Visions of Future Physics
quantamagazine.org
quantamagazine.org
A much more sober approach was put forth by David Gross in the article "And Gross, who considers naturalness a murky concept, simply wants a last-ditch search for new physics. “We need more hints from nature,” he said. “She’s got to tell us where to go.”
This is the reality of particle physics right now: we have a theory that works for pretty much all the measurements we've made, but it's not particularly elegant. There are big questions certainly (like dark matter) but we have no particle physics data to really study there. Particle physicists like elegant theories (b/c they learned and loved Maxwells equations) and therefore aren't satisfied with correct physics.
Definitely agree with Gross. It's why the loss of species, destruction of our environment, etc--replaced with mechanisms that are a reflection of ourselves--is all so disturbing. We are depriving ourselves of the potential to learn from the unique diverse world around us.
Certainly, the apparent fact that we can only know our own perceptions (images of observations) severely limits what we can know about the larger universe that may contain our perceptions. It would be foolish to believe that you know the ultimate reality; we already know that it is impossible to know since we can only ever access perceptions of the projections of "reality". Either all that exists is our perceptions, or we can never know the ultimate reality.
If we look at the technological changes of the preceding 30 years, anything we started in 1985 and finished in 2015 would likely be eclipsed by modern capabilities.
Should I work on Physics, or General AI, or IA? It seems that GAI or IA solve the other two.
Let's say you are 23 now and contemplating going to grad school to do particle physics. The hypothetical 100 TeV collider is not even at the stage the LHC was in the late 80s, but let's be very optimistic and assume that it will be ready to light up in only 25 years. You'll be 48 by then, and most likely long gone from academia (since there are next to no jobs). That should answer your question.
[1] e.g., https://en.wikipedia.org/wiki/Aristotelian_physics
[1] http://infoproc.blogspot.com/2008/07/annals-of-psychometry-i... ... In addition to evidence such as the long periods of time before simple understandings like natural selection, the heliocentric model, and constant acceleration of gravity were developed.
>A.I could run experiments by itself if it is provided with enough information to do so. Classical physics (already possible) and even quantum physics, once fully understood can be programmed. There are already scores of algorithms and computer programs that can run physics experiments and it doesn't take years. You seem to be misinformed about even present technological capability
> Computer simulations aren't slow. Distributed computing and processing power allow for a considerable number of experiments to be simulated.
If you work in this area, I feel you have a totally different view of things. You can either speak in terms of 'x' isn't possible and end it there or say 'x' is possible and I'm going to discover how.
1. How do you expect AI to create these simulations? Will it program it itself? I assume that the answer is yes, if so a. it needs to know how to program. b. it needs to know how to efficiently use the hardware that it can access. c. it may need to know all the quirks of the software, hardware and operating system that it works with. d. it also will need to have a pretty good math skills
Someone will need to teach AI how to do all of that or it will need to learn by itself.. This will take time.And experience.
Such AI will need to run the simulation it created, analyze it, compare results, come up with a hypothesis, and do it all over again to refine the results. What if there is a wrong assumption about fluid dynamics that is caused by some wrong assumptions on a lower level, i.e theory of matter. How will that change the results and will AI need to go back a step lower to "fix" our understanding of matter? what if there are some issues with math that first need to be "fixed", or totally new math theories must first be created?
Of course AI will not need to have everything perfect, right from the beginning, and better theories will suffice, but to say that long-term experiments such as this, are not necessary simply because AI will solve physics is just wrong.
Imagine if you didn't have to convince anyone else to fund your experiments.
Woah, Yudkowsky takes really long to get to the point, doesn't he? So his point seems to be, that humans aren't very efficient in processing empirical evidence, and an AI might be better at this, because it would be really, really smart?
Not that all this is to say advances in AI will automatically guarantee wonderful new physics, much less a final theory explaining it all, but it seems really unlikely that massively improved cognition (through AI or other means) wouldn't lead to much faster progress on all sorts of problems. We're certainly not making optimal use of our observed data about the world, and even if that was the bottleneck, AI should be better at collecting and correlating more data at once anyway. The LHC already relies on machine learning to sort through the massive number of collisions and detections being produced, so the recent experimental advances are basically reliant on AI as it is.
Also : https://www.youtube.com/watch?v=NM-zWTU7X-k It's good to keep all sorts of working ideas/knowledge in your head when you're working towards solving a problem. All the physics experiments in the world aren't going to give you insight into problems unless you have workable ideas for how to integrate the findings into understanding/knowledge.
What people often error in is that you can keep hacking away at and brute force your way to knowledge/understanding ...
“A theory can be proved by experiment; but no path leads from experiment to the birth of a theory.” — Albert Einstein
Ancient philosophers solved a lot of problems. More than you seem to be giving credit to. It's from their ideas that people knew where to look to 'prove' things. Watch the Feynman video and truly grasp what he is saying.
That's why you need both. You can't solve physics just by thinking about it, and you can't solve it just by doing experiments. And "solving physics" may also involve solving math, chemistry, philosophy and even linguistics (after all "the new physics" may not be describable in our own language, and AI will need to come up with a creative way to explain it to us)
EDIT> Why couldn't a GAI talk to every living physicist, at the same time? Read all the literature we've every written, and find links that we didn't notice?
It will be able to run experiments, but that will take a lot of time, and many iterations of hypothesis/experiment/evaluation. My point was: Many super-AI thought experiments assume that the AI is able to come up with new ways to manipulate the physical world (or humans) just by thinking about it, without running experiments. This is a flawed idea.
> Why couldn't a GAI talk to every living physicist, at the same time? Read all the literature we've every written, and find links that we didn't notice?
It would still have to run experiments in an effort to falsify its hypothesis, otherwise there's no way to be sure of its correctness.
Implying you're going to make single-handed advances on any of those things?