Exploring Ruliad: The Computational Universe and AI's Future

Understanding Ruliad and Its Implications

The concept of Ruliad, introduced by Stephen Wolfram, represents a fundamental structure that encompasses all possible formal systems and computational processes. It's a vast computational universe that contains every possible rule and every possible initial condition.

Ruliad and Observer Perspective

One might wonder if Ruliad itself could be an observer. However, this notion doesn't align with our understanding of observers. The key characteristic of observers like us is that we're relatively small and integrated. Our minds, through the concept of having a single thread of experience, aren't extensively spread out. If our minds were vastly extended, we wouldn't have the same sense of coherent identity.

Exploring Ruliad

Some might suggest that exploring Ruliad could be a goal for civilization, similar to how we explore physical space. However, this approach presents a significant challenge. When you try to hold in your mind all these different potential perspectives of what's happening, you lose coherence in what you believe. You might not be able to say that you still exist coherently. In a sense, you become everything, but also nothing.

The Necessity of Limitations

The concept of coherent existence depends on there being things that represent you and many things that are not you. If you claim to be everything, in a sense, there is no 'you' in that picture. For us to have a coherent existence, we need to be limited. This idea extends to mathematics as well.

Mathematics and Coherence

In mathematics, what matters is having a finite set of axioms and then building a tower of theorems above those axioms. If you allowed all possible axioms, you could prove everything. This might seem beneficial, but it actually undermines the coherence of mathematics.

The Problem with Proving Everything

In mathematics, there's an old result in logic that once you have something you consider false, you can deduce anything from falsehood. The rules of logical implication mean that starting from a false premise, everything becomes true. At this point, you've essentially destroyed everything. You can no longer make a coherent statement in mathematics.

Coherence in Ruliad

Similarly, if you were to pass as an observer through all of Ruliad, you wouldn't exist in any coherent sense. For observers like us, this is a kind of frustration. We can't encompass everything without losing our coherent identity.

Logical Systems and Ruliad

When discussing Ruliad, questions arise about different logical systems. There's classical logic, and then there's paraconsistent logic where you can have 'A' and not 'A', but not explosion. In Wolfram's approach to Ruliad, the focus is more on a constructive approach rather than traditional logic with truth and falsehood.

Beyond True and False

Many things in the world aren't simply true or false. For example, the statement "It will rain tomorrow" is neither true nor false at the present moment - it's undetermined. In Wolfram Language, you might say "X is greater than three," but if you haven't defined X, there's nothing you can do with this statement. It doesn't have a truth value in any useful sense.

A Constructive Approach

The approach in the Physics Project and the mathematics that comes from it is all constructive. Instead of asking "What is true?", the question becomes "What can you build?" This approach avoids getting entangled in the same kind of questions about logic because there is no logic - it's just about what you can construct.

The Nature of Truth in Mathematics and the World

In mathematics, the question of what is true becomes complex when you consider the foundations. There are axioms, and given those axioms, you can deduce things. But if you change the axioms, you might be able to deduce different things. The focus shifts to what you can deduce rather than what is "true" in an absolute sense.

Physics and Existence

This is similar to questions about what can exist in the world and what physics can produce in the world. Instead of asking if the Earth is "real," we ask if the Earth exists or if it was produced by physics. Similarly, in mathematics or other ways we talk about things, we ask if something can be produced, not if it's "true" in quotes.

Progress in Science and Breaking Dogma

There are two perspectives on making progress in a field. One view suggests that you can make progress because you have fresh eyes and aren't indoctrinated with the entire history of the field. The other view argues that you need to understand the tools and gain intuition, comprehending where the field is before you can make progress.

Personal Experience and Confidence

Wolfram shares his personal experience of being right several times when challenging established ideas. This builds a certain amount of confidence that just because everyone says X doesn't necessarily mean X is true. It's a valuable realization from a personal point of view.

Types of Misconceptions in Science

Wolfram identifies different types of misconceptions in science:

1. The belief that certain problems are too difficult and will never be solved.
2. The closure of fields after technical success, leading to assumptions that may not be entirely correct.
3. The importance of the observer in deducing how science works, which wasn't always considered.

The Limits of Science and Prediction

There's a common belief that science can explain and predict everything. However, the concept of computational irreducibility challenges this notion. While we can predict certain things in specific domains, life becomes uninteresting if we can predict everything.

AI and Computational Irreducibility

The concept of computational irreducibility has significant implications for artificial intelligence. An AI that performs computationally irreducible tasks cannot be predicted, which means it can surprise us. This leads to a crucial decision:

1. Allow AI to be computationally irreducible and potentially surprising.
2. Restrict AI to behave only in computationally reducible ways, ensuring we know what it will do but potentially limiting its capabilities.

This decision is not just about AI but reflects broader societal choices about control versus allowing dynamics to play out.

The Future of AI and Society

The decision about how to approach AI development is crucial and will be important in the coming years. It's not entirely separate from decisions about economic control versus allowing market forces to play out. The question becomes: Do you move towards restriction, or do you move towards allowing dynamics to have their effect?

Completely restricting AI would mean we don't really have AI. However, finding the right balance between capability and predictability will be a key challenge as we continue to develop and integrate AI into our society.

In conclusion, the exploration of Ruliad and its implications leads us to fundamental questions about the nature of existence, the limits of knowledge, and the future of artificial intelligence. As we continue to push the boundaries of science and technology, we must grapple with these complex issues, balancing our desire for progress with the need for understanding and control.

Article created from: https://www.youtube.com/watch?v=uKsuiO_ltCQ