This is a completely different scenario than what the article suggests, which is that EVs are some kind of medicine for climate change that society is trying to have discipline about. Not so. It's a life or death situation for the auto industry, they don't have a choice. They either join the race or die. This makes most concerns about the transition irrelevant. For example, laws banning gasoline cars by 2035 are as useful as laws banning flip phones by 2015 would have been.

Green solutions are part of the continuing decentralization through technology and will be just as popular in developing countries as in first world countries. One practical example of this is that green tech can be financed in bite-sized chunks, compared to the large commitments needed for power plants.

I'm sure the companies themselves understand that much, and understand a variety of the tradeoffs involved with the way they hire. What they might not understand is that they are at the exploitation stage of their lifespans. There's an entropy-like process as a company matures and cycles through its workforce which leads it to becoming highly specialized.

My bet is these companies don't understand the various ways in which they're limited, and therefore the ways in which they're limited in filtering candidates. And even if they did, they couldn't really hire any other way now even if they wanted to because they don't have the internal diversity for it, that possibility has long since closed on them.

I think it's entirely possible to memorize algorithms superficially. These types of interviews are selecting for exactly the type of person that is good at that rote memorization, and are otherwise selecting for a very narrow type of skillset.

It's unreasonable to not expect pathological outcomes with such a rigid system, especially when some people are themselves specialized for the ability to game social systems. Nothing is free. There are always trade offs when choosing one approach over another.

https://www.youtube.com/watch?v=dpmXyJrs7iU

One of the consequences is that companies become more specialized and lose deep expertise. To put it bluntly, its because they no longer have people with deep expertise, and even when they do they are ignored by management who tend to be less interested and knowledgeable about the subject matter.

I don't know of any company that has tried to prevent this. It's a general force that permeates everything, including recruiters, HR, their job postings, etc. So even companies that think they're preventing it probably still walk right into it regardless.

Of course, specialization is not necessarily good or bad. In a very competitive environment the company may not have a choice.

[1] https://www.youtube.com/watch?v=S1nc_chrNQk&t=380s

The point of the higher scale isn't just more data, it also makes it easier to solve the unbalanced data problem, because rarer and rarer scenarios will appear in large enough numbers to work with.

The lidar/no lidar discussion is a fun one because people have different ideas about how the world works. Personally I think LiDAR is the modern version of expert systems. It appeals to a logical/geometric intuition but the approach is brittle to real world contact, especially when paired with HD maps which are a great way to drive yourself into a local maximum.

It's important to distinguish between specialist/generalist roles versus specialist/generalist people. Most of FAANG is hiring specialists people for both roles. That's my sense of it anyway.

The company also has a lot of hubris. They spend tons of effort on things like trying to make healers and tanks fun. There's many good reasons to do that and they gave it a good try, but the conclusion should have been: we aren't able to make healers and tanks fun, let's try something else. Instead, they forced people to play them.

Other mistakes include not understanding "the meta." Once they think the meta is balanced in a game, they get conservative and don't want to tweak things too much. They don't realize that the meta is an equilibrium state found by the players. Change the game, a new meta will be found. They don't seem to get this and just let their games run stale because they think the competitive scene drives the player base, instead of the other way around.

Overall the facepalm factor has been too high for too long. Blizzard has always understood the science of game design, but since at least SC2 they lost the art.

* Prodigies which happen to be good in a field related to what their parents are good at. Often the wording used indicates a memory-like reason. For example, finding the rules of chess "familiar."

* Embeddings in machine learning, which allow encoding of high-dimensional information in a low-dimensional space. This would imply that humans have a somewhat-shared embedding space at some "layers". It's interesting to wonder how similar this space would be across various animals, as it would effectively be an evolved language.

* Other more subtle things, like the "cultural memory" of a society.

One question would be what types of time scales these memories survive across. Maybe some forms of instinct are deep memories that have been directly encoded in DNA.

The Nikola founder probably thought Musk had succeeded in unlocking a series of successful tricks, and set out to reproduce them. But when you don't know the reason for the formula, you don't know what steps you can leave in or out, so you just follow it mechanically.