It loses flexibility and readability for others, but you don't usually have enough time to concern yourself with such flexibility if you're working on a project by yourself, and you're not concerned about onboarding other developers and having them understand your code. The upshot is then that as a single person "bad code" is often highly effective code, and "clean code" is expensive code that buys you a lot of stuff you don't need or want.

I say this as a boring enterprise developer who at work is highly concerned with appropriate abstractions etc. imo there's no universally good approach, what is optimal is context dependent. Although there are some core features of code like consistency and strong conventions which are fairly universally helpful, this represents a small fraction of best practices.

Dependency on cloud AI models is, in effect, dependency on VC subsidy. From the user's point of view, this dependency is debt which will either be repaid with interest to a model provider or through the hard work of making themselves independent of such models after having become dependent.

The issue that I see is that Nvidia etc. are incentivised to perpetuate that so the open source community gets the table scraps of distills, fine-tunes etc.

We can't assume that a computer based neural network will have the same emergent behaviours as a biological one or vice versa.

The interesting point for me is in the neuroplasticity, because it implies that the networks which are specialised for language could start forming synapses which connect them to the parts which are more specialised to play doom giving rise to the possibility that this could be used for introspection

I think once they're able to put 15 million such neurons on a single device that puts them in the range of more relatable animals like mice and Syrian hamsters, and I also expect that relatability is also what will drive most opinions about consciousness.