zlacker

>>vforgi+(OP)
Imagine thinking that regression based function approximators are capable of anything other than fitting the data you give it. Then imagine willfully hyping up and scaring people who don't understand, and because it can predict words you take advantage of the human tendency to anthropomorphize, so it follows that it is something capable of generalized and adaptable intelligence.

Shame on all of the people involved in this: the people in these companies, the journalists who shovel shit (hope they get replaced real soon), researchers who should know better, and dementia ridden legislators.

So utterly predictable and slimy. All of those who are so gravely concerned about "alignment" in this context, give yourselves a pat on the back for hyping up science fiction stories and enabling regulatory capture.

>>srslac+I7
What do you think about the papers showing mathematical proofs that GNNs (i.e. GATs/transformers) are dynamic programmers and therefore perform algorithmic reasoning?

The fact that these systems can extrapolate well beyond their training data by learning algorithms is quite different than what has come before, and anyone stating that they "simply" predict next token is severely shortsighted. Things don't have to be 'brain-like' to be useful, or to have capabilities of reasoning, but we have evidence that these systems have aligned well with reasoning tasks, perform well at causal reasoning, and we also have mathematical proofs that show how.

So I don't understand your sentiment.

>>chaxor+hB
I just don't get how the average HN commenter thinks (and gets upvoted) that they know better than e.g. Ilya Sutskever who actually, you know, built the system. I keep reading this "it just predicts words, duh" rhetoric on HN which is not at all believed by people like Ilya or Hinton. Could it be that HN commenters know better than these people?

>>uh_uh+8E
Maybe I'm not "the average HN commenter" because I am deep in this field, but I think the overlap of what these famous experts know, and what you need to know to make the doomer claims is basically null. And in fact, for most of the technical questions, no one knows.

For example, we don't understand fundamentals like these: - "intelligence", how it relates to computing, what its connections/dependencies to interacting with the physical world are, its limits...etc. - emergence, and in particular: an understanding of how optimizing one task can lead to emergent ability on other tasks - deep learning--what the limits and capabilities are. It's not at all clear that "general intelligence" even exists in the optimization space the parameters operate in.

It's pure speculation on behalf of those like Hinton and Ilya. The only thing we really know is that LLMs have had surprising ability to perform on tasks they weren't explicitly trained for, and even this amount of "emergent ability" is under debate. Like much of deep learning, that's an empirical result, but we have no framework for really understanding it. Extrapolating to doom and gloom scenarios is outrageous.

>>agento+lu1
I'm what you'd call a doomer. Ok, so if it is possible for machines to host general intelligence, my question is, what scenario are you imagining where that ends well for people?

Or are you predicting that machines will just never be able to think, or that it'll happen so far off that we'll all be dead anyway?

>>Number+Ky1
So what if they kill us? That's nature, we killed the wooly mammoth.

>>henryf+6C1
I'm more interested in hearing how someone who expects that AGI is not going to go badly thinks.

I think it would be nice if humanity continued, is all. And I don't want to have my family suffer through a catastrophic event if it turns out that this is going to go south fast.