A team of theoretical physicists working with Microsoft published an amazing research paper today that describes the universe like a system itselflearningof evolutionary laws.
In other words: We live in a computer that learns.
The big idea: Το επιχείρημα προσομοίωσης του Bostrom είναι ένα καυτό θέμα στους επιστημονικούς κύκλους τον τελευταίο καιρό. Η έρευνα ονομάζεται "The Autodidactic Universe," και δημοσιεύτηκε σήμερα στο arXiv. Εκτείνεται σε 80 σελίδες και παρουσιάζει μια νέα θεωρία των πάντων.
Η έρευνα υποστηρίζει ότι οι νόμοι που διέπουν το σύμπαν είναι ένα εξελικτικό σύστημα μάθησης. Δηλαδή το σύμπαν είναι ένας υπολογιστής και αντί να υπάρχει σε "στερεή κατάσταση", διαιωνίζεται μέσω μιας σειράς νόμων που αλλάζουν με την πάροδο του χρόνου.
How does it work; This is the difficult part. The researchers explain that the universe is a learning system, citing other machine learning systems. Just as we can teach machines to run new functions over time, the laws of the universe are essentially algorithms that work in the form of learning operations.
According to the researchers:
For example, when we see structures that look like deep learning architectures appearing in simple self-taught systems, we can imagine that the architecture of the functional matrix in which our universe evolves laws evolved from a self-taught system that emerged from minimal conditions.
When you think about it, it makes sense that the original physicist law it would be incredibly simple, self-perpetuating, and able to learn and evolve.
Ίσως το σύμπαν δεν ξεκίνησε με ένα Big Bang, αλλά με μια απλή αλληλεπίδραση μεταξύ των σωματιδίων. Οι ερευνητές αναφέρουν αυτή την ταπεινή προέλευση δηλώνοντας ότι "οι αρχιτεκτονικές πληροφοριών συνήθως ενισχύουν τις αιτιώδεις δυνάμεις μάλλον μικρών συλλογών σωματιδίων".
Scientists describe the ever-evolving laws of the universe as irreversible:
If the evolution of the laws is real, it is likely to be one-way, because otherwise it would be common for the laws to return to previous situations. This is because a new situation is not accidental, but rather it must meet certain standards, while the state of the immediate past has already met its standards.
A reversible but evolving system would accidentally explore the immediate past. When we see an evolving system showing periods of stability, it is likely to evolve in one direction.
Explaining these points, the researchers rely on the image of an IT trying to understand how a given program came to a result. In one example, the specialist could simply check the magnetic marks left on the hard drive. In this way, the results of the program are reversible: there is a history of their execution.
But if the same expert were trying to determine the results of a program by examining the CPU, that is, the entity that is responsible for executing it, it would be much more difficult to do. There is no intentional, internal recording of the functions running a CPU.
Consequences: If the universe operates through a set of laws that, although initially simple, are self-taught and therefore can evolve over time, it is impossible for humans to put these pieces together.
Σύμφωνα με αυτό το έγγραφο, οι κανόνες που διέπουν έννοιες όπως η σχετικότητα μπορεί να είχαν λειτουργικά διαφορετικές λειτουργικές συνέπειες πριν από 13,8 δισεκατομμύρια χρόνια από ό,τι θα έχουν σε 100 τρισεκατομμύρια χρόνια από τώρα. Και αυτό σημαίνει ότι η "φυσική" είναι μια κινούμενη επιστήμη.
Of course, these are all conjectures based on theoretical physics. Certainly researchers do not literally mean that the universe is a computer.
According to the study:
We examine whether the Universe is a learning computer.
Part of the theory seems to suggest that the universe is a learning computer, as the laws by which it currently operates were not set in the beginning.
Δεν μπορούμε να αντιστρέψουμε το σύμπαν σαν διαδικασία, επειδή δεν υπάρχει καμία επαληθεύσιμη εγγραφή των διαδικασιών του - except and if there is a secular cruel disc floating somewhere in space.
The research is currently a draft, but researchers are doing a lot of work describing the types of neural network algorithmic systems that could create such a universe.
The team describes this work as the first steps towards a broader theory.
