It's a fair theory. I think coding is so pivotal, or scary, because it starts to prove these things can write or fix themselves. I'm still not sure whether it's impressive, depressing, or scary.

Just answering questions is a glorified Ask Jeeves.

Hmm not sure if it means it can self-improve itself exactly. It feels like a lot of variables involved there and often the code produced is just an approximation of an existing requirement / something in the training data.

But yeah, I’m not quite sure what the end goal of l this research is supposed to be either. Seems like we’re not acting very intelligently on many fronts.

In an ever-evolving AI landscape, data moats have become increasingly important. Companies that possess large amounts of generated human content, such as Microsoft's acquisition of GitHub, are likely to see an increase in value as a result of this development. The unique data generated by these platforms can give companies an advantage in training and fine-tuning AI models, potentially allowing them to stay ahead of the competition. In this context, a data moat serves as a protective barrier against competitors, ensuring that the company continues to hold a unique and valuable asset in the industry.