Real innovations come from constraints. The frugal AI movement is clearly where we will see interesting things emerging. Interestingly, those approaches are closer to what AI is about as a research field than the industrial complex which got unleashed with all its extractive power.

Definitely makes sense, you can be more innovative in your practices and processes than with the tech your depend on. The cost of changing is definitely not the same.

Interesting list and way to frame the problem. It's important to maintain this resource, an update is likely needed.

This is a very rich article. There's indeed more and more a rift between Open Source projects used by hyperscalers and the ones used by smaller businesses and individuals. You likely want to aim for the latter.

Indeed, innovation is far from being a linear process. It's actually messy, the breakthroughs already happened already and we describe it after the facts.

Or why it's important to deeply understand what you do and what you use. Cranking features and throwing code to the wall until it sticks will never lead to good engineering. Even if it's abstractions all the way, it's for convenience but don't treat them as black boxes.
Interestingly this article draws a parallel with organizations too. Isn't having very siloed teams the same as treating abstractions as black boxes?
Quite some food for thought here.

This is definitely a problem. It's doomed to influence how tech are chosen on software projects.

This will definitely push even more conservatism around the existing platforms. More articles mean more training data... The underdogs will then suffer.

This is another way to approach the question of having slack in your schedule. This is necessary, and probably at scale in the organization (as implied by this article).