4,588 karma · joined October 27, 2009
> In stark contrast, the modeling abstraction is about identifying what should leak and leveraging it! It exposes the fine-grained actions and orderings, and proves that invariants hold despite the interleavings. The payoff for this work is to harvest the maximum safe concurrency from the system.
I guess I don't understand the argument here because those just sound like two different flavours of the same custard to me; the difference is just the balance of work you're doing on each side of the interface, and that decision depends on use cases specific to the project.
This feels more like it's making a point about system design? Abstraction is abstraction - you can apply it at different levels within a project, and a big part of building skills in software development is in learning to zoom in and out and nail the abstraction at each stage, but ultimately you're doing the same thing over and over. I don't personally think we need categories of it.
etc.
What a time to be alive
I suspected also that kids in such situations are learning by example, so it's a double whammy of neglect and bad habits
Are schoolchildren in the US still required to recite the pledge of allegiance...?
Hyperfocus for example can be highly beneficial if you manage to point it in the right direction, and in general neurodivergence tends to specialise either into explorers or exploiters, that is, those who are good at exploring the space of possible solutions, and those who are good at applying a specific solution to solve the problem at hand. Such skills can be problematic in isolation (as you've described), but in combination can be very powerful and could've therefore been instrumental to our past success as a species.
I understand this is not much comfort for an individual who is struggling, but I second the GP in saying that many modern societies are not setup to provide the best environment for the neurodivergent among us to thrive, to the detriment of everyone.
I guess they mean total non-exhaust particulates.
> "The impact of AI is getting undeniable", so, the goalposts are "the impact of AI". Probably something like "the impact of AI is high, or will be soon".
those are not goalposts - that's an incredible vague 'goal'. What are we moving here exactly?
Actually, I'm really an LLM and this whole thing was a clever bluff.
In recent years, I have commonly seen the phrase "you're moving the goalposts" deployed by the "it might be sentient" crowd to shoot down the "it's a stochastic parrot" crowd when the latter respond to a new development with "OK but...". In a well-understood field of inquiry, that would be a clear case of goalpost-moving, in the commonly-understood meaning of the phrase where requirements are retroactively changed in response to them having been met. Thank you OP. 'Artificial Intelligence', and indeed intelligence in general, is very much not a well-understood field of inquiry - in fact we don't even have a common agreement about what 'intelligence' is. We are therefore learning as we go (even after all this time!) but making rapid progress in recent years. When rapid progress is made in a poorly-understood field, then how can our definitions and requirements for success not change? This is arguably one of the most pathological development projects ever - what are the requirements? 'It thinks like a human'? What does that mean? And the answer is we don't know what that means, and we're working it out as we go - moving the goalposts. If we didn't move the goalposts, then by definition we already knew exactly where we were headed at the beginning, and we very clearly did not.
Side note that, in case it's not obvious, none of this detracts from how impressive LLMs are. They're a marvel of the modern age, all the problems notwithstanding. However I reserve the right to stay sceptical about their capabilities.
That's not what I said.