan things figure out how to split feature development into these 6 months cycles, it made JEPs more granular and I think it made project Valhalla possible, if they tried doing it the old way it would never happen.
Splitting things in small chunks clarified what needs to be done and the path forward. It still takes very long time, but doesn't cause big incompatible changes and I think overall Java has good progress without being stalled.
second - main idea is about proportions, if you want to design apps that seamlessly transfer from one screen to another they have to have the same proportions of the sides. This is not a given and depends on the height and width.
If you take iPhone 18 Pro resolution : 2,622 x 1,206 doubling it would make the screen with 2,622 x 2,412 - almost a square screen.
They chose to have the folded phone to have 1.4:1 aspect ratio which is consistent when folded and when unfolded.
Professor says the assistants - why don't you dig in this direction, I have a hunch it might produce something valuable. And AI assistant does just that, proving or disproving a hunch. This would take the professor a lot of time if doing by themselves.
And according to them at some point they saw that one was close to being solved, so they pointed all the agents at it.
The same thing happens to humans - at this time there are no simple problems left, so solving the hard ones requires using prior knowledge and attempts at solving things.
6.5 billions paid, nothing so far, this was such a sus transaction, sounded like the way to get money out of OpenAI.
At least before it would listen to instructions like this.
1 Å = 100 pm. 1 pm = 0.01 Å.
xAI overbuilt their data centers - they can't find paying customers for them, that's the reason they made deals with other companies like Google to use their own datacenters.
Cursor has the opposite problem of not having enough capacity. So this works well for them together.
Weather it's worth it - if you beleive that AI will solve every problem then having a piece of the pie early on might be worth it.
Remember how when google bought youtube for 1.65 billions people thought they are crazy? Or when facebook bought instagram.
60B is a crazy number but might be worth it for someone fighting for world dominance :)
This makes it so an update to a popular library can compromise a huge number of packages that depend on it.
In Java for example almost all packages specify a concrete version, even if someone compromises the latest the blast radius is usually pretty small.