itsalwaysgood

I would say it's not intensity alone, but intensity towards a vision. Working hard by itself is never enough, but working hard to create something valuable, that only you can see requires intensity.

A lot of people don't realize they want something until they've seen it. So founders have intensity, and vision for a need only they can see.

Imagine that slow-paced DMV with a lot of intensity, but towards nothing at all. In that case, the vision should be efficiency (without burning out employees).

These are all great points but I'd also point out that the 'dark age' scenario is a highly competitive scenario, while the 'golden age' scenario is a highly collaborative one.

I don't think technology will fizzle out in either scenario. In the 'dark age' highly competitive scenario, you will still have those who 'understand what is produced' seeking progress and advancement. They will cohort with whoever/whichever organization is producing the best, most validated results.

I don't think knowledge would be become alien to human understanding, it would just become highly concentrated again as it was in the past. In the past, only the wealthy and noble could afford to spend time on education.

And usually, those who went deep into any field and provided contributions to science were those who had time to devote entire lives to the study or pursuit of knowledge. We still have these issues today, and these issues will always be present.

There is a supply chain of economy, and we provide different rewards based on the value of what is produced. The jobs never go away, the desire for prestige, greed, etc., never goes away. It's why economies exist, and it's why everyone is considering the value of LLMs, and their place in economies, and academies (presumably which exist to advance human understanding/appreciation, but also to prepare younger generations for future work).

Completely unrelated, but it's so odd to see upside down '8's in the first column of the base tables on their pricing page.

This is the best attitude to have about the current state. Unless you have some dramatically different sensible solution (and you probably don't when it comes to technology, because it seems to spread for reasons that would eliminate other sensible solutions) that will catch on and take over and replace AI: it's going to continue to mature as long as it's mostly useful to everyone. And AI isn't even a new industry, it has been maturing for quite a while, which adds more weight to the argument that having an attitude that adapts to technology (unless you wish to go solo) is a 'better' fit.

The dramatic solution can never be: 'we should all just want to do it this way because it felt better to me'. That never seems to work, from what I've seen. So there is a lot of public discourse, arguing, to determine if 'doing things the old way' is perhaps more better. And if not, maybe we just shed a tear and move on (to look for a better fit).

I get you. What people are doing now is questioning value: in themselves, and what they can create for others. I hate to always oversimplify things but we're pretty simple things to begin with:

Social creatures that share a common space, with finite time that nobody wants to waste.

I don't think it's the communication that's lost, it's the motivation. People love to collaborate, but they don't always want to waste time doing it.

It's the same reason you see 'no AI' repo labels: only by forcing some standard on the community can the 'old way of collaborating' continue to exist.

There will for sure be new ways of collaborating, and walled off gardens like you suggest, where communication stops and everyone just shares some final product.

But, in some cases the product must be understood (or demonstrated) before value can be derived, and so collaboration will still exist.

Desire, and the 'shape' of collaboration has changed greatly though. Why collaboration has changed, is a completely separate issue related to economy and how each of us spends our time.

Desire and motivation are factors to consider. Would you want to invest 5 years of effort into solving the Hypothesis 'the old way', knowing someone is probably working on it right now with AI?

And then once it's solved by AI: do you want to churn through the proof to understand it? What if it takes you 5 years to churn through the proof, and it turns out someone made a mistake with AI (I have no idea what would be realistic amounts of time, but the idea is still worth considering).

The issue is very complex, and you will always be hungry.