https://www.youtube.com/watch?v=5RpPTRcz1no&t=67s&pp=ygUQZGF...

I have started double checked with web searches more and more. It went from 100% of the time to only 20%

https://man7.org/tlpi/ This book is considered the best overview of linux kernel interface. Its old, but still gives a broad coverage of topics.

https://lkml.org/ Browsing LKML is really helpful since it shows you where current development is happening and how kernel devs think. Some conversations get very advanced and nuanced.

https://kernelnewbies.org/ is a good starting place for starting to compile and deploying kernel builds

Other than that, reading and tracing the source is probably the most productive thing to do for an experienced dev to do

Re-writes are also needed when the architecture doesn't match the problem space well. This can be incrementally done. Single threaded loops instead of using parallel-safe constructs like tasks and jobs.

This is going to be the biggest problem with general AI chat systems in the future, inconsistency. Often, they are too complex to know precisely how they work. Small tweaks will break some use cases while improving others. As more complexity is added to fix the next series of bugs, the systems will become less effective overall while user's have their workflows broken then mysteriously fixed.

From the end-users perspective, consumers will lose trust and move on.

1980 after the foundations of neural networks, but it was too computationally intensive to be useful

2009 with Watson

https://www.hiig.de/en/a-brief-history-of-ai-ai-in-the-hype-...

Its easy to imagine that previous generation tracking devices that sends its information across a broader range than an airtag will need to be larger battery thus being larger.

A better comparison would be the Twitter user that was tweeting Elon Musk's jet flights. This was before twitter was purchased, and Elon Musk was not able to get the court to order Twitter to hand over that information.

Its entirely possible that an update to self-driving car's algorithms cause a day of chaos as the self-driving cars lose control and crash. Worst case scenario.

I agree that the secondary effects of the ML systems are going to be far worse than the primary. We can only see how it goes.

Other than that, good insights from someone that works with self driving cars

If western countries with a similar birth rate problem stopped immigration, would western countries have a similar economic outlook as Japan?

The React team has done a great job of being generic enough for a broad range of use cases. As new use-cases arise, someone can build a new framework to support it. SSR has gotten much more popular than the SPA style, and the core React team has moved to support it with server side components.

If they can continue to follow the innovators, React will continue to dominate the front end landscape.

Processes -> Threads is the same improvement that Nginx had over Apache, and its pretty clear that Nginx is the preferred web server these days. Also, Nginx's configuration system is much better, so it's hard to say why they have won out so clearly