AI 2023. Meet ChatGPT. - page 207
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You didn't read the last paragraph carefully:
"Scientists have concluded that AI has a chance to show people previously unknown drivers of nature and push new conclusions that are likely to change both science and our view of the world."
And this is already now, and what will happen in three years, when heterogeneous AI systems, for example, will unite (link) in a single complex, which will be able to find new patterns, investigate them and then report the results.
And in six years, or nine years?
There is a very long list of discoveries in science that have been made without the use of experimentation. Experiments can only confirm or disprove a theory, but are not a prerequisite for discovery.
1. Isaac Newton's theory of gravity: Newton developed his theory of gravity based on observations of the motion of planets and other bodies in space by doing only theoretical calculations and analyses.
2. Relativity theory and the space-time continuum: Albert Einstein proposed his theory of relativity based on philosophical speculation and mathematical equations rather than direct experimentation.
3. Electromagnetic Waves and Maxwell's Equations: Maxwell developed equations describing electromagnetic waves, their propagation and interaction using theoretical analysis despite the lack of proof through experiment.
Discoveries in all areas of science and technology will appear more and more, in an avalanche, as AI capabilities grow. And this is despite the fact that independent AI capable of making decisions is still a long way off. This will lead to even greater acceleration in the development of technology and techniques. And the emergence of truly independent AI ready to make decisions (we are not talking about intelligence) will be led by man himself, who is striving to give robots with AI more and more autonomy.
The main thing is to print hands with the right number of fingers out of powder :)
But the breakthrough of robotics in trading has already happened
There is a serious brake on AI development, which I wanted to talk about further. Practicality.
True but it can learn . Will be expensive , but it will learn .
Furthermore it's evolution differs from ours . This is your main point that the human engineer must decide on the limbs of the machine , their structure , their strength max etc.
Whereas humans , there were a lot of "dice rolls" and the dominant setup won.
Theres another difference however . Once one of the machines that are similar learns something then they all learn it at once. It's like when Usain Bolt manages to run that fast the next day all humans can run that fast.
Imagine that in a warfare scenario . If you remember the film with Tom Cruise where he repeated the same battle over and over again , if an army of robots is interconnected , and , one falls and has time to transmit what happened then in real time the rest of the armed force instantly improves on the battlefield .
(1)True, but he can learn. It will be expensive, but he will learn.
(2)Also, his evolution is different from ours. This is your main point, that the human engineer has to decide the machine's limbs, their structure, their maximum strength, etc.
Whereas humans have had many "rolls of the dice" and the dominant attitude wins.
However, there is another difference. (3)As soon as one of the similar machines learns something, they all recognise it at once. It's like if Usain Bolt could run that fast, and the next day all humans could run that fast.
Imagine this in a war scenario. If you remember the Tom Cruise film where he replayed the same battle over and over again, if an army of robots are interconnected and one goes down and manages to relay what happened, then in real time the rest of the armed forces are instantly improved on the battlefield.
1. In the context of our discussion, AI learning is about assimilating experimentally verified facts and making connections between them. Anything above that is virtual modelling requiring separate experiments and evidence. Hypothetically, we can assume that AI will match scientists in knowledge of scientific fields, but without practical experience, will only be able to surpass them in virtual modelling and making assumptions. In actual and provable knowledge, AI won't be able to surpass scientists until it conducts experiments on its own. Experiments, however, do not take place at a fantastic speed and require serious preparation.
2. In the context of our discussion, "AI Evolution" looks like a branch of humanity's scientific and technological development, but not an independent natural phenomenon. However, evolution presupposes not only creation but also destruction of the "evolved". If AI is let "out in the wild", we can assume with high probability that it will quickly disappear without any development. The reason is that it is not adaptable to physical conditions. It's not enough to invent limbs. It is necessary to realise a method of autonomous reproduction of robots with a working algorithm of successive improvement of production technology, and only then will "evolution" begin. By the way, this topic is devoted to the theoretical study of this very question. We are trying to answer whether autonomous reproduction is possible in principle. According to the laws of physics, if you will. Personally, I am sceptical about it, while some participants consider it quite probable.
3- This claim is debatable. The point is that in a sci-fi scenario, a single powerful control centre (AI) is more efficient than many independent robots learning something. After all, each particular robot, due to the limited size of its "brain", will not be able to cope with assimilation of the broadcasted experience of thousands of other autonomous robots. We need a single analytical centre of incoming data, but then the other robots are just puppets. However, in my opinion, these considerations are too hypothetical and ignore the lion's share of harsh realism. Therefore, I will not continue them.))))))
1. In the context of our discussion, AI learning is about assimilating experimentally verified facts and making connections between them. Anything above that is virtual modelling requiring separate experiments and evidence. Hypothetically, we can assume that AI will match scientists in knowledge of scientific fields, but without practical experience, will only be able to surpass them in virtual modelling and making assumptions. In actual and provable knowledge, AI won't be able to surpass scientists until it conducts experiments on its own. Experiments, however, do not take place at a fantastic speed and require serious preparation.
2. In the context of our discussion, "AI Evolution" looks like a branch of humanity's scientific and technological development, but not an independent natural phenomenon. However, evolution presupposes not only creation but also destruction of the "evolved". If AI is let "out in the wild", we can assume with high probability that it will quickly disappear without any development. The reason is that it is not adaptable to physical conditions. It's not enough to invent limbs. It is necessary to realise a method of autonomous reproduction of robots with a working algorithm of successive improvement of production technology, and only then will "evolution" begin. By the way, this topic is devoted to the theoretical study of this very question. We are trying to answer whether autonomous reproduction is possible in principle. According to the laws of physics, if you will. Personally, I am sceptical about it, while some participants consider it quite probable.
3- This claim is debatable. The point is that in a sci-fi scenario, a single powerful control centre (AI) is more efficient than many independent robots learning something. After all, each particular robot, due to the limited size of its "brain", will not be able to cope with assimilation of the broadcasted experience of thousands of other autonomous robots. We need a single analytical centre of incoming data, but then the other robots are just puppets. However, in my opinion, these considerations are too hypothetical and ignore the lion's share of harsh realism. Therefore, I will not continue them.))))))
1. Yeah in essence , while in the "gan" stage , if any scientific discovery in the latent space that is on par with the global science levels is useful it will find it . The question is , when the "music" ai makes music , it is music but it does not mean it is pleasant . So the burden is on humans to verify indeed . For now it will "dicsover" what we could have discovered in other words .
3. Good point , the cost would be insane
After watching Matt Wolfe's video about the "Suno" song neuron in the neighbouring Mijorney thread, I realised that the music industry is slowly and surely going down the drain. If you haven't seen it, check it out.
...
Painting is dying, music is dying. We don't know what's in store for us. Let's try to understand further...
The crisis of painting and music was visible years ago, when they were still alive. Today, endless generations are turning the once high art into mockery, with all the traits of meaningless consumption. A kind of "gluttony" ... But I won't go into metaphors.
The market lives as long as there is demand. Demand gives birth to supply. Everyone knows the rule - no demand - no supply. There will be no more mass demand for painting, and there will be no more demand for music.... It's enough to say "AI, make me a song with this motive and meaning" or "draw me a picture like this". Free of charge. No labour.
The market is over as soon as it becomes a dumping ground for cheap products. That's what's happening.
I'm not in favour of pessimistic scenarios, but it's not clear how to avoid it.