The problem with these bromides is not that they're wrong, it's that they're not even wrong. They're predictive nulls.

What observable differences can we expect between an entity with True Understanding and an entity without True Understanding? It's a theological question, not a scientific one.

I'm not an AI booster by any means, but I do strongly prefer we address the question of AI agent intelligence scientifically rather than theologically.

- clear generalizability

- insane growth rates (go back and look at where we were maybe 2 years ago and then consider the already signed compute infrastructure deals coming online)

And still say with a straight face that this is some kind of parlor trick or monkeys with typewriters.

we don’t need to run LLMs for years. The point is look at where we are today and consider performance gets 10x cheaper every year.

LLMs and agentic systems are clearly not monkeys with typewriters regurgitating training data. And they have and continue to grow in capabilities at extremely fast rates.

Alternative perspective: the science may not have been ready, so instead we brute-forced the problem, through training of LLMs. Consider what the overall goal function of LLM training is: it's predicting tokens that continue given input in a way that makes sense to humans - in fully general meaning of this statement.

It's a single training process that gives LLMs the ability to parse plain language - even if riddled with 1337-5p34k, typos, grammar errors, or mixing languages - and extract information from it, or act on it; it's the same single process that makes it equally good at writing code and poetry, at finding bugs in programs, inconsistencies in data, corruptions in images, possibly all at once. It's what makes LLMs good at lying and spotting lies, even if input is a tree of numbers.

(It's also why "hallucinations" and "prompt injection" are not bugs, but fundamental facets of what makes LLMs useful. They cannot and will not be "fixed", any more than you can "fix" humans to be immune to confabulation and manipulation. It's just the nature of fully general sytems.)

All of that, and more, is encoded in this simple goal function: if a human looks at the output, will they say it's okay or nonsense? We just took that and thrown a ton of compute at it.