4 ms·
> The current GPT models are not going to "wake up" or accidentally take over the world. This is very obvious. It's pretty obvious that GPT-4 isn't consistentl
by ekidd 4y ago
> The current GPT models are not going to "wake up" or accidentally take over the world. This is very obvious.
It's pretty obvious that GPT-4 isn't consistently coherent enough to carry out complex plans or to do serious scientific research. There are several other major shortcomings which also prevent this from being viable, too. And of course, it's possible that some of these shortcomings are very hard to "fix." We've had AI winters before, and self-driving seems to have stalled.
However, I strongly suspect that it's theoretically possible to build a machine that "thinks" as well as a human. And I no longer have any solid idea how far we are from that point, especially if we make certain architectural changes. We might be closer than we think. Or at least we should stop assuming that next-gen models are obviously safe.
nVidia's hope to increase training performance 1 million times in 10 years seems potentially dangerous to me. Anthrophic's plan to spend over $1 billion training next gen models seems awfully sketchy as well.
- pixl97 4y agoSelf driving, I think is where we got it backwards. To drive correctly we need AGI because 'uncommon' but not 'rare' events are avoided by drivers all the time and in a manner you have to understand how the world works and how people think. LLMs, especially the multi-modal ones go much further to making self driving possible, that is if we ever get to the point they can incorporate and act on data fast enough. We may still have a hardware problem for some time there. --- But on your second point I am with you. There is nothing obvious about at what level emergent behavior occurs in the models. Just keep adding parameters and new things keep popping out with no real means to determine where and when seems kinda sketch as we push these things past the exa scale.
- xvilka 4y ago> However, I strongly suspect that it's theoretically possible to build a machine that "thinks" as well as a human Not any time soon. Modern "AI" research built on completely wrong assumptions about how neurons work from the middle of XX century. It turned out they are much more complex than that (long story short every single neuron is analogous to the "neural network" as AI researchers understand them). See more at https://www.youtube.com/watch?v=hmtQPrH-gC4 https://www.youtube.com/watch?v=hmtQPrH-gC4
- kiratp 4y agoWhy would you think that the machine implementation of “thinking” would need to mimic the biological implementation? Your brain does 1+1 = 2 very differently than an integrated circuit, but the end output is the same.
- xvilka 4y agoBecause it shows that real brain complexity is much larger than we thought, which means AGI is farther down the road.