Future Timeline

Yuli Ban,

Fair points, though keep in mind that automation will lower the costs of goods and services, so even if humans lose their jobs and get poorer, it will be easier to afford things.

If people will be poor even though we are going to experience +20% GDP a year, then it certainly must mean some grave mistakes in govervance. But I don't think that will be the case, at least not for long. People will vote for getting some of the wealth created by machines. And technological deflation is going to make everything cheaper, so if government keeps printing money, people will be able to afford things.

Tadasuke wrote: ↑Tue Sep 06, 2022 8:51 pm If people will be poor even though we are going to experience +20% GDP a year, then it certainly must mean some grave mistakes in govervance. But I don't think that will be the case, at least not for long. People will vote for getting some of the wealth created by machines. And technological deflation is going to make everything cheaper, so if government keeps printing money, people will be able to afford things.

Digital currency should help bring some balance to all this. Possible actual peace and stability with this? Let's find out!

Nanotechandmorefuture wrote: ↑Wed Sep 07, 2022 12:26 am

Tadasuke wrote: ↑Tue Sep 06, 2022 8:51 pm If people will be poor even though we are going to experience +20% GDP a year, then it certainly must mean some grave mistakes in govervance. But I don't think that will be the case, at least not for long. People will vote for getting some of the wealth created by machines. And technological deflation is going to make everything cheaper, so if government keeps printing money, people will be able to afford things.

Digital currency should help bring some balance to all this. Possible actual peace and stability with this? Let's find out!

So far, cryptocurrencies have shown exceptional instability.

Yuli Ban wrote: ↑Sat Sep 10, 2022 7:52 pm

The impression I get is that on top of an immediate boost to AI ability e.g. making GPT-4 better THE % RATE THAT AI GETS BETTER HAS NOW BEEN INCREASED. Is this correct and will the increase to the % rate of AI improvement translate to getting AGI faster or will it only effect language models?

Hey everyone. I've seen some talk recently that there is an impending slowdown in AI research. Basically the reasoning goes: we picked the low hanging fruit in terms of optimizing hardware for AI training, by doing things like reducing precision in custom silicon (google TPUs for example). But the bigger problem is that we've reached the upper limit of what people are willing to spend training models. So a lot of the progress was driven by the fact that AI was hyped up and companies were willing to spend huge money to train their models. For example, it is thought that GPT-3 took over $10 million to train. The argument is that this exponential investment in training new models wont continue, so AI will once again be limited to increasing at the same speed as general purpose hardware improvements (Moore's law).

I'm curious to hear people's opinions about this. Do you agree with that reasoning, or is there some hope that we can continue to see the blistering progress in AI research that we have enjoyed in the past decade? I certainly hope that it will continue to improve, because I had great fun playing with Stable Diffusion (an image generator) all weekend long. However, the limitations of the software definitely has me itching to get my hands on something that is a bit more capable.

Not a particularly major step forward, but a fantastic showcase of the new scaling laws. 17B optimized parameters vs 80B unoptimized ones for Flamingo; 17B wins overwhelmingly.

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