Fire is a natural and necessary part of many ecosystemsm. It keeps parasitic insect populations down, stuff like ticks and chiggers, and some plant species rely on fire to prepare the soil for seeds and even is required for some plants to release their seeds. In dry ecosystems like the western USA it also consumes old dead plant material, reducing the fuel available for future fires and reducing fire severity overall. Many foresters and fire fighters advocate for increasing prescribed burns, essentially forest fires that we light on purpose in cooler and wetter times of the year to consume the fuel without risking a catastrophic fire that is difficult to control. I just think that’s neat.

Long ago the four nations lived in harmony. But everything changed when the business nation attacked. Only the regulations could stop them, but when the world needed them most, they vanished.

They didn’t have zero experience. There were two full rocket designs that were built and flown before rocket 3, hence why it was called rocket 3. It also achieved orbit successfully two times, which only a limited number of companies have ever achieved.

The first offer wasn’t rejected, they didn’t have the money on hand at the time. Between the first offer and the second they got investor funding together and the cash on hand dwindled, so the second offer was with cash to cover the offer and some to cover running the business between acceptance and closing. After the second offer the board released a statement saying it’s this or liquidate the company, so they went with this because it’s the best outcome for everyone with the current state of things.

Memory unsafe languages will always have value in applications where speed and performance mean anything. Embedded programming and video games are the obvious examples, but pretty much any application taken far enough will eventually demand the performance benefits of memory unsafe languages. Some even require writing assembly directly. Contrary to common dogma, the compiler isn’t always best.

Business majors are ruining the world one quarter at a time.

Doubt. These large language models can’t produce anything outside their dataset. Everything they do is derivative, pretty much by definition. Maybe they can mix and match things they were trained on but at the end of the day they are stupid text predictors, like an advanced version of the autocomplete on your phone. If the information they need to solve your problem isn’t in their dataset they can’t help, just like all those cheap Indian call centers operating off a script. It’s just a bigger script. They’ll still need people to help with outlier problems. All this does is add another layer of annoying unhelpful bullshit between a person with a problem and the person who can actually help them. Which just makes people more pissed and abusive. At best it’s an upgrade for their shit automated call systems.