Fr I was about to say the same thing. Aside from better hardware and more layers the technology really hasn’t changed from this level to begin with.
We’ve learned a little about what emergent behavior and trends look like in machine learning algorithms when graphed, though: it becomes more and more convergent, as if it forms its own little confirmation bias it will produce more and more samey results.
Rebranding a Markov Chain stapled onto a particularly large graph
Could you elaborate how this applies to various areas of AI in your opinion?
Several models are non-markovian. Then there are also a lot of models and algorithms, where the description or even comparison to Markov-chains would be incorrect and not suitable.
I’m not sure what people think AI was ever going to be… every time something new comes out it’s always dismissed because “it’s basically just a X that does Y”. I think that will continue to be the case until there is some literal connection to actual brains, in which case the concept of what a brain is will probably be questioned as well.
I’m not sure what people think AI was ever going to be…
The heavy investment in AI is coming under the assumption that these advanced processes will replace huge portions of the human workforce.
So we don’t need lawyers, because we just put prompts into a Law AI and it gives us a verdict. We don’t need doctors, because we just put symptoms into a Medical AI and it gives us a diagnosis and treatment plan. We don’t need salespeople, because we just put the product into a Marketing AI and it spits out a bunch of comvincing ad copy.
the concept of what a brain is will probably be questioned as well.
We already connect our brains to our computers. We just use screens and keyboards as our interface.
I suppose you could argue that a guy with a calculator or a camera or a chat app is mentally different than one without it. But I think the goal with AI is supplementing human minds, not complementing then.
So much of the drift has just been marketing. Rebranding a Markov Chain stapled onto a particularly large graph as Master Computer from Tron.
Fr I was about to say the same thing. Aside from better hardware and more layers the technology really hasn’t changed from this level to begin with.
We’ve learned a little about what emergent behavior and trends look like in machine learning algorithms when graphed, though: it becomes more and more convergent, as if it forms its own little confirmation bias it will produce more and more samey results.
Could you elaborate how this applies to various areas of AI in your opinion?
Several models are non-markovian. Then there are also a lot of models and algorithms, where the description or even comparison to Markov-chains would be incorrect and not suitable.
I’m not sure what people think AI was ever going to be… every time something new comes out it’s always dismissed because “it’s basically just a X that does Y”. I think that will continue to be the case until there is some literal connection to actual brains, in which case the concept of what a brain is will probably be questioned as well.
The heavy investment in AI is coming under the assumption that these advanced processes will replace huge portions of the human workforce.
So we don’t need lawyers, because we just put prompts into a Law AI and it gives us a verdict. We don’t need doctors, because we just put symptoms into a Medical AI and it gives us a diagnosis and treatment plan. We don’t need salespeople, because we just put the product into a Marketing AI and it spits out a bunch of comvincing ad copy.
We already connect our brains to our computers. We just use screens and keyboards as our interface.
I suppose you could argue that a guy with a calculator or a camera or a chat app is mentally different than one without it. But I think the goal with AI is supplementing human minds, not complementing then.