Future superintelligences could steal minds to cure “past sufferings” and to prevent s-risks, and to resurrect all the dead. These is actually a good thing, but for the resurrection of the dead they have to run the whole world simulation once again for last few thousands years. In that case it will look almost like normal world.
avturchin
Karma: 1,945
Quantum immortality of the second type. Classical theory of QI is based on the idea that all possible futures of a given observer do exist because of MWI and thus there will be always a future where he will not die in the next moment, even in the most dangerous situations (e.g. Russian roulette).
QI of the second type makes similar claims but about past. In MWI the same observer could appear via different past histories.
The main claim of QI-2: for any given observer there is a past history where current dangerous situation is not really dangerous. For example, a person has a deadly car accident. But there is another similar observer who is night dreaming about the same accident, or who is having much less severe accident but hallucinate that it is really bad. Interestingly, QI-2 could be reported: a person could say: “I have memory of really bad accident, but it turn out to be nothing. Maybe I died in the parallel world”. There are a lot of such report on reddit.
Agreed. Superhuman levels will unlikely be achieved simultaneously in different domain even for universal system. For example, some model could be universal and superhuman in math, but not superhuman in say emotion readings. Bad for alignment.
Why it lengthens your timelines?
If we use median AI timings, we will be 50 per cent dead before that moment. May be it will be useful different measure, like 10 per cent of TAI, before which our protective measures should be prepared?
Also, this model contradicts naive model of GPT growth in which the number of parameters has been growing 2 orders of magnitude a year last couple of years, and if this trend continues, it could reach human level of 100 trillion parameters in 2 years.
Interestingly, an hour in childhood is subjectively equal between a day or a week in adulthood, according to recent poll I made. As a result, the middle of human life in term of subjective experiences is somewhere in teenage.
Also, experiences of an adult are more dull and similar to each other.
Tin Urban tweeted recently: “Was just talking to my 94-year-old grandmother and I was saying something about how it would be cool if I could be 94 one day, a really long time from now. And she cut me off and said “it’s tomorrow.” The “years go faster as you age” phenomenon is my least favorite phenomenon.”
I reread the post and have some more questions:
Where is “human values” in this model? If we give this model to an AI which wants to learn human values and have full access to human brain, where it should search for human values?
If cortical algorithm will be replaced with GPT-N in some human mind model, will the whole system work?
Thanks. I think that a plausible explanation of dreaming is generating of virtual training environments where an agent is training to behave in the edge cases, on which it is too costly to train in real life or in real world games. That is why the generic form of the dreams is nightmare: like, a lion attack me, or I am on stage and forget my speech.
From “technical” point view, dream generation seems rather simple: if the brain has world-model generation engine, it could generate predictions without any inputs, and it will look like an dream.
I have several questions:
Where are qualia and consciousness in this model?
Is this model address difference between two hemispheres?
What about long term-memory? Is it part of neocortex?
How this model explain the phenomenon of night dreams?
For Marx, capitalism was Moloch, and communism was a solution.
For Unabomber, the method to stop Moloch was the destruction of complex technological society and all complex coordination problems.
Predictive world model?
Maybe I am too late to comment here and it is already covered in collapsed comments, but it looks like that it is possible to make this experiment in real life.
Imagine that instead of copying, I will use waking up. If I win, I will be waked up 3 times and informed that I won and will be given a drug which will make me forget the act of awakening. If I lose, I will be wakened only one time and informed that I lost. Now I have 3 to 1 observer moments where I informed about winning.
In such setup in is exactly the Sleeping beauty problem, with all its pro and contra, which I will not try to explore here.
EY suggested (if I remember correctly) that MWI interpretation of quantum mechanics is true as it is simplest explanation. There are around hundred other more complex interpretations of QM. Thus, in his interpretation, P(MWI) is more than a sum of probabilities of all other interpretations.
It means that p(one of them is true) is more than p(simplest explanation is true)
Two types of Occam’ razor:
1) The simplest explanation is the most probable, so the distribution of probabilities for hypotheses looks like: 0.75, 0.12, 0.04 …. if hypothesis are ordered from simplest to more complex.
2) The simplest explanation is the just more probable, so the distribution of probabilities for hypotheses looks like: 0.09, 0.07, 0.06, 0.05.
The interesting feature of the second type is that simplest explanation is more likely to be wrong than right (its probability is less than 0.5).
Different types of Occam razor are applicable in different situations. If the simplest hypothesis is significantly simpler than others, it is the first case. If all hypothesis are complex, it is the second. First situation is more applicable some inherently simple models, e.g. laws of physics or games. The second situation is more about complex situation real life.
It looks like that you think that modal realism is false and everything possible doesn’t exist. What is the argument which convinced you in it?
We can make a test on computer viruses. What is the probability that a random code will be self-replicating program? 10^50 probability is not that extraordinary—it is just a probability of around 150 bits of code being on right places.
There are more than 1 million households in US which have 10 mln usd capitalisation, and they could afford such travel without damaging their wealth. No all will go, but may be a 10 thousand a year will. This gives 1 billion a year for tickets and they will spend at least the same amount on the Moon. So it is 2 billion dollar a year tourist economy. Not much.
We can estimate apriori probability that some sequence will work at all by taking a random working protein and comparing its with all other possible strings of the same length. I think this probability will be very small.
Another way to describe the same (or similar) plateau: we could think about GPT-n as GLUT with approximation between prerecorded answers: it can produce intelligent products similar to the ones which were created by humans in the past and are presented in its training dataset – but not above the human intelligence level, as there is no superintelligent examples in the dataset.