studies show a clear trend – output is up (more code, more commits, bigger diffs), but outcomes don’t reflect that trend. If anything, the average team is taking longer to ship worse software
studies show a clear trend – output is up (more code, more commits, bigger diffs), but outcomes don’t reflect that trend. If anything, the average team is taking longer to ship worse software
Hehehehe
The future looks… unreliable.
We all know that true AGIs becoming smarter than humans seems inevitable, but that could be like a hundred years from now, if ever. What’s unclear is what will happen two years from now, involving matters having little to do with the technology & what it is capable of and instead more to do with the economy and what jobs will be available then.
AGI isn’t possible with current or near tech. Anyone who says otherwise is huffing paint or selling AI crap.
I literally said “if ever”, and also “seems” rather than “is”. I also never so much as implied current tech, with my comment about a hundred years from now.
You are reacting against what I never said.
Though I choose to upvote your comment anyway, since at least you said it rather than simply assumed it and moved on.
Wow, what a solid argument you’ve made. It definitely doesn’t reek of someone trying to hype themselves up in the face of an unknown threat.
We invented a next token predictor. That isn’t intelligence nor is it on the path to it, either. The word rocks aren’t any closer to real intellect than the math rocks were. You just think they are cause words are the things that humans use to communicate across time and space.
The only ones spouting nonsense that it is are those whose business models require AGI to be achievable within the next decade. But, ya know, wish in one hand and all that.
That’s better, but you’re still just defining things such that you have to be correct.
Humans spend 90% of their time just predicting the next token. All we need is to mix in a little bit more reasoning and bam, AGI!
See how annoying and hollow that rhetorical technique is?
The fact is that we have no idea whatsoever. We might reach AGI next week. We might never reach AGI. The Chinese government might be sitting on AGI right now. We have no idea, and this is completely new territory that has caused us to question our very understanding of intelligence.
The problem is that you’re not arguing anything. Your first comment is an ad hominem at best, and your second is an appeal to the unknown. You haven’t argued anything.
Here, here’s my argument. LLMs are built on neutral networks. They use a ridiculous amount of compute to “simulate neurons”, but their neurons are not even a 100th of the power of an actual neuron, which is why this is a dead-end for AGI. You’ve probably seen this diagram before
And had it explained that each of the nodes in this image represents a virtual neuron. Assuming that AGI is achieved via the means we know right now, namely being human-like, then you’d probably expect creating a neural net with the complexity of a human brain, minus all the stuff needed for steering a meat-suit, would get us there.
The problem is that those little nodes are input-output machines that are ridiculously simple compared to real neurons. They take in inputs from every connection they have, based on internal weights and measures, and then they output a single value to all their output neurons. That value is a float between 0 and 1, representing some percentage of activation.
Real neurons, meanwhile, use neurotransmitters to communicate to their neighbors, not simple electrical signals. There are hundreds of those, but even if there were 10, then neural networks would be completely incapable of modeling a simple brain, let alone a human one.
Why? Because that means each of those nodes in the neural net would need 10 separate inputs and outputs connected to all their existing nodes to even come close. That’s a 100x more connections for every part of the node. And we’re currently consuming basically every chip on earth to feed to this thing, and it’s not even 1/100th the complexity needed for even a dumbed down neuron, let alone a realistic one.
15 - 30 years of pain followed by the end of life as we know it those who adapt may thrive but will continue to be exploited.
Tbf to LLM manufacturers, the end of life as we know it was coming either way.