An AI Generated ‘Theory of Everything’
They already create art, literature and soon entire movies. Why not math and scientific theories?
Watch this: https://www.youtube.com/watch?v=PdfFRlabohg
by astronut Aug 21, 2022 11 Comments 10 Links
#ai, #artificialintelligence, #cosmology, #math, #maths, #openai, #physics, #science, #space, #theory, #understanding, #universe,
They already create art, literature and soon entire movies. Why not math and scientific theories?
Watch this: https://www.youtube.com/watch?v=PdfFRlabohg
by robbiesanders Oct 5, 2024 4 Comments 4 Links
#exercise, #health, #healthylifestyle, #immortality, #livelong, #science,
It’s happening already, read this: “A theory of everything, a grand unified theory of physics and nature, has been elusive for the world of Physics. While unifying various forces and interactions in nature, starting from the unification of electricity and magnetism in James Clerk Maxwell’s seminal work A Treatise on Electricity and Magnetism [8] to the electroweak unification by Weinberg-Salam-Glashow [9-11] and research in the direction of establishing the Standard Model including the QCD sector by Murray Gell-Mann and Richard Feynman [12,13], has seen developments in a slow but surefooted manner, we now have a few candidate theories of everything, primary among which is String Theory [14]. Unfortunately, we are still some way off from establishing various areas of the theory in an empirical manner. Chief among this is the concept of supersymmetry [15], which is an important part of String Theory. There were no evidences found for supersymmetry in the first run of the Large Hadron Collider [16]. When the Large Hadron Collider discovered the Higgs Boson in 2011-12 [17-19], there were results that were problematic for the Minimum Supersymmetric Model (MSSM), since the value of the mass of the Higgs Boson at 125 GeV is relatively large for the model and could only be attained with large radiative loop corrections from top squarks that many theoreticians considered to be `unnatural’ [20]. In the absence of experiments that can test certain frontiers of Physics, particularly due to energy constraints particularly at the smallest of scales, the importance of simulations and computational research cannot be underplayed.”
No doubt DeepMind is working on it. It seems to have cracked the structure of the protein and other complex relationships, the whole shebang is likely next on the cards.
https://www.deepmind.com/blog/alphafold-reveals-the-structure-of-the-protein-universe
An AI Generated ‘Theory of Everything’
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(4 upvotes)I’m linking to this. its a good place to start with regards to how Artificial Intelligence will solve our problems for us, probably by removing us alongside our problems.
!Crack AI and you’ve cracked EVERYTHING!
One of the reasons A.I. has been so successful at solving games,” Dr. Thaler said, “is that games have a very well-defined notion of success.” He added, “If we could define what success means for physical laws, that would be an incredible breakthrough.
“In the recent past, neural networks have also helped in determining heavy quarks as well as identifying electrons [76]. We can use deep learning to solve Schrodinger’s equation, to find the ground state energy [77]. There is a growing need to turn noisy and large data sets into meaningful information as we try to increase our ability to prepare and control increasingly complex quantum systems experimentally. It is in this area that we can utilize machine learning, such as the use of algorithmic learning and Bayesian methods for Hamiltonian learning [78], to classify quantum states [79] and to characterize unknown unitary transformations [80]. Reconstruction of the Hamiltonian to identify an accurate model for quantum system dynamics, extracting information on unknown quantum states and engineering quantum gates with pairwise interactions, using both time-independent and time-dependent hamiltonians, are all better done using artificial intelligence.”
Great video you posted. Adding it as a link to others can see how the video explains how AI will take more of the work of our hands, even with creativity and understanding the Universe.
Steven Weinberg, called it “a troubling thought” that humans might not be smart enough to understand the final Theory of Everything. “But I suspect in that case,” he wrote in an email, “we will also not be smart enough to design a computer that can find a final theory.” — MORE HERE https://mindmatters.ai/2020/12/can-a-powerful-enough-computer-work-out-a-theory-of-everything/
Careful now! Behold the hawk in the chair. AI could undo us. Talking XXX rather than Science.
Good point. The late Stephen Hawking thought that computers would replace humans and was alarmed by the prospect. According to Overbye, Hawking had been warning that computers would start to replace physicists in particular since 1980. Advocates believe they have now found a tool for the job:
Their tool in this endeavor is a brand of artificial intelligence known as neural networking. Unlike so-called expert systems like IBM’s Watson, which are loaded with human and scientific knowledge, neural networks are designed to learn as they go, similarly to the way human brains do. By analyzing vast amounts of data for hidden patterns, they swiftly learn to distinguish dogs from cats, recognize faces, replicate human speech, flag financial misbehavior and more.