When they’re here I’ll make an upvote farming bot that learns from experience how not to get caught and unleash it on HM.
After that I’ll make an agent that runs a SaaS company that learns from experience how to make money and I’ll finally be able to chill out and play video games.
That last thing I’ll actually do myself, I won’t use an agent, although the experience revolution stared with games. Ironic!
But I’ll make an agent that learns from experience what kind of games I like and how to make them. This way I’ll have an endless supply.
If they're not careful, they'll be sued for copyright violation of the Real Soon Now™ brand.
We just need it to get better at building agents.
With social media and the Internet, stupid just got louder. I don't think people got stupid.
Eg: https://www.popularmechanics.com/science/a43469569/american-...
Also well documented. Anyone interested, read the book: Attention Merchants by Wu.
It's not. It's just that previously we were unaware how stupid people are, and now we're starting to understand this.
It’s quite beautiful. Once a civilization tries to build machine intelligence it slowly degrades its own capacity during the process thus eventually losing all hope of ever achieving their goal - assuming they still understand their goal at that point. Maybe it’s an algorithm in the Universe to keep us from being naughty.
is it ? i am listening to most beautiful music that was ever created. it was created in 2024.
Happening right out in the open, and quite blatantly.
I’m burning out from all this hypester type of thing, it’s really really tiring.
The constant barrage of excrement makes critical thinking ever harder, which is by design (it has been proven that pumping out BS en masse is way easier than debunking it). Stop using your brain already and just buy what they tell you. Thinking is done by machines now. As is pumping out BS about how good machines are at thinking.
And they imitate the style pretty well. It's kinda funny. (I don't follow this topic closely (I clicked because I imagined something entirely different from the title), so it's the first time I see it)
As for the graph, it’s too generic, it doesn’t provide any real value, other than a certain pseudo-appeal reminiscent of paper-style visuals. In my humble opinion, it’s designed to mislead people who fall for hype, much like some of Google’s recent pseudo-scientific blog posts on machine learning.
I have deep respect for Sutton and his work, but this kind of things are a hard pass for me.
They specifically talk about this in the position paper and describe the need for a "flexible" reward function that's adaptive. It's very hand-wavy and doesn't really describe how they would do this, but there's a lot of research along these lines. "agi" is also not really the subject of the paper.
But I guess you mean this? https://www.sciencedirect.com/science/article/pii/S000437022...
"Reward is enough", David Silver, Satinder Singh, Doina Precup, Richard S. Sutton, 2021.
I think the core idea from the paper is that while we have already hit the ceiling of normal kind of data; there's a new kind of data from agents acting in the real world and users (or some one else?) providing rewards based on some ground truth.
Somehow I misinterpreted from this paper that this kind of learning would be autonomous and continuous.
Meaning we need less strong arms and more strong brains. Not something that new anyway, the "information age" already makes clear intelligent people could do pretty anything they want to do, while less intelligent are constrained in what they can actually do even if they want.
Experience means essentially automation in the chapter terms, something we have already "solved" could be automated by some machine. To solve new things we need humans. That's is.
Small potatoes new knowledge, meaning knowledge emerging merely crossing per-existing knowledge like from a literature review paper could be a machine game, it's not really creation of new knowledge in the end.
BUT the real point is another: who own the model? LLMs state a clear thing, we need open knowledge just to train them, copyright can't be sustained anymore. But once a model is created who own it? Because the current model is dramatically dangerous since training is expensive and not much exiting, so while it could be a community procedure in practice is a giant-led process, and the giant own the result while harvesting anything from anyone. The effect implied by such evolution are much more startling then the mere automation risk in Lisanne Bainbridge terms https://ckrybus.com/static/papers/Bainbridge_1983_Automatica... or short/mid term job losses.
